Compounds > hydrocortisone acetate, (11beta)-isomer
Page last updated: 2024-08-01 21:05:08
hydrocortisone acetate, (11beta)-isomer
Description
Cross-References
ID Source | ID |
PubMed CID | 5702068 |
CHEMBL ID | 306147 |
SCHEMBL ID | 2679809 |
MeSH ID | M0314595 |
Synonyms (42)
Synonym |
gnf-pf-4997 , |
CHEMBL306147 |
BRD-A65767837-001-02-8 |
KBIO1_000194 |
DIVK1C_000194 |
SPECTRUM_000879 |
IDI1_000194 |
BSPBIO_002134 |
NCGC00178800-01 |
SPECTRUM5_000826 |
KBIO2_003927 |
KBIOSS_001359 |
KBIOGR_000353 |
KBIO2_001359 |
KBIO3_001354 |
KBIO2_006495 |
NINDS_000194 |
SPECTRUM2_001030 |
SPECTRUM4_000007 |
SPECTRUM3_000457 |
SPBIO_001219 |
SPECTRUM1500338 |
HMS2091L07 |
HMS500J16 |
HMS1920D21 |
NCGC00183367-01 |
cas-50-03-3 |
tox21_113074 |
dtxcid0028612 |
dtxsid0048686 , |
pharmakon1600-01500338 |
nsc-757060 |
nsc757060 |
CCG-40248 |
NCGC00021277-04 |
tox21_113074_1 |
SCHEMBL2679809 |
AB00052014_02 |
SR-05000001650-1 |
sr-05000001650 |
SBI-0051408.P003 |
BRD-A65767837-001-03-6 |
Protein Targets (12)
Potency Measurements
Bioassays (66)
Assay ID | Title | Year | Journal | Article |
AID73417 | Inhibition of human Farnesyltransferase at 100 uM | 1998 | Journal of medicinal chemistry, Nov-05, Volume: 41, Issue:23 ISSN: 0022-2623 | Clavaric acid and steroidal analogues as Ras- and FPP-directed inhibitors of human farnesyl-protein transferase. |
AID449704 | NOVARTIS: Inhibition of Plasmodium falciparum W2 (drug-resistant) proliferation in erythrocyte-based infection assay | 2008 | Proceedings of the National Academy of Sciences of the United States of America, Jul-01, Volume: 105, Issue:26 ISSN: 1091-6490 | In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. |
AID449703 | NOVARTIS: Inhibition of Plasmodium falciparum 3D7 (drug-susceptible) proliferation in erythrocyte-based infection assay | 2008 | Proceedings of the National Academy of Sciences of the United States of America, Jul-01, Volume: 105, Issue:26 ISSN: 1091-6490 | In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. |
AID51052 | In silico binding affinity to corticosteroid binding globulin (CBG) | 1997 | Journal of medicinal chemistry, Dec-19, Volume: 40, Issue:26 ISSN: 0022-2623 | Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations. |
AID449706 | NOVARTIS: Inhibition Frequency Index (IFI) - the number of HTS assays where a compound showed > 50% inhibition/induction, expressed as a percentage of the number of assays in which the compound was tested. | 2008 | Proceedings of the National Academy of Sciences of the United States of America, Jul-01, Volume: 105, Issue:26 ISSN: 1091-6490 | In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. |
AID449705 | NOVARTIS: Cytotoxicity against human hepatocellular carcinoma cell line (Huh7) | 2008 | Proceedings of the National Academy of Sciences of the United States of America, Jul-01, Volume: 105, Issue:26 ISSN: 1091-6490 | In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. |
AID51062 | In silico steroid binding affinity to transport protein corticosteroid binding globulin | 1994 | Journal of medicinal chemistry, Jul-22, Volume: 37, Issue:15 ISSN: 0022-2623 | Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark. |
AID51053 | Compound was evaluated for its binding affinity towards the human corticosteroid binding globulin | 1999 | Journal of medicinal chemistry, Feb-25, Volume: 42, Issue:4 ISSN: 0022-2623 | Self-organizing molecular field analysis: a tool for structure-activity studies. |
AID51048 | In silico binding affinity to human corticosteriod binding globulin | 1997 | Journal of medicinal chemistry, Sep-26, Volume: 40, Issue:20 ISSN: 0022-2623 | Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data. |
AID540299 | A screen for compounds that inhibit the MenB enzyme of Mycobacterium tuberculosis | 2010 | Bioorganic & medicinal chemistry letters, Nov-01, Volume: 20, Issue:21 ISSN: 1464-3405 | Synthesis and SAR studies of 1,4-benzoxazine MenB inhibitors: novel antibacterial agents against Mycobacterium tuberculosis. |
AID588519 | A screen for compounds that inhibit viral RNA polymerase binding and polymerization activities | 2011 | Antiviral research, Sep, Volume: 91, Issue:3 ISSN: 1872-9096 | High-throughput screening identification of poliovirus RNA-dependent RNA polymerase inhibitors. |
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. |
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. |
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. |
