Compounds > 1-(2-(1-adamantyl)ethyl)-1-pentyl-3-(3-(4-pyridyl)propyl)urea
Page last updated: 2024-08-02 14:42:17
1-(2-(1-adamantyl)ethyl)-1-pentyl-3-(3-(4-pyridyl)propyl)urea
Description
1-(2-(1-adamantyl)ethyl)-1-pentyl-3-(3-(4-pyridyl)propyl)urea: structure in first source [MeSH]
Cross-References
ID Source | ID |
PubMed CID | 10158562 |
CHEMBL ID | 1210507 |
SCHEMBL ID | 504493 |
MeSH ID | M0524172 |
Synonyms (14)
Synonym |
sa-13353 |
CHEMBL1210507 |
1-[2-(1-adamantyl)ethyl]-1-pentyl-3-(3-pyridin-4-ylpropyl)urea |
sa13353 |
1-(2-(1-adamantyl)ethyl)-1-pentyl-3-(3-(4-pyridyl)propyl)urea |
NCGC00263016-01 |
[2-(1-adamantyl)ethyl]-1-pentyl-3-[3-(4-pyridyl)propyl]urea |
AIUJHENHBJHHMY-UHFFFAOYSA-N |
1-[2-(1-adamantyl)ethyl]-1-pentyl-3-[3-(4-pyridyl)propyl]urea |
SCHEMBL504493 |
379262-36-9 |
sa 13353 |
de-096 |
PD161272 |
Protein Targets (1)
Potency Measurements
Bioassays (38)
Assay ID | Title | Year | Journal | Article |
AID1347411 | qHTS to identify inhibitors of the type 1 interferon - major histocompatibility complex class I in skeletal muscle: primary screen against the NCATS Mechanism Interrogation Plate v5.0 (MIPE) Libary | 2020 | ACS chemical biology, 07-17, Volume: 15, Issue:7 ISSN: 1554-8937 | High-Throughput Screening to Identify Inhibitors of the Type I Interferon-Major Histocompatibility Complex Class I Pathway in Skeletal Muscle. |
AID1346986 | P-glycoprotein substrates identified in KB-3-1 adenocarcinoma cell line, qHTS therapeutic library screen | 2019 | Molecular pharmacology, 11, Volume: 96, Issue:5 ISSN: 1521-0111 | A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. |
AID1347091 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for SJ-GBM2 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347086 | qHTS for Inhibitors of the Functional Ribonucleoprotein Complex (vRNP) of Lymphocytic Choriomeningitis Arenaviruses (LCMV): LCMV Primary Screen - GLuc reporter signal | 2020 | Antiviral research, 01, Volume: 173ISSN: 1872-9096 | A cell-based, infectious-free, platform to identify inhibitors of lassa virus ribonucleoprotein (vRNP) activity. |
AID1347104 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for RD cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347083 | qHTS for Inhibitors of the Functional Ribonucleoprotein Complex (vRNP) of Lassa (LASV) Arenavirus: Viability assay - alamar blue signal for LASV Primary Screen | 2020 | Antiviral research, 01, Volume: 173ISSN: 1872-9096 | A cell-based, infectious-free, platform to identify inhibitors of lassa virus ribonucleoprotein (vRNP) activity. |
AID1347098 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for SK-N-SH cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347090 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for DAOY cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347101 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for BT-12 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347107 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for Rh30 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347154 | Primary screen GU AMC qHTS for Zika virus inhibitors | 2020 | Proceedings of the National Academy of Sciences of the United States of America, 12-08, Volume: 117, Issue:49 ISSN: 1091-6490 | Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors. |
AID1347105 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for MG 63 (6-TG R) cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1296008 | Cytotoxic Profiling of Annotated Libraries Using Quantitative High-Throughput Screening | 2020 | SLAS discovery : advancing life sciences R & D, 01, Volume: 25, Issue:1 ISSN: 2472-5560 | Cytotoxic Profiling of Annotated and Diverse Chemical Libraries Using Quantitative High-Throughput Screening. |
AID1347096 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for U-2 OS cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347089 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for TC32 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1508612 | NCATS Parallel Artificial Membrane Permeability Assay (PAMPA) Profiling | 2017 | Bioorganic & medicinal chemistry, 02-01, Volume: 25, Issue:3 ISSN: 1464-3391 | Highly predictive and interpretable models for PAMPA permeability. |
AID1347092 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for A673 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347094 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for BT-37 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347108 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for Rh41 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347097 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for Saos-2 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1508630 | Primary qHTS for small molecule stabilizers of the endoplasmic reticulum resident proteome: Secreted ER Calcium Modulated Protein (SERCaMP) assay | 2021 | Cell reports, 04-27, Volume: 35, Issue:4 ISSN: 2211-1247 | A target-agnostic screen identifies approved drugs to stabilize the endoplasmic reticulum-resident proteome. |
AID1347099 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for NB1643 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1645848 | NCATS Kinetic Aqueous Solubility Profiling | 2019 | Bioorganic & medicinal chemistry, 07-15, Volume: 27, Issue:14 ISSN: 1464-3391 | Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity. |
AID1347106 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for control Hh wild type fibroblast cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1508591 | NCATS Rat Liver Microsome Stability Profiling | 2020 | Scientific reports, 11-26, Volume: 10, Issue:1 ISSN: 2045-2322 | Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models. |
AID1347103 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for OHS-50 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347082 | qHTS for Inhibitors of the Functional Ribonucleoprotein Complex (vRNP) of Lassa (LASV) Arenavirus: LASV Primary Screen - GLuc reporter signal | 2020 | Antiviral research, 01, Volume: 173ISSN: 1872-9096 | A cell-based, infectious-free, platform to identify inhibitors of lassa virus ribonucleoprotein (vRNP) activity. |
AID1745845 | Primary qHTS for Inhibitors of ATXN expression | 2022 | The Journal of biological chemistry, 08, Volume: 298, Issue:8 ISSN: 1083-351X | |
AID1347102 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for Rh18 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347160 | Primary screen NINDS Rhodamine qHTS for Zika virus inhibitors | 2020 | Proceedings of the National Academy of Sciences of the United States of America, 12-08, Volume: 117, Issue:49 ISSN: 1091-6490 | Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors. |
AID1347100 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for LAN-5 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID686947 | qHTS for small molecule inhibitors of Yes1 kinase: Primary Screen | 2013 | Bioorganic & medicinal chemistry letters, Aug-01, Volume: 23, Issue:15 ISSN: 1464-3405 | Identification of potent Yes1 kinase inhibitors using a library screening approach. |
AID1347095 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for NB-EBc1 cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID1347159 | Primary screen GU Rhodamine qHTS for Zika virus inhibitors: Unlinked NS2B-NS3 protease assay | 2020 | Proceedings of the National Academy of Sciences of the United States of America, 12-08, Volume: 117, Issue:49 ISSN: 1091-6490 | Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors. |
AID1346987 | P-glycoprotein substrates identified in KB-8-5-11 adenocarcinoma cell line, qHTS therapeutic library screen | 2019 | Molecular pharmacology, 11, Volume: 96, Issue:5 ISSN: 1521-0111 | A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. |
AID1347093 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Primary screen for SK-N-MC cells | 2018 | Oncotarget, Jan-12, Volume: 9, Issue:4 ISSN: 1949-2553 | Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing. |
AID493442 | Antiinflammatory activity in po dosed Lewis rat assessed as inhibition of LPS-induced TNFalpha production administered 30 mins prior to LPS challenge measured after 1.5 hrs | 2010 | Bioorganic & medicinal chemistry letters, Aug-01, Volume: 20, Issue:15 ISSN: 1464-3405 | Synthesis and pharmacological evaluation of 1,1,3-substituted urea derivatives as potent TNF-alpha production inhibitors. |
AID493443 | Antiinflammatory activity in Lewis rat assessed as inhibition of LPS-induced TNFalpha production at 2 mg/kg, po administered 30 mins prior to LPS challenge measured after 1.5 hrs | 2010 | Bioorganic & medicinal chemistry letters, Aug-01, Volume: 20, Issue:15 ISSN: 1464-3405 | Synthesis and pharmacological evaluation of 1,1,3-substituted urea derivatives as potent TNF-alpha production inhibitors. |
Research
Studies (18)
Timeframe | Studies, This Drug (%) | All Drugs % |
pre-1990 | 0 (0.00) | 18.7374 |
1990's | 0 (0.00) | 18.2507 |
2000's | 2 (11.11) | 29.6817 |
2010's | 9 (50.00) | 24.3611 |
2020's | 7 (38.89) | 2.80 |
Study Types
Publication Type | This drug (%) | All Drugs (%) |
Trials | 0 (0.00%) | 5.53% |
Reviews | 0 (0.00%) | 6.00% |
Case Studies | 0 (0.00%) | 4.05% |
Observational | 0 (0.00%) | 0.25% |
Other | 18 (100.00%) | 84.16% |
Substance | Studies | Classes | Roles | First Year | Last Year | Average Age | Relationship Strength | Trials | pre-1990 | 1990's | 2000's | 2010's | post-2020 |
b 844-39 | | diarylmethane | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pk 11195 | | aromatic amide; isoquinolines; monocarboxylic acid amide; monochlorobenzenes | antineoplastic agent | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
pd 173074 | | aromatic amine; biaryl; dimethoxybenzene; pyridopyrimidine; tertiary amino compound; ureas | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; fibroblast growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
jtv519 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
abt 702 | | bipyridines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
alprazolam | | organochlorine compound; triazolobenzodiazepine | anticonvulsant; anxiolytic drug; GABA agonist; muscle relaxant; sedative; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dan 2163 | | aromatic amide; aromatic amine; benzamides; pyrrolidines; sulfone | environmental contaminant; second generation antipsychotic; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
amlexanox | | monocarboxylic acid; pyridochromene | anti-allergic agent; anti-ulcer drug; non-steroidal anti-inflammatory drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
astemizole | | benzimidazoles; piperidines | anti-allergic agent; anticoronaviral agent; H1-receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benzbromarone | | 1-benzofurans; aromatic ketone | uricosuric drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bicalutamide | | (trifluoromethyl)benzenes; monocarboxylic acid amide; monofluorobenzenes; nitrile; sulfone; tertiary alcohol | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bisindolylmaleimide i | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bufexamac | | aromatic ether; hydroxamic acid | antipyretic; non-narcotic analgesic; non-steroidal anti-inflammatory drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cadralazine | | organic molecular entity | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
verapamil | | aromatic ether; nitrile; polyether; tertiary amino compound | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
carvedilol | | carbazoles; secondary alcohol; secondary amino compound | alpha-adrenergic antagonist; antihypertensive agent; beta-adrenergic antagonist; cardiovascular drug; vasodilator agent | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
celecoxib | | organofluorine compound; pyrazoles; sulfonamide; toluenes | cyclooxygenase 2 inhibitor; geroprotector; non-narcotic analgesic; non-steroidal anti-inflammatory drug | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cetirizine | | ether; monocarboxylic acid; monochlorobenzenes; piperazines | anti-allergic agent; environmental contaminant; H1-receptor antagonist; xenobiotic | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
chelerythrine | | benzophenanthridine alkaloid; organic cation | antibacterial agent; antineoplastic agent; EC 2.7.11.13 (protein kinase C) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