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. |
AID651635 | Viability Counterscreen for Primary qHTS for Inhibitors of ATXN expression | 2022 | The Journal of biological chemistry, 08, Volume: 298, Issue:8 ISSN: 1083-351X | |
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. |
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. |
AID1347407 | qHTS to identify inhibitors of the type 1 interferon - major histocompatibility complex class I in skeletal muscle: primary screen against the NCATS Pharmaceutical Collection | 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. |
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. |
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. |
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. |
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. |
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. |
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. |
AID1745845 | Primary qHTS for Inhibitors of ATXN expression | 2022 | The Journal of biological chemistry, 08, Volume: 298, Issue:8 ISSN: 1083-351X | |
AID1347124 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347119 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
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. |
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. |
AID1347425 | Rhodamine-PBP qHTS Assay for Modulators of WT P53-Induced Phosphatase 1 (WIP1) | 2019 | The Journal of biological chemistry, 11-15, Volume: 294, Issue:46 ISSN: 1083-351X | Physiologically relevant orthogonal assays for the discovery of small-molecule modulators of WIP1 phosphatase in high-throughput screens. |
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. |
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. |
AID1347113 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
AID1347114 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347125 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
AID1347129 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347128 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
AID1347110 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
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. |
AID1347122 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347126 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347118 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347111 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347127 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
AID1347123 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347112 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
AID1347116 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347109 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
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. |
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. |
AID1347121 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347117 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347115 | qHTS of pediatric cancer cell lines to identify multiple opportunities for drug repurposing: Confirmatory 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. |
AID1347424 | RapidFire Mass Spectrometry qHTS Assay for Modulators of WT P53-Induced Phosphatase 1 (WIP1) | 2019 | The Journal of biological chemistry, 11-15, Volume: 294, Issue:46 ISSN: 1083-351X | Physiologically relevant orthogonal assays for the discovery of small-molecule modulators of WIP1 phosphatase in high-throughput screens. |
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. |
AID1159607 | Screen for inhibitors of RMI FANCM (MM2) intereaction | 2016 | Journal of biomolecular screening, Jul, Volume: 21, Issue:6 ISSN: 1552-454X | A High-Throughput Screening Strategy to Identify Protein-Protein Interaction Inhibitors That Block the Fanconi Anemia DNA Repair Pathway. |
AID602156 | Novartis GNF Liver Stage Dataset: Malariabox Annotation | 2011 | Science (New York, N.Y.), Dec-09, Volume: 334, Issue:6061 ISSN: 1095-9203 | Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery. |
Research
Studies (19)
Timeframe | Studies, This Drug (%) | All Drugs % |
pre-1990 | 0 (0.00) | 18.7374 |
1990's | 5 (26.32) | 18.2507 |
2000's | 1 (5.26) | 29.6817 |
2010's | 7 (36.84) | 24.3611 |
2020's | 6 (31.58) | 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 | 19 (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 |