chlorcyclizine | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ci 994 | | acetamides; benzamides; substituted aniline | antineoplastic agent; EC 3.5.1.98 (histone deacetylase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclosporine | | | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
fenbendazole | | aryl sulfide; benzimidazoles; carbamate ester | antinematodal drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
berotek | | resorcinols; secondary alcohol; secondary amino compound | beta-adrenergic agonist; bronchodilator agent; sympathomimetic agent; tocolytic agent | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
furosemide | | chlorobenzoic acid; furans; sulfonamide | environmental contaminant; loop diuretic; xenobiotic | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
go 6976 | | indolocarbazole; organic heterohexacyclic compound | EC 2.7.11.13 (protein kinase C) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gossypol | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
fasudil | | isoquinolines; N-sulfonyldiazepane | antihypertensive agent; calcium channel blocker; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor; geroprotector; neuroprotective agent; nootropic agent; vasodilator agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
haloperidol | | aromatic ketone; hydroxypiperidine; monochlorobenzenes; organofluorine compound; tertiary alcohol | antidyskinesia agent; antiemetic; dopaminergic antagonist; first generation antipsychotic; serotonergic antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
homochlorocyclizine | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hydroxyzine | | hydroxyether; monochlorobenzenes; N-alkylpiperazine | anticoronaviral agent; antipruritic drug; anxiolytic drug; dermatologic drug; H1-receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ifenprodil | | piperidines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
indirubin-3'-monoxime | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1-(2-naphthalenyl)-3-[(phenylmethyl)-propan-2-ylamino]-1-propanone | | naphthalenes | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
ketamine | | cyclohexanones; monochlorobenzenes; secondary amino compound | analgesic; environmental contaminant; intravenous anaesthetic; neurotoxin; NMDA receptor antagonist; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ketoprofen | | benzophenones; oxo monocarboxylic acid | antipyretic; drug allergen; EC 1.14.99.1 (prostaglandin-endoperoxide synthase) inhibitor; environmental contaminant; non-steroidal anti-inflammatory drug; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
leflunomide | | (trifluoromethyl)benzenes; isoxazoles; monocarboxylic acid amide | antineoplastic agent; antiparasitic agent; EC 1.3.98.1 [dihydroorotate oxidase (fumarate)] inhibitor; EC 3.1.3.16 (phosphoprotein phosphatase) inhibitor; hepatotoxic agent; immunosuppressive agent; non-steroidal anti-inflammatory drug; prodrug; pyrimidine synthesis inhibitor; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
letrozole | | nitrile; triazoles | antineoplastic agent; EC 1.14.14.14 (aromatase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
lg 100268 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mebendazole | | aromatic ketone; benzimidazoles; carbamate ester | antinematodal drug; microtubule-destabilising agent; tubulin modulator | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
mephenesin | | aromatic ether; glycerol ether | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
metformin | | guanidines | environmental contaminant; geroprotector; hypoglycemic agent; xenobiotic | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mitoxantrone | | dihydroxyanthraquinone | analgesic; antineoplastic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
entinostat | | benzamides; carbamate ester; primary amino compound; pyridines; substituted aniline | antineoplastic agent; apoptosis inducer; EC 3.5.1.98 (histone deacetylase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
niclosamide | | benzamides; C-nitro compound; monochlorobenzenes; salicylanilides; secondary carboxamide | anthelminthic drug; anticoronaviral agent; antiparasitic agent; apoptosis inducer; molluscicide; piscicide; STAT3 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
olprinone | | bipyridines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
omeprazole | | aromatic ether; benzimidazoles; pyridines; sulfoxide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
oxibendazole | | benzimidazoles; carbamate ester | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-(2'-methoxyphenyl)-1-(2'-(n-(2''-pyridinyl)-4-iodobenzamido)ethyl)piperazine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
perphenazine | | N-(2-hydroxyethyl)piperazine; N-alkylpiperazine; organochlorine compound; phenothiazines | antiemetic; dopaminergic antagonist; phenothiazine antipsychotic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pimobendan | | benzimidazoles; pyridazinone | cardiotonic drug; EC 3.1.4.* (phosphoric diester hydrolase) inhibitor; vasodilator agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pioglitazone | | aromatic ether; pyridines; thiazolidinediones | antidepressant; cardioprotective agent; EC 2.7.1.33 (pantothenate kinase) inhibitor; EC 6.2.1.3 (long-chain-fatty-acid--CoA ligase) inhibitor; ferroptosis inhibitor; geroprotector; hypoglycemic agent; insulin-sensitizing drug; PPARgamma agonist; xenobiotic | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ag 1879 | | aromatic amine; monochlorobenzenes; pyrazolopyrimidine | beta-adrenergic antagonist; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; geroprotector | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-[(3,5-dibromo-4-hydroxyphenyl)methylidene]-5-iodo-1H-indol-2-one | | indoles | | 2013 | 2020 | 7.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
riluzole | | benzothiazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ro 31-8220 | | imidothiocarbamic ester; indoles; maleimides | EC 2.7.11.13 (protein kinase C) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ropinirole | | indolones; tertiary amine | antidyskinesia agent; antiparkinson drug; central nervous system drug; dopamine agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sb 206553 | | pyrroloindole | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 220025 | | aminopyrimidine; imidazoles; organofluorine compound; piperidines | angiogenesis inhibitor; anti-inflammatory agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 202190 | | imidazoles; organofluorine compound; phenols; pyridines | apoptosis inducer; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sk&f 86002 | | imidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
imatinib | | aromatic amine; benzamides; N-methylpiperazine; pyridines; pyrimidines | antineoplastic agent; apoptosis inducer; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
vorinostat | | dicarboxylic acid diamide; hydroxamic acid | antineoplastic agent; apoptosis inducer; EC 3.5.1.98 (histone deacetylase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
sulfasalazine | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-[4-(1,2-diphenylbut-1-enyl)phenoxy]-N,N-dimethylethanamine | | stilbenoid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-[4-(4-chloro-1,2-diphenylbut-1-enyl)phenoxy]-N,N-dimethylethanamine | | stilbenoid | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
trifluperidol | | aromatic ketone | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
troglitazone | | chromanes; thiazolidinone | anticoagulant; anticonvulsant; antineoplastic agent; antioxidant; EC 6.2.1.3 (long-chain-fatty-acid--CoA ligase) inhibitor; ferroptosis inhibitor; hypoglycemic agent; platelet aggregation inhibitor; vasodilator agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
3-(5'-hydroxymethyl-2'-furyl)-1-benzylindazole | | aromatic primary alcohol; furans; indazoles | antineoplastic agent; apoptosis inducer; platelet aggregation inhibitor; soluble guanylate cyclase activator; vasodilator agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
zotepine | | dibenzothiepine; tertiary amino compound | alpha-adrenergic drug; second generation antipsychotic; serotonergic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
colchicine | | alkaloid; colchicine | anti-inflammatory agent; gout suppressant; mutagen | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benziodarone | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclizine | | N-alkylpiperazine | antiemetic; central nervous system depressant; cholinergic antagonist; H1-receptor antagonist; local anaesthetic | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
trehalose | | trehalose | Escherichia coli metabolite; geroprotector; human metabolite; mouse metabolite; Saccharomyces cerevisiae metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
triclocarban | | dichlorobenzene; monochlorobenzenes; phenylureas | antimicrobial agent; antiseptic drug; disinfectant; environmental contaminant; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-tert-octylphenol | | alkylbenzene | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ethamivan | | methoxybenzenes; phenols | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
azacitidine | | N-glycosyl-1,3,5-triazine; nucleoside analogue | antineoplastic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
methysergide | | ergoline alkaloid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
emetine | | isoquinoline alkaloid; pyridoisoquinoline | antiamoebic agent; anticoronaviral agent; antiinfective agent; antimalarial; antineoplastic agent; antiprotozoal drug; antiviral agent; autophagy inhibitor; emetic; expectorant; plant metabolite; protein synthesis inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
podophyllotoxin | | furonaphthodioxole; lignan; organic heterotetracyclic compound | antimitotic; antineoplastic agent; keratolytic drug; microtubule-destabilising agent; plant metabolite; tubulin modulator | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
formestane | | 17-oxo steroid; 3-oxo-Delta(4) steroid; enol; hydroxy steroid | antineoplastic agent; EC 1.14.14.14 (aromatase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
hydroxychloroquine sulfate | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
etonitazene | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
amiloride hydrochloride, anhydrous | | hydrochloride | diuretic; sodium channel blocker | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
clothiapine | | dibenzothiazepine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
benperidol | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
7-hydroxychlorpromazine | | phenothiazines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
acadesine | | 1-ribosylimidazolecarboxamide; aminoimidazole; nucleoside analogue | antineoplastic agent; platelet aggregation inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cladribine | | organochlorine compound; purine 2'-deoxyribonucleoside | antineoplastic agent; immunosuppressive agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
camptothecin | | delta-lactone; pyranoindolizinoquinoline; quinoline alkaloid; tertiary alcohol | antineoplastic agent; EC 5.99.1.2 (DNA topoisomerase) inhibitor; genotoxin; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
thenalidine | | dialkylarylamine; tertiary amino compound | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bromocriptine | | indole alkaloid | antidyskinesia agent; antiparkinson drug; dopamine agonist; hormone antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dexchlorpheniramine | | chlorphenamine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
dv 1006 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
zidovudine | | azide; pyrimidine 2',3'-dideoxyribonucleoside | antimetabolite; antiviral drug; HIV-1 reverse transcriptase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
climbazole | | aromatic ether; hemiaminal ether; imidazoles; ketone; monochlorobenzenes | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
lonidamine | | dichlorobenzene; indazoles; monocarboxylic acid | antineoplastic agent; antispermatogenic agent; EC 2.7.1.1 (hexokinase) inhibitor; geroprotector | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
triadimenol | | aromatic ether; conazole fungicide; hemiaminal ether; monochlorobenzenes; secondary alcohol; triazole fungicide | antifungal agrochemical; EC 1.14.13.70 (sterol 14alpha-demethylase) inhibitor; xenobiotic metabolite | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
amonafide | | isoquinolines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
flupirtine | | aminopyridine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
chaetochromin | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
enoximone | | aromatic ketone | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
simvastatin | | delta-lactone; fatty acid ester; hexahydronaphthalenes; statin (semi-synthetic) | EC 1.1.1.34/EC 1.1.1.88 (hydroxymethylglutaryl-CoA reductase) inhibitor; EC 3.4.24.83 (anthrax lethal factor endopeptidase) inhibitor; ferroptosis inducer; geroprotector; prodrug | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
itraconazole | | aromatic ether; conazole antifungal drug; cyclic ketal; dichlorobenzene; dioxolane; N-arylpiperazine; triazole antifungal drug; triazoles | EC 3.6.3.44 (xenobiotic-transporting ATPase) inhibitor; Hedgehog signaling pathway inhibitor; P450 inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pravadoline | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
zileuton | | 1-benzothiophenes; ureas | anti-asthmatic drug; EC 1.13.11.34 (arachidonate 5-lipoxygenase) inhibitor; ferroptosis inhibitor; leukotriene antagonist; non-steroidal anti-inflammatory drug | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
niguldipine | | diarylmethane | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
topotecan | | pyranoindolizinoquinoline | antineoplastic agent; EC 5.99.1.2 (DNA topoisomerase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
eliprodil | | monochlorobenzenes; monofluorobenzenes; piperidines; secondary alcohol; tertiary amino compound | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gemcitabine | | organofluorine compound; pyrimidine 2'-deoxyribonucleoside | antimetabolite; antineoplastic agent; antiviral drug; DNA synthesis inhibitor; EC 1.17.4.1 (ribonucleoside-diphosphate reductase) inhibitor; environmental contaminant; immunosuppressive agent; photosensitizing agent; prodrug; radiosensitizing agent; xenobiotic | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
aripiprazole | | aromatic ether; delta-lactam; dichlorobenzene; N-alkylpiperazine; N-arylpiperazine; quinolone | drug metabolite; H1-receptor antagonist; second generation antipsychotic; serotonergic agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
verapamil hydrochloride | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
efavirenz | | acetylenic compound; benzoxazine; cyclopropanes; organochlorine compound; organofluorine compound | antiviral drug; HIV-1 reverse transcriptase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bendamustine | | benzimidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
aloxistatin | | epoxide; ethyl ester; L-leucine derivative; monocarboxylic acid amide | anticoronaviral agent; cathepsin B inhibitor | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
caroverine | | quinoxaline derivative | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
indocate | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
cgs 9343b | | benzimidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
telmisartan | | benzimidazoles; biphenyls; carboxybiphenyl | angiotensin receptor antagonist; antihypertensive agent; EC 3.4.15.1 (peptidyl-dipeptidase A) inhibitor; environmental contaminant; xenobiotic | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-methoxyestradiol | | 17beta-hydroxy steroid; 3-hydroxy steroid | angiogenesis modulating agent; antimitotic; antineoplastic agent; human metabolite; metabolite; mouse metabolite | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N(4)-acetylsulfathiazole | | 1,3-thiazoles; acetamides; sulfonamide | marine xenobiotic metabolite | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cyclizine hydrochloride | | | | 2017 | 2020 | 5.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
2,3-trimethylene-4-quinazolone | | quinazolines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
1,3-dimethyluric acid | | oxopurine | metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
danofloxacin | | quinolines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
nitrefazole | | imidazoles | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
alacepril | | dipeptide; thioacetate ester | EC 3.4.15.1 (peptidyl-dipeptidase A) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ubenimex | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
methotrimeprazine | | phenothiazines; tertiary amine | anticoronaviral agent; cholinergic antagonist; dopaminergic antagonist; EC 3.4.21.26 (prolyl oligopeptidase) inhibitor; non-narcotic analgesic; phenothiazine antipsychotic drug; serotonergic antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
honokiol | | biphenyls | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
9-methoxyellipticine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-aminophenoxazone | | phenoxazine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-deazaneplanocin | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
tryptanthrine | | alkaloid antibiotic; organic heterotetracyclic compound; organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
2-chlorodiazepam | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
Polycartine B | | phenazines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
aminoquinuride dihydrochloride | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
thioproperazine mesylate | | phenothiazines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
n(6)-(delta(2)-isopentenyl)adenine | | 6-isopentenylaminopurine | cytokinin | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-methyl-N-(phenylmethyl)benzenesulfonamide | | sulfonamide | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
zpck | | | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
sr141716 | | amidopiperidine; carbohydrazide; dichlorobenzene; monochlorobenzenes; pyrazoles | anti-obesity agent; appetite depressant; CB1 receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
vinpocetine | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
(6R)-7-[4-(dimethylamino)phenyl]-N-hydroxy-4,6-dimethyl-7-oxohepta-2,4-dienamide | | aromatic ketone | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
deguelin | | aromatic ether; diether; organic heteropentacyclic compound; rotenones | angiogenesis inhibitor; anti-inflammatory agent; antineoplastic agent; antiviral agent; apoptosis inducer; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor; mitochondrial NADH:ubiquinone reductase inhibitor; plant metabolite | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
fingolimod | | aminodiol; primary amino compound | antineoplastic agent; CB1 receptor antagonist; immunosuppressive agent; prodrug; sphingosine-1-phosphate receptor agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
triptolide | | diterpenoid; epoxide; gamma-lactam; organic heteroheptacyclic compound | antispermatogenic agent; plant metabolite | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tesmilifene | | diarylmethane | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sr 48692 | | N-acyl-amino acid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
elacridar | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sr 27897 | | indolyl carboxylic acid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gefitinib | | aromatic ether; monochlorobenzenes; monofluorobenzenes; morpholines; quinazolines; secondary amino compound; tertiary amino compound | antineoplastic agent; epidermal growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
n-(n-(3-carboxyoxirane-2-carbonyl)leucyl)isoamylamine | | leucine derivative | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bay x 1005 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
norketamine | | organochlorine compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
indatraline | | indanes | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
gyki 53655 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
methotrexate | | dicarboxylic acid; monocarboxylic acid amide; pteridines | abortifacient; antimetabolite; antineoplastic agent; antirheumatic drug; dermatologic drug; DNA synthesis inhibitor; EC 1.5.1.3 (dihydrofolate reductase) inhibitor; immunosuppressive agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
salvinorin a | | organic heterotricyclic compound; organooxygen compound | metabolite; oneirogen | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-diethoxyphosphorylmethyl-n-(4-bromo-2-cyanophenyl)benzamide | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
n,n-di-n-hexyl-2-(4-fluorophenyl)indole-3-acetamide | | phenylindole | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ml-3000 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
l 741626 | | piperidines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cd 437 | | adamantanes; monocarboxylic acid; naphthoic acid; phenols | apoptosis inducer; retinoic acid receptor gamma agonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
docetaxel anhydrous | | secondary alpha-hydroxy ketone; tetracyclic diterpenoid | antimalarial; antineoplastic agent; photosensitizing agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
perifosine | | ammonium betaine; phospholipid | EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
dx 8951 | | pyranoindolizinoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
mk 767 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bazedoxifene acetate | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
canertinib | | monochlorobenzenes; morpholines; organofluorine compound; quinazolines | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
birb 796 | | aromatic ether; morpholines; naphthalenes; pyrazoles; ureas | EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor; immunomodulator | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tipifarnib | | imidazoles; monochlorobenzenes; primary amino compound; quinolone | antineoplastic agent; apoptosis inducer; EC 2.5.1.58 (protein farnesyltransferase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
cyc 202 | | 2,6-diaminopurines | antiviral drug; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
avasimibe | | monoterpenoid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sb 203580 | | imidazoles; monofluorobenzenes; pyridines; sulfoxide | EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor; geroprotector; Hsp90 inhibitor; neuroprotective agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
enzastaurin | | indoles; maleimides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
erlotinib | | aromatic ether; quinazolines; secondary amino compound; terminal acetylenic compound | antineoplastic agent; epidermal growth factor receptor antagonist; protein kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
piboserod | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
l 163191 | | | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
dizocilpine | | secondary amino compound; tetracyclic antidepressant | anaesthetic; anticonvulsant; neuroprotective agent; nicotinic antagonist; NMDA receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bd 1047 | | primary amine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
s-benzylcysteine | | S-aryl-L-cysteine zwitterion | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
chelidonine | | alkaloid antibiotic; alkaloid fundamental parent; benzophenanthridine alkaloid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
lapatinib | | furans; organochlorine compound; organofluorine compound; quinazolines | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
sorafenib | | (trifluoromethyl)benzenes; aromatic ether; monochlorobenzenes; phenylureas; pyridinecarboxamide | angiogenesis inhibitor; anticoronaviral agent; antineoplastic agent; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor; ferroptosis inducer; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
lenalidomide | | aromatic amine; dicarboximide; isoindoles; piperidones | angiogenesis inhibitor; antineoplastic agent; immunomodulator | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N-[4-(3-chloro-4-fluoroanilino)-3-cyano-7-ethoxy-6-quinolinyl]-4-(dimethylamino)-2-butenamide | | aminoquinoline | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