quinacrine | | acridines; aromatic ether; organochlorine compound; tertiary amino compound | antimalarial; EC 1.8.1.12 (trypanothione-disulfide reductase) inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid | | non-proteinogenic alpha-amino acid | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
1,3-dipropyl-8-cyclopentylxanthine | | oxopurine | adenosine A1 receptor antagonist; EC 3.1.4.* (phosphoric diester hydrolase) inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
nsc-267703 | | anthracycline | | 2011 | 2011 | 13.0 | high | 0 | 0 | 0 | 0 | 1 | 0 |
dactinomycin | | cyclodepsipeptide | | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
1-aminoindan-1,5-dicarboxylic acid | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
amodiaquine | | aminoquinoline; organochlorine compound; phenols; secondary amino compound; tertiary amino compound | anticoronaviral agent; antimalarial; drug allergen; EC 2.1.1.8 (histamine N-methyltransferase) inhibitor; non-steroidal anti-inflammatory drug; prodrug | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
astemizole | | benzimidazoles; piperidines | anti-allergic agent; anticoronaviral agent; H1-receptor antagonist | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
berberine | | alkaloid antibiotic; berberine alkaloid; botanical anti-fungal agent; organic heteropentacyclic compound | antilipemic drug; antineoplastic agent; antioxidant; EC 1.1.1.141 [15-hydroxyprostaglandin dehydrogenase (NAD(+))] inhibitor; EC 1.1.1.21 (aldehyde reductase) inhibitor; EC 1.13.11.52 (indoleamine 2,3-dioxygenase) inhibitor; EC 1.21.3.3 (reticuline oxidase) inhibitor; EC 2.1.1.116 [3'-hydroxy-N-methyl-(S)-coclaurine 4'-O-methyltransferase] inhibitor; EC 2.1.1.122 [(S)-tetrahydroprotoberberine N-methyltransferase] inhibitor; EC 2.7.11.10 (IkappaB kinase) inhibitor; EC 3.1.1.4 (phospholipase A2) inhibitor; EC 3.1.1.7 (acetylcholinesterase) inhibitor; EC 3.1.1.8 (cholinesterase) inhibitor; EC 3.1.3.48 (protein-tyrosine-phosphatase) inhibitor; EC 3.4.14.5 (dipeptidyl-peptidase IV) inhibitor; EC 3.4.21.26 (prolyl oligopeptidase) inhibitor; geroprotector; hypoglycemic agent; metabolite; potassium channel blocker | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
chloroquine | | aminoquinoline; organochlorine compound; secondary amino compound; tertiary amino compound | anticoronaviral agent; antimalarial; antirheumatic drug; autophagy inhibitor; dermatologic drug | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
aricine | | cinchona alkaloid | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
clofilium | | benzenes; organic amino compound | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
clotrimazole | | conazole antifungal drug; imidazole antifungal drug; imidazoles; monochlorobenzenes | antiinfective agent; environmental contaminant; xenobiotic | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
dequalinium | | quinolinium ion | antifungal agent; antineoplastic agent; antiseptic drug; mitochondrial NADH:ubiquinone reductase inhibitor | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
thiorphan | | N-acyl-amino acid | | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
nsc-526417 | | | | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
gentian violet | | iminium ion | antibacterial agent; antifungal agent | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
hexahydrosiladifenidol | | | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
mefloquine hydrochloride | | organofluorine compound; piperidines; quinolines; secondary alcohol | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
moclobemide | | benzamides; monochlorobenzenes; morpholines | antidepressant; environmental contaminant; xenobiotic | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
n-acetyl-4-nitrophenylserinol | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
oxiracetam | | organonitrogen compound; organooxygen compound | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
pentamidine | | aromatic ether; carboxamidine; diether | anti-inflammatory agent; antifungal agent; calmodulin antagonist; chemokine receptor 5 antagonist; EC 2.3.1.48 (histone acetyltransferase) inhibitor; NMDA receptor antagonist; S100 calcium-binding protein B inhibitor; trypanocidal drug; xenobiotic | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
pronethalol | | naphthalenes | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
propafenone | | aromatic ketone; secondary alcohol; secondary amino compound | anti-arrhythmia drug | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