roxindole | | indoles | alpha-adrenergic antagonist; serotonergic drug | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sr 142806 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
conidendrin | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
Porfiromycine | | mitomycin | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
nsc 95397 | | 1,4-naphthoquinones | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-methyl-2-quinazolinamine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-glycineamide-5-chlorophenyl-2-pyrryl ketone | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
elesclomol | | carbohydrazide; thiocarbonyl compound | antineoplastic agent; apoptosis inducer | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
niguldipine hydrochloride | | | | 2019 | 2020 | 4.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
2,5-bis(5-hydroxymethyl-2-thienyl)furan | | thiophenes | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
nsc 663284 | | quinolone | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bortezomib | | amino acid amide; L-phenylalanine derivative; pyrazines | antineoplastic agent; antiprotozoal drug; protease inhibitor; proteasome inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ritonavir | | 1,3-thiazoles; carbamate ester; carboxamide; L-valine derivative; ureas | antiviral drug; environmental contaminant; HIV protease inhibitor; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bardoxolone methyl | | cyclohexenones | | 2013 | 2019 | 8.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
nsc 23766 | | aminopyrimidine; aminoquinoline; primary amino compound; secondary amino compound; tertiary amino compound | antiviral agent; apoptosis inducer; EC 3.6.5.2 (small monomeric GTPase) inhibitor; muscarinic antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Destruxin B | | cyclodepsipeptide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tosylphenylalanyl chloromethyl ketone | | alpha-chloroketone; sulfonamide | alkylating agent; serine proteinase inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
trichostatin a | | antibiotic antifungal agent; hydroxamic acid; trichostatin | bacterial metabolite; EC 3.5.1.98 (histone deacetylase) inhibitor; geroprotector | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gw 3965 | | diarylmethane | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
y 27632 | | aromatic amide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
6-bromoindirubin-3'-oxime | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
purvalanol b | | purvalanol | protein kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
y-700 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
repsox | | pyrazolopyridine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sitafloxacin | | fluoroquinolone antibiotic; quinolines; quinolone antibiotic | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4,4-difluoro-N-[(1S)-3-[3-(3-methyl-5-propan-2-yl-1,2,4-triazol-4-yl)-8-azabicyclo[3.2.1]octan-8-yl]-1-phenylpropyl]-1-cyclohexanecarboxamide | | tropane alkaloid | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
2'-c-methylcytidine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
jp-1302 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
7-chloro-5,10-dihydrothieno[3,4-b][1,5]benzodiazepin-4-one | | benzodiazepine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tenatoprazole | | imidazopyridine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
s 1033 | | (trifluoromethyl)benzenes; imidazoles; pyridines; pyrimidines; secondary amino compound; secondary carboxamide | anticoronaviral agent; antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
5-[(2-fluoroanilino)methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
benidipine hydrochloride | | | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
benidipine | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-(1,3-benzoxazol-2-ylamino)-5-spiro[1,6,7,8-tetrahydroquinazoline-4,1'-cyclopentane]one | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
chlorprothixene | | chlorprothixene | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
mercaptopurine | | aryl thiol; purines; thiocarbonyl compound | anticoronaviral agent; antimetabolite; antineoplastic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
jrf 12 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
rg108 | | indolyl carboxylic acid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-amino-3-(4-methoxyphenyl)-4-oxo-1-thieno[3,4-d]pyridazinecarboxylic acid ethyl ester | | methoxybenzenes; substituted aniline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
stf 083010 | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
3-hydroxypyridine, sodium salt | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-(3-cyano-4,5,6,7-tetrahydro-1-benzothiophen-2-yl)-1-naphthalenecarboxamide | | naphthalenecarboxamide | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
5-[(2-bromoanilino)methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-amino-n-(4-methoxybenzyl)-4,6-dimethylthieno(2,3-b)pyridine-2-carboxamide | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-[(2-methoxyphenyl)methyl]-4-(1-piperidinyl)aniline | | aromatic amine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cct018159 | | benzodioxine; pyrazoles; resorcinols | antineoplastic agent; apoptosis inducer; Hsp90 inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1-[4-(4-bromophenyl)-2-thiazolyl]-4-piperidinecarboxamide | | piperidinecarboxamide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
secinh3 | | triazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
jk184 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-[[2-(trifluoromethyl)anilino]methyl]-8-quinolinol | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[3-[2-[(4-methyl-2-pyridinyl)amino]-4-thiazolyl]phenyl]acetamide | | acetamides; anilide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-bromo-N-(5-cyclohexyl-1,3,4-thiadiazol-2-yl)-2-thiophenecarboxamide | | aromatic amide; thiophenes | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-amino-1-[2-(3,4-dimethoxyphenyl)ethyl]-2-sulfanylidene-4-pyrimidinone | | dimethoxybenzene | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-[(3,4-dimethyl-5-isoxazolyl)sulfamoyl]phenyl]-6,8-dimethyl-2-(2-pyridinyl)-4-quinolinecarboxamide | | aromatic amide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[5-[(4-chlorophenoxy)methyl]-1,3,4-thiadiazol-2-yl]-5-methyl-3-phenyl-4-isoxazolecarboxamide | | aromatic ether | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-chloro-1-(2,5-dimethoxyphenyl)-4-(1-piperidinyl)pyrrole-2,5-dione | | maleimides | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
Src Inhibitor-1 | | aromatic ether; polyether; quinazolines; secondary amino compound | EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1-[2-(3,4-dimethoxyphenyl)ethyl]-6-propyl-2-sulfanylidene-7,8-dihydro-5H-pyrimido[4,5-d]pyrimidin-4-one | | dimethoxybenzene | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-phenyl-N-[4-(2-thiazolylsulfamoyl)phenyl]-4-quinolinecarboxamide | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-(2,5-dimethyl-1-phenyl-3-pyrrolyl)-6,7,8,9-tetrahydro-5H-[1,2,4]triazolo[4,3-a]azepine | | pyrroles | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
tamoxifen citrate | | citrate salt | angiogenesis inhibitor; anticoronaviral agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
hc-067047 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bi-78d3 | | aryl sulfide | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
gsk 3787 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
kartogenin | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
methyl-thiohydantoin-tryptophan | | organonitrogen compound; organooxygen compound | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-[2-chloro-6-ethoxy-4-[(3-methyl-5-oxo-1-phenyl-4-pyrazolylidene)methyl]phenoxy]acetic acid methyl ester | | monocarboxylic acid | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
4-(5-(4-methoxyphenyl)-3-phenyl-4,5-dihydro-1h-pyrazol-1-yl)benzenesulfonamide | | sulfonamide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
LSM-1318 | | oxa-steroid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
toremifene | | aromatic ether; organochlorine compound; tertiary amine | antineoplastic agent; bone density conservation agent; estrogen antagonist; estrogen receptor modulator | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
rwj 67657 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
6-methyl-2-(phenylethynyl)pyridine | | acetylenic compound; methylpyridines | anxiolytic drug; metabotropic glutamate receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bms 387032 | | 1,3-oxazoles; 1,3-thiazoles; organic sulfide; piperidinecarboxamide; secondary carboxamide | angiogenesis inhibitor; antineoplastic agent; apoptosis inducer; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tandutinib | | aromatic ether; N-arylpiperazine; N-carbamoylpiperazine; phenylureas; piperidines; quinazolines; tertiary amino compound | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
vx-745 | | aryl sulfide; dichlorobenzene; difluorobenzene; pyrimidopyridazine | anti-inflammatory drug; apoptosis inducer; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
corlanor | | hydrochloride | cardiotonic drug | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
dasatinib | | 1,3-thiazoles; aminopyrimidine; monocarboxylic acid amide; N-(2-hydroxyethyl)piperazine; N-arylpiperazine; organochlorine compound; secondary amino compound; tertiary amino compound | anticoronaviral agent; antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
zd 6474 | | aromatic ether; organobromine compound; organofluorine compound; piperidines; quinazolines; secondary amine | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
N-[2-(diethylamino)ethyl]-5-[(5-fluoro-2-oxo-1H-indol-3-ylidene)methyl]-2,4-dimethyl-1H-pyrrole-3-carboxamide | | indoles | | 2019 | 2020 | 4.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
compound 968 | | benzophenanthridine | EC 3.5.1.2 (glutaminase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nih-12848 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2,4-dioxo-3-pentyl-N-[3-(1-piperidinyl)propyl]-1H-quinazoline-7-carboxamide | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
[1-(3-methylphenyl)-5-benzimidazolyl]-(1-piperidinyl)methanone | | benzimidazoles | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-[[(6-bromo-1H-imidazo[4,5-b]pyridin-2-yl)thio]methyl]benzonitrile | | imidazopyridine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-[(3-fluorophenyl)methyl]-8-[4-(4-fluorophenyl)-4-oxobutyl]-1-phenyl-1,3,8-triazaspiro[4.5]decan-4-one | | aromatic ketone | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb-224289 | | 1,2,4-oxadiazole; azaspiro compound; benzamides; organic heterotetracyclic compound | serotonergic antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-[[7-[(4-fluorophenyl)methyl]-1,3-dimethyl-2,6-dioxo-8-purinyl]methyl]-1-piperazinecarboxylic acid ethyl ester | | oxopurine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gw 7647 | | aryl sulfide; monocarboxylic acid; ureas | PPARalpha agonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N,N-dimethylcarbamodithioic acid (1-acetamido-2,2,2-trichloroethyl) ester | | organonitrogen compound; organosulfur compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-bromo-2-(4-methylphenyl)-N-[(1-methyl-4-pyrazolyl)methyl]-4-quinolinecarboxamide | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
l 663536 | | aryl sulfide; indoles; monocarboxylic acid; monochlorobenzenes | antineoplastic agent; EC 1.13.11.34 (arachidonate 5-lipoxygenase) inhibitor; leukotriene antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
LSM-1924 | | organic heterotricyclic compound; organooxygen compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1-[6-(4-chlorophenyl)-5-imidazo[2,1-b]thiazolyl]-N-[(3,4-dichlorophenyl)methoxy]methanimine | | imidazoles | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
N4-ethyl-N6,1,2-trimethyl-N4-phenylpyrimidin-1-ium-4,6-diamine | | aromatic amine; tertiary amino compound | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
ferrostatin-1 | | ethyl ester; primary arylamine; substituted aniline | antifungal agent; antioxidant; ferroptosis inhibitor; neuroprotective agent; radiation protective agent; radical scavenger | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
2-[[2-[2-(2,3-dihydro-1,4-benzodioxin-6-ylamino)-2-oxoethyl]-1-oxo-5-isoquinolinyl]oxy]propanoic acid ethyl ester | | isoquinolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sch 79797 | | quinazolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
6-(2-methyl-1-piperidinyl)-5-nitro-4-pyrimidinamine | | C-nitro compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
4-(5-benzo(1,3)dioxol-5-yl-4-pyridin-2-yl-1h-imidazol-2-yl)benzamide | | benzamides; benzodioxoles; imidazoles; pyridines | EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
rabeprazole(1-) | | organic nitrogen anion | | 2019 | 2020 | 4.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
1-(4-Fluorophenyl)-3-(3-(4-fluorophenyl)-3-hydroxypropyl)-4-(4-hydroxyphenyl)azetidin-2-one | | monobactam | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
imd 0354 | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ex 527 | | carbazoles; monocarboxylic acid amide; organochlorine compound | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ncgc00099374 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
2-nitro-4-[(6-nitro-4-quinolinyl)amino]-N-[4-(pyridin-4-ylamino)phenyl]benzamide | | benzamides | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
quercetin | | 7-hydroxyflavonol; pentahydroxyflavone | antibacterial agent; antineoplastic agent; antioxidant; Aurora kinase inhibitor; chelator; EC 1.10.99.2 [ribosyldihydronicotinamide dehydrogenase (quinone)] inhibitor; geroprotector; phytoestrogen; plant metabolite; protein kinase inhibitor; radical scavenger | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
luteolin | | 3'-hydroxyflavonoid; tetrahydroxyflavone | angiogenesis inhibitor; anti-inflammatory agent; antineoplastic agent; apoptosis inducer; c-Jun N-terminal kinase inhibitor; EC 2.3.1.85 (fatty acid synthase) inhibitor; immunomodulator; nephroprotective agent; plant metabolite; radical scavenger; vascular endothelial growth factor receptor antagonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cyclosporine | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
kaempferol | | 7-hydroxyflavonol; flavonols; tetrahydroxyflavone | antibacterial agent; geroprotector; human blood serum metabolite; human urinary metabolite; human xenobiotic metabolite; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
genistein | | 7-hydroxyisoflavones | antineoplastic agent; EC 5.99.1.3 [DNA topoisomerase (ATP-hydrolysing)] inhibitor; geroprotector; human urinary metabolite; phytoestrogen; plant metabolite; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
mycophenolate mofetil | | carboxylic ester; ether; gamma-lactone; phenols; tertiary amino compound | anticoronaviral agent; EC 1.1.1.205 (IMP dehydrogenase) inhibitor; immunosuppressive agent; prodrug | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bruceantin | | triterpenoid | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
chrysin | | 7-hydroxyflavonol; dihydroxyflavone | anti-inflammatory agent; antineoplastic agent; antioxidant; EC 2.7.11.18 (myosin-light-chain kinase) inhibitor; hepatoprotective agent; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
daidzein | | 7-hydroxyisoflavones | antineoplastic agent; EC 2.7.7.7 (DNA-directed DNA polymerase) inhibitor; EC 3.2.1.20 (alpha-glucosidase) inhibitor; phytoestrogen; plant metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
neticonazole | | aromatic ether; benzenes; conazole antifungal drug; enamine; imidazole antifungal drug; imidazoles; methyl sulfide | antifungal drug; EC 1.14.13.70 (sterol 14alpha-demethylase) inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-(4Z,7Z,10Z,13Z,16Z,19Z)-docosahexaenoylethanolamine | | endocannabinoid; N-acylethanolamine 22:6 | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
n-oleoylethanolamine | | endocannabinoid; N-(long-chain-acyl)ethanolamine; N-acylethanolamine 18:1 | EC 3.5.1.23 (ceramidase) inhibitor; geroprotector; PPARalpha agonist | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
alpha-zearalenol | | macrolide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
fenretinide | | monocarboxylic acid amide; retinoid | antineoplastic agent; antioxidant | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
su 9516 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
N-(4-bromo-3-methylphenyl)-2,5-dimethyl-[1,2,4]triazolo[1,5-a]pyrimidin-7-amine | | triazolopyrimidines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ter 199 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
arachidonylcyclopropylamide | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 277011 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ly 320135 | | benzofurans | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pd 166285 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 223412 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sr 59230a | | tetralins | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
3-[6-[4-(trifluoromethoxy)anilino]-4-pyrimidinyl]benzamide | | pyrimidines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
kn 62 | | piperazines | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
su 6656 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
MeJA | | Jasmonate derivatives | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
1h-pyrrole-2,5-dione, 3-(1-methyl-1h-indol-3-yl)-4-(1-methyl-6-nitro-1h-indol-3-yl)- | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pd 161570 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
semaxinib | | olefinic compound; oxindoles; pyrroles | angiogenesis modulating agent; antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; vascular endothelial growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
su 11248 | | monocarboxylic acid amide; pyrroles | angiogenesis inhibitor; antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; immunomodulator; neuroprotective agent; vascular endothelial growth factor receptor antagonist | 2013 | 2017 | 9.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
palbociclib | | aminopyridine; aromatic ketone; cyclopentanes; piperidines; pyridopyrimidine; secondary amino compound; tertiary amino compound | antineoplastic agent; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
jnj-7706621 | | sulfonamide | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
virginiamycin factor s1 | | cyclodepsipeptide; macrolide antibiotic | antibacterial drug; bacterial metabolite | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cisplatin | | diamminedichloroplatinum | antineoplastic agent; apoptosis inducer; cross-linking reagent; ferroptosis inducer; genotoxin; mutagen; nephrotoxin; photosensitizing agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
vx680 | | N-arylpiperazine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
fenoterol | | hydrobromide | beta-adrenergic agonist; bronchodilator agent; sympathomimetic agent | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
xib 4035 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gw-5074 | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
d 4476 | | imidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cyc 116 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bay 19-8004 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
axitinib | | aryl sulfide; benzamides; indazoles; pyridines | antineoplastic agent; tyrosine kinase inhibitor; vascular endothelial growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pai 039 | | indole-3-acetic acids | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
belotecan | | pyranoindolizinoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
norgestimate | | ketoxime; steroid ester; terminal acetylenic compound | contraceptive drug; progestin; synthetic oral contraceptive | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
b 43 | | aromatic amine; aromatic ether; cyclopentanes; primary amino compound; pyrrolopyrimidine | EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; geroprotector | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gw2974 | | pyridopyrimidine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-(2' methoxyphenyl)-1-(2'-(n-(2''-pyridinyl)-4-fluorobenzamido)ethyl)piperazine | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
methiazole | | benzimidazoles; carbamate ester | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb 218795 | | quinolines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
bvt.948 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ispinesib | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
fk 866 | | benzamides; N-acylpiperidine | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
a 38503 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
temsirolimus | | macrolide lactam | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pd 184352 | | aminobenzoic acid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bibx 1382bs | | substituted aniline | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
hdac-42 | | amidobenzoic acid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
parthenolide | | sesquiterpene lactone | drug allergen; inhibitor; non-narcotic analgesic; non-steroidal anti-inflammatory drug; peripheral nervous system drug | 2017 | 2019 | 6.0 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
krn 633 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
[4-[[4-(1-benzothiophen-2-yl)-2-pyrimidinyl]amino]phenyl]-[4-(1-pyrrolidinyl)-1-piperidinyl]methanone | | benzamides; N-acylpiperidine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-amino-4-oxo-3-phenyl-1-thieno[3,4-d]pyridazinecarboxylic acid | | organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
iniparib | | carbonyl compound; organohalogen compound | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mk 0752 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gw 501516 | | 1,3-thiazoles; aromatic ether; aryl sulfide; monocarboxylic acid; organofluorine compound | carcinogenic agent; PPARbeta/delta agonist | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
av 412 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ag-041r | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
telatinib | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
dolastatin 10 | | 1,3-thiazoles; tetrapeptide | animal metabolite; antineoplastic agent; apoptosis inducer; marine metabolite; microtubule-destabilising agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cp 547632 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
spc-839 | | | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
lenvatinib | | aromatic amide; aromatic ether; cyclopropanes; monocarboxylic acid amide; monochlorobenzenes; phenylureas; quinolines | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; fibroblast growth factor receptor antagonist; orphan drug; vascular endothelial growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
andarine | | acetamides; anilide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gw843682x | | (trifluoromethyl)benzenes | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pd 0325901 | | difluorobenzene; hydroxamic acid ester; monofluorobenzenes; organoiodine compound; propane-1,2-diols; secondary amino compound | antineoplastic agent; EC 2.7.12.2 (mitogen-activated protein kinase kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
midostaurin | | benzamides; gamma-lactam; indolocarbazole; organic heterooctacyclic compound | antineoplastic agent; EC 2.7.11.13 (protein kinase C) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
ag 14361 | | benzimidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 265610 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
valnemulin | | | | 2019 | 2020 | 4.5 | medium | 0 | 0 | 0 | 0 | 2 | 0 |
nu 7026 | | organic heterotricyclic compound; organooxygen compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
fr 148083 | | aromatic ether; macrolide; phenols; secondary alcohol; secondary alpha-hydroxy ketone | antibacterial agent; antineoplastic agent; metabolite; NF-kappaB inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mocetinostat | | aminopyrimidine; benzamides; pyridines; secondary amino compound; secondary carboxamide; substituted aniline | antineoplastic agent; apoptosis inducer; autophagy inducer; cardioprotective agent; EC 3.5.1.98 (histone deacetylase) inhibitor; hepatotoxic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