pyrimethamine | | aminopyrimidine; monochlorobenzenes | antimalarial; antiprotozoal drug; EC 1.5.1.3 (dihydrofolate reductase) inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
scriptaid | | isoquinolines | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
trimethoprim | | aminopyrimidine; methoxybenzenes | antibacterial drug; diuretic; drug allergen; EC 1.5.1.3 (dihydrofolate reductase) inhibitor; environmental contaminant; xenobiotic | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
6,18,30-trimethyl-3,9,12,15,21,24,27,33,36-nona(propan-2-yl)-1,7,13,19,25,31-hexaoxa-4,10,16,22,28,34-hexazacyclohexatriacontane-2,5,8,11,14,17,20,23,26,29,32,35-dodecone | | cyclodepsipeptide | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
cortisone acetate | | corticosteroid hormone | | 1998 | 1998 | 26.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
corticosterone | | 11beta-hydroxy steroid; 20-oxo steroid; 21-hydroxy steroid; 3-oxo-Delta(4) steroid; C21-steroid; glucocorticoid; primary alpha-hydroxy ketone | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
prednisolone | | 11beta-hydroxy steroid; 17alpha-hydroxy steroid; 20-oxo steroid; 21-hydroxy steroid; 3-oxo-Delta(1),Delta(4)-steroid; C21-steroid; glucocorticoid; primary alpha-hydroxy ketone; tertiary alpha-hydroxy ketone | adrenergic agent; anti-inflammatory drug; antineoplastic agent; drug metabolite; environmental contaminant; immunosuppressive agent; xenobiotic | 1994 | 1999 | 27.2 | low | 0 | 0 | 4 | 0 | 0 | 0 |
estriol | | 16alpha-hydroxy steroid; 17beta-hydroxy steroid; 3-hydroxy steroid | estrogen; human metabolite; human xenobiotic metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
estrone | | 17-oxo steroid; 3-hydroxy steroid; phenolic steroid; phenols | antineoplastic agent; bone density conservation agent; estrogen; human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
androsterone | | 17-oxo steroid; 3alpha-hydroxy steroid; androstanoid; C19-steroid | androgen; anticonvulsant; human blood serum metabolite; human metabolite; human urinary metabolite; mouse metabolite; pheromone | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
etiocholanolone | | 17-oxo steroid; 3alpha-hydroxy steroid; androstanoid | human metabolite; mouse metabolite | 1994 | 1997 | 28.5 | low | 0 | 0 | 2 | 0 | 0 | 0 |
androstenedione | | 17-oxo steroid; 3-oxo-Delta(4) steroid; androstanoid | androgen; Daphnia magna metabolite; human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
desoxycorticosterone | | 20-oxo steroid; 21-hydroxy steroid; 3-oxo-Delta(4) steroid; mineralocorticoid; primary alpha-hydroxy ketone | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
cycloheximide | | antibiotic fungicide; cyclic ketone; dicarboximide; piperidine antibiotic; piperidones; secondary alcohol | anticoronaviral agent; bacterial metabolite; ferroptosis inhibitor; neuroprotective agent; protein synthesis inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
17-alpha-hydroxyprogesterone | | 17alpha-hydroxy-C21-steroid; 17alpha-hydroxy steroid; tertiary alpha-hydroxy ketone | human metabolite; metabolite; mouse metabolite; progestin | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
phanquinone | | orthoquinones | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
diphenan | | diarylmethane | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
2-phenylacetamide | | monocarboxylic acid amide | mouse metabolite | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
tetraphenylborate | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
pregnenolone | | 20-oxo steroid; 3beta-hydroxy-Delta(5)-steroid; C21-steroid | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
cycloguanil hydrochloride | | hydrochloride; organic molecular entity | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
cycloguanil | | triazines | antifolate; antiinfective agent; antimalarial; antiparasitic agent; antiprotozoal drug; EC 1.5.1.3 (dihydrofolate reductase) inhibitor | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
triphenyltetrazolium | | organic cation | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
nandrolone | | 17beta-hydroxy steroid; 3-oxo-Delta(4) steroid; anabolic androgenic steroid | human metabolite | 1994 | 1999 | 27.2 | low | 0 | 0 | 4 | 0 | 0 | 0 |
berbamine | | phenylpropanoid | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 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 | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