osi 930 | | aromatic amide | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
ki 20227 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
scio-469 | | aromatic amide; aromatic ketone; chloroindole; dicarboxylic acid diamide; indolecarboxamide; monofluorobenzenes; N-acylpiperazine; N-alkylpiperazine | antineoplastic agent; apoptosis inducer; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ticagrelor | | aryl sulfide; hydroxyether; organofluorine compound; secondary amino compound; triazolopyrimidines | P2Y12 receptor antagonist; platelet aggregation inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ssr 69071 | | pyridopyrimidine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
l 692585 | | peptide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pi103 | | aromatic amine; morpholines; organic heterotricyclic compound; phenols; tertiary amino compound | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
sb 210313 | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
gw 4064 | | stilbenoid | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nnc 26-9100 | | aminopyridine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
2-(3-chlorobenzyloxy)-6-(piperazin-1-yl)pyrazine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sa 4503 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ic 87114 | | 6-aminopurines; biaryl; quinazolines | EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
zibotentan | | phenylpyridine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tivozanib | | aromatic ether | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
hki 272 | | nitrile; quinolines | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2019 | 8.0 | low | 0 | 0 | 0 | 0 | 2 | 0 |
tofacitinib | | N-acylpiperidine; nitrile; pyrrolopyrimidine; tertiary amino compound | antirheumatic drug; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bibr 1532 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
n-(6-chloro-7-methoxy-9h-beta-carbolin-8-yl)-2-methylnicotinamide | | | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
rucaparib | | azepinoindole; caprolactams; organofluorine compound; secondary amino compound | antineoplastic agent; EC 2.4.2.30 (NAD(+) ADP-ribosyltransferase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cediranib | | aromatic ether | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tae226 | | morpholines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gw0742 | | monocarboxylic acid | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
ps1145 | | beta-carbolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bay 41-8543 | | pyrazolopyridine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
u 18666a | | hydrochloride | antiviral agent; EC 1.3.1.72 (Delta(24)-sterol reductase) inhibitor; Hedgehog signaling pathway inhibitor; nicotinic antagonist; sterol biosynthesis inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
chir 99021 | | aminopyridine; aminopyrimidine; cyanopyridine; diamine; dichlorobenzene; imidazoles; secondary amino compound | EC 2.7.11.26 (tau-protein kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sb 525334 | | quinoxaline derivative | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
way-362450 | | indoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
masitinib | | 1,3-thiazoles; benzamides; N-alkylpiperazine; pyridines | antineoplastic agent; antirheumatic drug; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bx795 | | ureas | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
pazopanib | | aminopyrimidine; indazoles; sulfonamide | angiogenesis modulating agent; antineoplastic agent; tyrosine kinase inhibitor; vascular endothelial growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sepantronium | | organic cation | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 6244 | | benzimidazoles; bromobenzenes; hydroxamic acid ester; monochlorobenzenes; organofluorine compound; secondary amino compound | anticoronaviral agent; antineoplastic agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
bay 61-3606 | | pyrimidines | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-(3-cyanophenyl)-2'-methyl-5'-(5-methyl-1,3,4-oxadiazol-2-yl)biphenyl-4-carboxamide | | 1,3,4-oxadiazoles; benzamides; biphenyls; nitrile | EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
ar c155858 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
aee 788 | | 6-{4-[(4-ethylpiperazin-1-yl)methyl]phenyl}-N-(1-phenylethyl)-7H-pyrrolo[2,3-d]pyrimidin-4-amine | angiogenesis inhibitor; antineoplastic agent; apoptosis inducer; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; epidermal growth factor receptor antagonist; trypanocidal drug | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
saracatinib | | aromatic ether; benzodioxoles; diether; N-methylpiperazine; organochlorine compound; oxanes; quinazolines; secondary amino compound | anticoronaviral agent; antineoplastic agent; apoptosis inducer; autophagy inducer; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; radiosensitizing agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sd-208 | | | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
vx 702 | | phenylpyridine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
crenolanib | | aminopiperidine; aromatic ether; benzimidazoles; oxetanes; quinolines; tertiary amino compound | angiogenesis inhibitor; antineoplastic agent; apoptosis inducer; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cj 033466 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
cc 401 | | pyrazoles; ring assembly | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
volasertib | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
PB28 | | aromatic ether; piperazines; tetralins | anticoronaviral agent; antineoplastic agent; apoptosis inducer; sigma-2 receptor agonist | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
arterolane | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
azd 7762 | | aromatic amide; thiophenes | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cariprazine | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
krp-203 | | | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
mk 0354 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
regorafenib | | (trifluoromethyl)benzenes; aromatic ether; monochlorobenzenes; monofluorobenzenes; phenylureas; pyridinecarboxamide | antineoplastic agent; hepatotoxic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
at 7867 | | monochlorobenzenes; piperidines; pyrazoles | antineoplastic agent; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
acetic acid 2-[4-methyl-8-(4-morpholinylsulfonyl)-1,3-dioxo-2-pyrrolo[3,4-c]quinolinyl]ethyl ester | | pyrroloquinoline | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
6-[[5-fluoro-2-(3,4,5-trimethoxyanilino)-4-pyrimidinyl]amino]-2,2-dimethyl-4H-pyrido[3,2-b][1,4]oxazin-3-one | | methoxybenzenes; substituted aniline | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ptc 124 | | oxadiazole; ring assembly | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
degrasyn | | | | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
brivanib | | aromatic ether; diether; fluoroindole; pyrrolotriazine; secondary alcohol | angiogenesis inhibitor; antineoplastic agent; apoptosis inducer; drug metabolite; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; fibroblast growth factor receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
icg 001 | | peptide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mp470 | | N-arylpiperazine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nu 7441 | | dibenzothiophenes | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
at 7519 | | dichlorobenzene; piperidines; pyrazoles; secondary carboxamide | antineoplastic agent; EC 2.7.11.22 (cyclin-dependent kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bi 2536 | | | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
danusertib | | piperazines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N-[4-(2-tert-butylphenyl)sulfonylphenyl]-2,3,4-trihydroxy-5-[(2-propan-2-ylphenyl)methyl]benzamide | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N-[5-[[5-[(4-acetyl-1-piperazinyl)-oxomethyl]-4-methoxy-2-methylphenyl]thio]-2-thiazolyl]-4-[(3,3-dimethylbutan-2-ylamino)methyl]benzamide | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
abt 869 | | aromatic amine; indazoles; phenylureas | angiogenesis inhibitor; antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 1152 | | anilide; monoalkyl phosphate; monofluorobenzenes; pyrazoles; quinazolines; secondary amino compound; secondary carboxamide; tertiary amino compound | antineoplastic agent; Aurora kinase inhibitor; prodrug | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
dorsomorphin | | aromatic ether; piperidines; pyrazolopyrimidine; pyridines | bone morphogenetic protein receptor antagonist; EC 2.7.11.31 {[hydroxymethylglutaryl-CoA reductase (NADPH)] kinase} inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ac 261066 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
carfilzomib | | epoxide; morpholines; tetrapeptide | antineoplastic agent; proteasome inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
gw9508 | | aromatic amine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
jnj 26854165 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf 573228 | | quinolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gw 2580 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
idelalisib | | aromatic amine; organofluorine compound; purines; quinazolines; secondary amino compound | antineoplastic agent; apoptosis inducer; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
crizotinib | | 3-[1-(2,6-dichloro-3-fluorophenyl)ethoxy]-5-[1-(piperidin-4-yl)pyrazol-4-yl]pyridin-2-amine | antineoplastic agent; biomarker; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-(5,6-dimethoxy-1-benzimidazolyl)-3-[(2-methylsulfonylphenyl)methoxy]-2-thiophenecarbonitrile | | benzimidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-[2-(2-chloro-4-fluoroanilino)-5-methyl-4-pyrimidinyl]-N-[(1S)-1-(3-chlorophenyl)-2-hydroxyethyl]-1H-pyrrole-2-carboxamide | | aromatic amide; heteroarene | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
osi 906 | | cyclobutanes; quinolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ly2109761 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
chir-265 | | aromatic ether | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
motesanib | | pyridinecarboxamide | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
az-628 | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
trametinib | | acetamides; aromatic amine; cyclopropanes; organofluorine compound; organoiodine compound; pyridopyrimidine; ring assembly | anticoronaviral agent; antineoplastic agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor; geroprotector | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf-562,271 | | indoles | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
gliocladin c | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sb 706504 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
veliparib | | benzimidazoles | EC 2.4.2.30 (NAD(+) ADP-ribosyltransferase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ku-0060648 | | dibenzothiophenes | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
dactolisib | | imidazoquinoline; nitrile; quinolines; ring assembly; ureas | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bgt226 | | aromatic ether; imidazoquinoline; N-arylpiperazine; organofluorine compound; pyridines | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
palomid 529 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
n-desmethyldanofloxacin | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
rabeprazole sodium | | organic sodium salt | | 2017 | 2017 | 7.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tosedostat | | carboxylic ester; hydroxamic acid; secondary carboxamide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mdv 3100 | | (trifluoromethyl)benzenes; benzamides; imidazolidinone; monofluorobenzenes; nitrile; thiocarbonyl compound | androgen antagonist; antineoplastic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ku 60019 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk 461364 | | (trifluoromethyl)benzenes | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
n-(3,4-difluoro-2-(2-fluoro-4-iodophenylamino)-6-methoxyphenyl)-1-(2,3-dihydroxypropyl)cyclopropane-1-sulfonamide | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 1152-hqpa | | anilide; monofluorobenzenes; primary alcohol; pyrazoles; quinazolines; secondary amino compound; secondary carboxamide; tertiary amino compound | antineoplastic agent; Aurora kinase inhibitor | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
CDN1163 | | aromatic ether; quinolines; secondary carboxamide | SERCA activator | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
nvp-tae684 | | piperidines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4-methyl-3-(2-(2-morpholinoethylamino)quinazolin-6-yl)-n-(3-(trifluoromethyl)phenyl)benzamide | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
gsk 269962a | | | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
a-83-01 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
3-[(1-methyl-3-indolyl)methylidene]-1H-pyrrolo[3,2-b]pyridin-2-one | | indoles | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
vx-770 | | aromatic amide; monocarboxylic acid amide; phenols; quinolone | CFTR potentiator; orphan drug | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
buparlisib | | aminopyridine; aminopyrimidine; morpholines; organofluorine compound | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 1480 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pha 848125 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
fedratinib | | sulfonamide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk690693 | | 1,2,5-oxadiazole; acetylenic compound; aromatic amine; aromatic ether; imidazopyridine; piperidines; primary amino compound; tertiary alcohol | antineoplastic agent; EC 2.7.11.1 (non-specific serine/threonine protein kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cnf 2024 | | 2-aminopurines; aromatic ether; organochlorine compound; pyridines | antineoplastic agent; Hsp90 inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ku 0063794 | | benzyl alcohols; monomethoxybenzene; morpholines; pyridopyrimidine; tertiary amino compound | antineoplastic agent; mTOR inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
azd 7545 | | benzamides; monochlorobenzenes; organofluorine compound; secondary carboxamide; sulfone; tertiary alcohol; tertiary carboxamide | EC 2.7.11.2 - [pyruvate dehydrogenase (acetyl-transferring)] kinase inhibitor; hypoglycemic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nvp-bhg712 | | benzamides | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
nutlin-3b | | Nutlin; piperazinone | anticoronaviral agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf 04217903 | | quinolines | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
gdc 0941 | | indazoles; morpholines; piperazines; sulfonamide; thienopyrimidine | EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sm 164 | | benzenes; organic heterobicyclic compound; secondary carboxamide; triazoles | antineoplastic agent; apoptosis inducer; radiosensitizing agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-[[4-(4-acetylphenyl)-1-piperazinyl]sulfonyl]-1,3-dihydroindol-2-one | | aromatic ketone | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ph 797804 | | aromatic ether; benzamides; organobromine compound; organofluorine compound; pyridone | anti-inflammatory agent; EC 2.7.11.24 (mitogen-activated protein kinase) inhibitor | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
pha 408 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk 1016790a | | 1-benzothiophenes; aromatic primary alcohol; dichlorobenzene; N-acylpiperazine; sulfonamide; tertiary carboxamide | TRPV4 agonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
olaparib | | cyclopropanes; monofluorobenzenes; N-acylpiperazine; phthalazines | antineoplastic agent; apoptosis inducer; EC 2.4.2.30 (NAD(+) ADP-ribosyltransferase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
srt1720 | | | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
plx 4720 | | aromatic ketone; difluorobenzene; organochlorine compound; pyrrolopyridine; sulfonamide | antineoplastic agent; B-Raf inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cx 4945 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cudc 101 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
purfalcamine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
mln 8237 | | benzazepine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
lde225 | | aminopyridine; aromatic ether; benzamides; biphenyls; morpholines; organofluorine compound; tertiary amino compound | antineoplastic agent; Hedgehog signaling pathway inhibitor; SMO receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gdc 0449 | | benzamides; monochlorobenzenes; pyridines; sulfone | antineoplastic agent; Hedgehog signaling pathway inhibitor; SMO receptor antagonist; teratogenic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sgx 523 | | aryl sulfide; biaryl; pyrazoles; quinolines; triazolopyridazine | c-Met tyrosine kinase inhibitor; nephrotoxic agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bms 754807 | | pyrazoles; pyridines; pyrrolidines; pyrrolotriazine | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bms 777607 | | aromatic amide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
sgi 1776 | | imidazoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pci 32765 | | acrylamides; aromatic amine; aromatic ether; N-acylpiperidine; pyrazolopyrimidine; tertiary carboxamide | antineoplastic agent; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ponatinib | | (trifluoromethyl)benzenes; acetylenic compound; benzamides; imidazopyridazine; N-methylpiperazine | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
amg 900 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mk-1775 | | piperazines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bag956 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
quizartinib | | benzoimidazothiazole; isoxazoles; morpholines; phenylureas | antineoplastic agent; EC 2.7.10.1 (receptor protein-tyrosine kinase) inhibitor; necroptosis inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
PP121 | | aromatic amine; cyclopentanes; pyrazolopyrimidine; pyrrolopyridine | antineoplastic agent; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; tyrosine kinase inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-[3-[[[7-(hydroxyamino)-7-oxoheptyl]amino]-oxomethyl]-5-isoxazolyl]phenyl]carbamic acid tert-butyl ester | | carbamate ester | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tak 733 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mk 2206 | | organic heterotricyclic compound | EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
navitoclax | | aryl sulfide; monochlorobenzenes; morpholines; N-sulfonylcarboxamide; organofluorine compound; piperazines; secondary amino compound; sulfone; tertiary amino compound | antineoplastic agent; apoptosis inducer; B-cell lymphoma 2 inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
sns 314 | | ureas | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
jzl 184 | | benzodioxoles | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk 650394 | | phenylpyridine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
n-(cyanomethyl)-4-(2-((4-(4-morpholinyl)phenyl)amino)-4-pyrimidinyl)benzamide | | aminopyrimidine; benzamides; morpholines; nitrile; secondary amino compound; tertiary amino compound | anti-anaemic agent; antineoplastic agent; apoptosis inducer; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
dcc-2036 | | organofluorine compound; phenylureas; pyrazoles; pyridinecarboxamide; quinolines | tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
cabozantinib | | aromatic ether; dicarboxylic acid diamide; organofluorine compound; quinolines | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
N-(2,6-difluorophenyl)-5-[3-[2-[5-ethyl-2-methoxy-4-[4-(4-methylsulfonyl-1-piperazinyl)-1-piperidinyl]anilino]-4-pyrimidinyl]-2-imidazo[1,2-a]pyridinyl]-2-methoxybenzamide | | benzamides | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
incb-018424 | | nitrile; pyrazoles; pyrrolopyrimidine | antineoplastic agent; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
bix 01294 | | piperidines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf 3845 | | piperidines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
TAK-580 | | 1,3-thiazolecarboxamide; aminopyrimidine; chloropyridine; organofluorine compound; pyrimidinecarboxamide; secondary carboxamide | antineoplastic agent; apoptosis inducer; B-Raf inhibitor | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gsk 2126458 | | aromatic ether; difluorobenzene; pyridazines; pyridines; quinolines; sulfonamide | anticoronaviral agent; antineoplastic agent; autophagy inducer; EC 2.7.1.137 (phosphatidylinositol 3-kinase) inhibitor; mTOR inhibitor; radiosensitizing agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
8-(4-aminophenyl)-2-(4-morpholinyl)-1-benzopyran-4-one | | chromones | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ixazomib | | benzamides; boronic acids; dichlorobenzene; glycine derivative | antineoplastic agent; apoptosis inducer; drug metabolite; orphan drug; proteasome inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ldn 193189 | | pyrimidines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf 3758309 | | organic heterobicyclic compound; organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
(5-(2,4-bis((3s)-3-methylmorpholin-4-yl)pyrido(2,3-d)pyrimidin-7-yl)-2-methoxyphenyl)methanol | | benzyl alcohols; morpholines; pyridopyrimidine; tertiary amino compound | antineoplastic agent; apoptosis inducer; mTOR inhibitor | 2019 | 2020 | 4.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
plx4032 | | aromatic ketone; difluorobenzene; monochlorobenzenes; pyrrolopyridine; sulfonamide | antineoplastic agent; B-Raf inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
(2S)-2-[[2-(2,3-dihydro-1H-inden-5-yloxy)-9-[(4-phenylphenyl)methyl]-6-purinyl]amino]-3-phenyl-1-propanol | | biphenyls | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk 1363089 | | aromatic ether | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
kin-193 | | pyridopyrimidine | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-(2-benzofuranyl)-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-(3-methylsulfonylphenyl)-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
5-bromo-4-[(1-methyl-5-tetrazolyl)thio]thieno[2,3-d]pyrimidine | | aryl sulfide; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
bay 869766 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
baricitinib | | azetidines; nitrile; pyrazoles; pyrrolopyrimidine; sulfonamide | anti-inflammatory agent; antirheumatic drug; antiviral agent; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor; immunosuppressive agent | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
4-[6-[4-(methoxycarbonylamino)phenyl]-4-(4-morpholinyl)-1-pyrazolo[3,4-d]pyrimidinyl]-1-piperidinecarboxylic acid methyl ester | | carbamate ester | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
6-(1,3-benzodioxol-5-yl)-N-methyl-N-(thiophen-2-ylmethyl)-4-quinazolinamine | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6-[(3-aminophenyl)methyl]-4-methyl-2-methylsulfinyl-5-thieno[3,4]pyrrolo[1,3-d]pyridazinone | | organic heterobicyclic compound; organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2013 | 2020 | 6.8 | medium | 0 | 0 | 0 | 0 | 4 | 0 |
N-[(5-bromo-8-hydroxy-7-quinolinyl)-thiophen-2-ylmethyl]acetamide | | hydroxyquinoline | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
p505-15 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
mrt67307 | | aromatic amine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
3-[[4-(2,3-dihydro-1,4-benzodioxin-6-ylsulfonyl)-1,4-diazepan-1-yl]sulfonyl]aniline | | benzenes; sulfonamide | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cp 466722 | | quinazolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
CAY10626 | | ureas | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
N-[3-[[5-chloro-2-[4-(4-methyl-1-piperazinyl)anilino]-4-pyrimidinyl]oxy]phenyl]-2-propenamide | | piperazines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