androstenediol | | 17beta-hydroxy steroid; 3beta-hydroxy-Delta(5)-steroid | androgen; human metabolite; mouse metabolite; radiation protective agent | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
dihydrotestosterone | | 17beta-hydroxy steroid; 17beta-hydroxyandrostan-3-one; 3-oxo-5alpha-steroid | androgen; Daphnia magna metabolite; human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
dequalinium chloride | | organic chloride salt | antifungal agent; antineoplastic agent; antiseptic drug; mitochondrial NADH:ubiquinone reductase inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
gentian violet | | organic chloride salt | anthelminthic drug; antibacterial agent; antifungal agent; antiseptic drug; histological dye | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
algestone | | 16alpha-hydroxy steroid; 17-hydroxy steroid; 20-oxo steroid; 3-oxo-Delta(4) steroid; C21-steroid; tertiary alpha-hydroxy ketone | progestin | 1994 | 1999 | 27.2 | low | 0 | 0 | 4 | 0 | 0 | 0 |
Berberine chloride (TN) | | organic molecular entity | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
9,10-dimethylanthracene | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
c 137 | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
palmatine | | berberine alkaloid; organic heterotetracyclic compound | plant metabolite | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
4,6-diamino-2,2-dimethyl-1,2-dihydro-1-phenyl-s-triazine | | | | 1997 | 2011 | 20.0 | low | 0 | 0 | 1 | 0 | 1 | 0 |
diaveridine | | aminopyrimidine | antiparasitic agent; drug allergen | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
buquinolate | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
propranolol glycol | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
naphthoxybutanolcyclohexylamine | | | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
captopril | | alkanethiol; L-proline derivative; N-acylpyrrolidine; pyrrolidinemonocarboxylic acid | antihypertensive agent; EC 3.4.15.1 (peptidyl-dipeptidase A) inhibitor | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
staurosporine | | indolocarbazole alkaloid; organic heterooctacyclic compound | apoptosis inducer; bacterial metabolite; EC 2.7.11.13 (protein kinase C) inhibitor; geroprotector | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
propamidine | | aromatic ether; guanidines; polyether | antimicrobial agent; antiseptic drug | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
thionine | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
neocuproine | | phenanthrolines | chelator; copper chelator | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
mefloquine hydrochloride | | hydrochloride | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
toxoflavin | | carbonyl compound; pyrimidotriazine | antibacterial agent; antineoplastic agent; apoptosis inducer; bacterial metabolite; toxin; virulence factor; Wnt signalling inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
selfotel | | non-proteinogenic alpha-amino acid | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
plasmenylserine | | O-phosphoserine | EC 1.4.7.1 [glutamate synthase (ferredoxin)] inhibitor; EC 2.5.1.49 (O-acetylhomoserine aminocarboxypropyltransferase) inhibitor; EC 4.3.1.10 (serine-sulfate ammonia-lyase) inhibitor; Escherichia coli metabolite; human metabolite; mouse metabolite; Saccharomyces cerevisiae metabolite | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
quinocide | | | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2,2',2''-terpyridine | | terpyridines | chelator | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
clobetasone butyrate | | organic molecular entity | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cletoquine | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
jatrorrhizine | | alkaloid | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
lycorine | | indolizidine alkaloid | anticoronaviral agent; antimalarial; plant metabolite; protein synthesis inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
bathophenanthroline | | benzenes; phenanthrolines | chelator | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
fascaplysine | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
LSM-4272 | | beta-carbolines | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