thiopental sodium | | organochlorine compound; piperazines; pyrimidines | antineoplastic agent; tyrosine kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ribociclib | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
1-[3-[4-[(1-methyl-5-tetrazolyl)thio]-5-thieno[2,3-d]pyrimidinyl]phenyl]ethanone | | aromatic ketone; thienopyrimidine | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
pha 793887 | | piperidinecarboxamide | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
gsk 2334470 | | indazoles | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nvp-bsk805 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ml228 probe | | 1,2,4-triazines; biphenyls; pyridines; secondary amino compound | hypoxia-inducible factor pathway activator | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
xmd 8-92 | | pyrimidobenzodiazepine | protein kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf-03882845 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
jq1 compound | | carboxylic ester; organochlorine compound; tert-butyl ester; thienotriazolodiazepine | angiogenesis inhibitor; anti-inflammatory agent; antineoplastic agent; apoptosis inducer; bromodomain-containing protein 4 inhibitor; cardioprotective agent; ferroptosis inducer | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
jnj38877605 | | quinolines | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N-[3-(1,3-benzothiazol-2-yl)-5,6-dihydro-4H-thieno[2,3-c]pyrrol-2-yl]acetamide | | benzothiazoles | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
pf-04620110 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
gsk525762a | | benzodiazepine | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
birinapant | | dipeptide | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
torin 1 | | N-acylpiperazine; N-arylpiperazine; organofluorine compound; pyridoquinoline; quinolines | antineoplastic agent; mTOR inhibitor | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
abt-199 | | aromatic ether; C-nitro compound; monochlorobenzenes; N-alkylpiperazine; N-arylpiperazine; N-sulfonylcarboxamide; oxanes; pyrrolopyridine | antineoplastic agent; apoptosis inducer; B-cell lymphoma 2 inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
ly2940680 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1-[4-fluoro-3-(trifluoromethyl)phenyl]-3-(5-pyridin-4-yl-1,3,4-thiadiazol-2-yl)urea | | ureas | | 2013 | 2020 | 6.8 | high | 0 | 0 | 0 | 0 | 4 | 0 |
N-(4-methyl-2-pyridinyl)-4-[3-(trifluoromethyl)anilino]-1-piperidinecarbothioamide | | (trifluoromethyl)benzenes | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ro 4929097 | | dibenzoazepine; dicarboxylic acid diamide; lactam; organofluorine compound | EC 3.4.23.46 (memapsin 2) inhibitor | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
ncgc00242364 | | quinazolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gsk4112 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
torin 2 | | aminopyridine; organofluorine compound; primary amino compound; pyridoquinoline | antineoplastic agent; mTOR inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
pf-4708671 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
gsk1210151a | | imidazoquinoline | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hs-173 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
sr1664 | | indolecarboxamide | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
4-(3-chloro-5-(trifluoromethyl)pyridin-2-yl)-n-(4-methoxypyridin-2-yl)piperazine-1-carbothioamide | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-(1-benzoyl-4-piperidinyl)butyl]-3-(3-pyridinyl)-2-propenamide | | benzamides; N-acylpiperidine | | 2013 | 2020 | 7.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
N-[4-[3-chloro-4-(2-pyridinylmethoxy)anilino]-3-cyano-7-ethoxy-6-quinolinyl]-4-(dimethylamino)-2-butenamide | | aminoquinoline | | 2017 | 2020 | 5.5 | high | 0 | 0 | 0 | 0 | 2 | 0 |
2-methoxy-N-[3-[4-[3-methyl-4-[(6-methyl-3-pyridinyl)oxy]anilino]-6-quinazolinyl]prop-2-enyl]acetamide | | aromatic ether; methylpyridines; olefinic compound; quinazolines; secondary amino compound; secondary carboxamide; toluenes | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
belinostat | | olefinic compound | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
cudc-907 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
methacycline | | | | 2019 | 2019 | 5.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ethyl 1-benzyl-3-hydroxy-2(5h)-oxopyrrole-4-carboxylate | | carboxylic acid; pyrroline | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
methacycline monohydrochloride | | | | 2017 | 2020 | 5.5 | low | 0 | 0 | 0 | 0 | 2 | 0 |
2-[[[4-hydroxy-2-oxo-1-(phenylmethyl)-3-quinolinyl]-oxomethyl]amino]acetic acid | | quinolines | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
a 769662 | | biphenyls | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
agi-5198 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
cep-32496 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
epz004777 | | N-glycosyl compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
3-[[2-(2-pyridinyl)-6-(1,2,4,5-tetrahydro-3-benzazepin-3-yl)-4-pyrimidinyl]amino]propanoic acid | | organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
LimKi 3 | | 1,3-thiazoles; dichlorobenzene; organofluorine compound; pyrazoles; secondary carboxamide | LIM kinase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1-[4-amino-7-[3-(2-methoxyethylamino)propyl]-5-(4-methylphenyl)-6-pyrrolo[2,3-d]pyrimidinyl]-2-fluoroethanone | | pyrroles | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
entecavir | | benzamides; N-acylpiperidine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
2-[5-[(3,5-dimethyl-1H-pyrrol-2-yl)methylidene]-4-methoxy-2-pyrrolylidene]indole | | dipyrrins | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
N-hydroxy-3-[4-[[2-(2-methyl-1H-indol-3-yl)ethylamino]methyl]phenyl]-2-propenamide | | tryptamines | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
3-[(5-tert-butyl-1H-imidazol-4-yl)methylidene]-6-(phenylmethylene)piperazine-2,5-dione | | pyrazines | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
gsk837149a | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
N-[4-(3-chloro-4-fluoroanilino)-7-[[(3S)-3-oxolanyl]oxy]-6-quinazolinyl]-4-(dimethylamino)-2-butenamide | | quinazolines | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
N-[4-(3-chloro-4-fluoroanilino)-7-methoxy-6-quinazolinyl]-4-(1-piperidinyl)-2-butenamide | | quinazolines | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
wnt-c59 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
5-[1-(2-hydroxyethyl)-3-pyridin-4-yl-4-pyrazolyl]-2,3-dihydroinden-1-one oxime | | indanes | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
gkt137831 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
vx-509 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
vx-970 | | sulfonamide | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gs-9973 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
amg 925 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
gne-618 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
g007-lk | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
volitinib | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ML355 | | benzothiazoles; monomethoxybenzene; phenols; secondary amino compound; substituted aniline; sulfonamide | EC 1.13.11.31 (arachidonate 12-lipoxygenase) inhibitor; platelet aggregation inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
acp-196 | | aromatic amine; benzamides; imidazopyrazine; pyridines; pyrrolidinecarboxamide; secondary carboxamide; tertiary carboxamide; ynone | antineoplastic agent; apoptosis inducer; EC 2.7.10.2 (non-specific protein-tyrosine kinase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gsk343 | | aminopyridine; indazoles; N-alkylpiperazine; N-arylpiperazine; pyridone; secondary carboxamide | antineoplastic agent; apoptosis inducer; EC 2.1.1.43 (enhancer of zeste homolog 2) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
agi-6780 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
khs101 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
cb-839 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
gsk-j4 | | organonitrogen heterocyclic compound | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pf-06424439 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
etp-46464 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
onc201 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
kai407 | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
6,7-dimethoxy-2-(pyrrolidin-1-yl)-n-(5-(pyrrolidin-1-yl)pentyl)quinazolin-4-amine | | | | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
enasidenib | | 1,3,5-triazines; aminopyridine; aromatic amine; organofluorine compound; secondary amino compound; tertiary alcohol | antineoplastic agent; EC 1.1.1.42 (isocitrate dehydrogenase) inhibitor | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
oicr-9429 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
lly-507 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
at 9283 | | | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
chir 258 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
osi 027 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
hypoxanthine | | nucleobase analogue; oxopurine; purine nucleobase | fundamental metabolite | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
clozapine | | benzodiazepine; N-arylpiperazine; N-methylpiperazine; organochlorine compound | adrenergic antagonist; dopaminergic antagonist; EC 3.4.21.26 (prolyl oligopeptidase) inhibitor; environmental contaminant; GABA antagonist; histamine antagonist; muscarinic antagonist; second generation antipsychotic; serotonergic antagonist; xenobiotic | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
hli 373 | | | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
pemetrexed | | N-acyl-L-glutamic acid; pyrrolopyrimidine | antimetabolite; antineoplastic agent; EC 1.5.1.3 (dihydrofolate reductase) inhibitor; EC 2.1.1.45 (thymidylate synthase) inhibitor; EC 2.1.2.2 (phosphoribosylglycinamide formyltransferase) inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1-hydroxyphenazine | | phenazines | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
sildenafil citrate | | citrate salt | EC 3.1.4.35 (3',5'-cyclic-GMP phosphodiesterase) inhibitor; vasodilator agent | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
aprepitant | | (trifluoromethyl)benzenes; cyclic acetal; morpholines; triazoles | antidepressant; antiemetic; neurokinin-1 receptor antagonist; peripheral nervous system drug; substance P receptor antagonist | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
xav939 | | (trifluoromethyl)benzenes; thiopyranopyrimidine | tankyrase inhibitor | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-carboxyarabinitol 1-phosphate | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
ro 24-7429 | | benzodiazepine | | 2017 | 2020 | 5.3 | medium | 0 | 0 | 0 | 0 | 3 | 0 |
nintedanib | | | | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
n'-(3,4-dihydroxybenzylidene)-3-hydroxy-2-naphthahydrazide | | catechols; hydrazide; hydrazone; naphthols | EC 3.6.5.5 (dynamin GTPase) inhibitor | 2017 | 2020 | 5.3 | high | 0 | 0 | 0 | 0 | 3 | 0 |
ver 52296 | | aromatic amide; isoxazoles; monocarboxylic acid amide; morpholines; resorcinols | angiogenesis inhibitor; antineoplastic agent; Hsp90 inhibitor | 2013 | 2020 | 6.8 | low | 0 | 0 | 0 | 0 | 4 | 0 |
sb-590885 | | aromatic ether; imidazoles; ketoxime; pyridines; tertiary amino compound | | 2013 | 2013 | 11.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
rvx 208 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
bmn 673 | | | | 2017 | 2020 | 5.3 | low | 0 | 0 | 0 | 0 | 3 | 0 |
pf-477736 | | | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
fenobam | | ureas | | 2013 | 2013 | 11.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters, , Aug-01, Volume: 23, Issue:15, 2013
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.Scientific reports, , 11-26, Volume: 10, Issue:1, 2020
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.Bioorganic & medicinal chemistry, , 07-15, Volume: 27, Issue:14, 2019
Highly predictive and interpretable models for PAMPA permeability.Bioorganic & medicinal chemistry, , 02-01, Volume: 25, Issue:3, 2017
Bioavailability (2)