tryptanthrine | | alkaloid antibiotic; organic heterotetracyclic compound; organonitrogen heterocyclic compound | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
2,4-diamino-5-benzylpyrimidine | | | | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
ethylhydrocupreine | | aromatic ether; cinchona alkaloid | EC 3.6.3.10 (H(+)/K(+)-exchanging ATPase) inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
2,4-diamino-5,6-dihydro-6,6-dimethyl-5-(4'-methoxyphenyl)-s-triazine | | | | 1997 | 2011 | 20.0 | medium | 0 | 0 | 1 | 0 | 1 | 0 |
cinchonine | | (8xi)-cinchonan-9-ol; cinchona alkaloid | metabolite | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
17-alpha-hydroxypregnenolone | | 17alpha-hydroxy-C21-steroid; 17alpha-hydroxy steroid; 3beta-hydroxy-Delta(5)-steroid; hydroxypregnenolone; tertiary alpha-hydroxy ketone | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
11-ketoprogesterone | | corticosteroid hormone | | 1994 | 1999 | 27.2 | medium | 0 | 0 | 4 | 0 | 0 | 0 |
7-chloro-4-aminoquinoline | | aminoquinoline | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
mmv665852 | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
1,3,4,10-Tetrahydro-9(2H)-acridinone | | acridines | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
wr 158122 | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
10-deazaaminopterin | | | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2 alpha-methyl-9 alpha-fluorocortisol | | | | 1994 | 1999 | 27.2 | high | 0 | 0 | 4 | 0 | 0 | 0 |
dihydroergocristine | | ergot alkaloid | adrenergic antagonist; vasodilator agent | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
benzamil | | guanidines; pyrazines | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
3',4'-dichlorobenzamil | | guanidines; pyrazines | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
cleistanthin b | | beta-D-glucoside; cleistanthins; monosaccharide derivative | alpha-adrenergic antagonist; antihypertensive agent; diuretic | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
n-acetyltyramine | | acetamides; tyramines | animal metabolite; Aspergillus metabolite; bacterial metabolite; marine metabolite; quorum sensing inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
1,3-di(4-imidazolinophenoxyl)propane | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
7h-pyrido(4,3-c)carbazole | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
imiloxan | | benzodioxine | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
cl 246738 | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
retrothiorphan | | | | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
a 58365a | | | | 1997 | 1997 | 27.0 | medium | 0 | 0 | 1 | 0 | 0 | 0 |
celastrol methyl ester | | carboxylic ester | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
epiberberine | | | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-phenyl-4-oxohydroquinoline | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
cypripedin | | phenanthrol | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
respinomycin d | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
azacrin | | | | 2008 | 2008 | 16.0 | medium | 0 | 0 | 0 | 1 | 0 | 0 |
cortisone | | 11-oxo steroid; 17alpha-hydroxy steroid; 20-oxo steroid; 21-hydroxy steroid; 3-oxo-Delta(4) steroid; C21-steroid; glucocorticoid; primary alpha-hydroxy ketone; tertiary alpha-hydroxy ketone | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
acetoxycycloheximide | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
(R)-Roemerine | | isoquinoline alkaloid | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
5 alpha-androstane-3 beta,17 beta-diol | | 17beta-hydroxy steroid; 3beta-hydroxy steroid; androstane-3,17-diol | Daphnia magna metabolite; human metabolite | 1994 | 1997 | 28.0 | high | 0 | 0 | 3 | 0 | 0 | 0 |
anisomycin | | monohydroxypyrrolidine; organonitrogen heterocyclic antibiotic | anticoronaviral agent; antimicrobial agent; antineoplastic agent; antiparasitic agent; bacterial metabolite; DNA synthesis inhibitor; protein synthesis inhibitor | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
2-guanidine-4-methylquinazoline | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
jatrorrhizine chloride | | | | 2008 | 2008 | 16.0 | medium | 0 | 0 | 0 | 1 | 0 | 0 |
mensacarcin | | | | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
puromycin | | puromycins | antiinfective agent; antimicrobial agent; antineoplastic agent; EC 3.4.11.14 (cytosol alanyl aminopeptidase) inhibitor; EC 3.4.14.2 (dipeptidyl-peptidase II) inhibitor; nucleoside antibiotic; protein synthesis inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
cortodoxone | | deoxycortisol; glucocorticoid; primary alpha-hydroxy ketone; tertiary alpha-hydroxy ketone | human metabolite; mouse metabolite | 1994 | 1997 | 28.0 | low | 0 | 0 | 3 | 0 | 0 | 0 |
quinidine | | cinchona alkaloid | alpha-adrenergic antagonist; anti-arrhythmia drug; antimalarial; drug allergen; EC 1.14.13.181 (13-deoxydaunorubicin hydroxylase) inhibitor; EC 3.6.3.44 (xenobiotic-transporting ATPase) inhibitor; muscarinic antagonist; P450 inhibitor; potassium channel blocker; sodium channel blocker | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
cephaelin | | pyridoisoquinoline | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
trichostatin a | | antibiotic antifungal agent; hydroxamic acid; trichostatin | bacterial metabolite; EC 3.5.1.98 (histone deacetylase) inhibitor; geroprotector | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
epothilone b | | epothilone; epoxide | antineoplastic agent; apoptosis inducer; microtubule-stabilising agent | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
wr-142,490 | | [2,8-bis(trifluoromethyl)quinolin-4-yl]-(2-piperidyl)methanol | antimalarial | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
dactinomycin | | actinomycin | mutagen | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
1,3,6-trimethylpyrimido[5,4-e][1,2,4]triazine-5,7-dione | | pyrimidotriazine | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
jp-1302 | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
7-hydroxy-2-methoxy-1,4-phenanthrenedione | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
cgp 60474 | | substituted aniline | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
prednisolone hemisuccinate | | 11beta-hydroxy steroid; 17alpha-hydroxy steroid; 20-oxo steroid; 3-oxo-Delta(1),Delta(4)-steroid; hemisuccinate; tertiary alpha-hydroxy ketone | anti-inflammatory drug | 1998 | 1998 | 26.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
(1S,2R)-2-(octylamino)-1-[4-(propan-2-ylthio)phenyl]-1-propanol | | alkylbenzene | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
2-[2-hydroxy-6,7-dimethoxy-4-(4-morpholinyl)-1-naphthalenyl]-N-phenylacetamide | | naphthols | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N4-(3-chlorophenyl)-6-methyl-N2-(phenylmethyl)pyrimidine-2,4-diamine | | aralkylamine | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
n-(4-methylpyridin-2-yl)-4-(pyridin-2-yl)thiazol-2-amine | | | | 2011 | 2011 | 13.0 | high | 0 | 0 | 0 | 0 | 1 | 0 |
2,6-bis(benzimidazol-2-yl)pyridine | | benzimidazoles | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
n-(pyridin-2-yl)-4-(pyridin-2-yl)thiazol-2-amine | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
N-[4-(1-azepanyl)phenyl]-2-chloroacetamide | | anilide | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N-(4-methylphenyl)carbamic acid (cyclopentylideneamino) ester | | toluenes | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
(2'-(4-aminophenyl)-(2,5'-bi-1h-benzimidazol)-5-amine) | | benzimidazoles | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
1,4,8-trimethyl-12-quinolino[2,3-b]quinolinamine | | aminoquinoline | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
2-furanyl-(4,4,8-trimethyl-1-sulfanylidene-5-dithiolo[3,4-c]quinolinyl)methanone | | aromatic amide; heteroarene | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
1-(6-methoxy-2,2,4-trimethyl-1-quinolinyl)-2-[[5-(4-methylphenyl)-1,3,4-oxadiazol-2-yl]thio]ethanone | | quinolines | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
stk295900 | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
6-(4-methyl-1-piperazinyl)-2-(3,4,5-trimethoxyphenyl)-1H-benzimidazole | | benzimidazoles | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N9-(4-butoxyphenyl)-6,8,10-triazaspiro[4.5]deca-6,9-diene-7,9-diamine | | aromatic ether | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N-[2-[5-(1,3-benzothiazol-2-yl)-3-ethyl-1-phenyl-2-benzimidazol-3-iumyl]ethenyl]-N-methylaniline | | benzimidazoles | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
4-(1-adamantyl)-2-methyl-1,3-thiazole | | thiazoles | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
2-amino-6-[4-(6-chloro-2-pyridinyl)-1-piperazinyl]pyridine-3,5-dicarbonitrile | | piperazines; pyridines | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
1-(4-fluorophenyl)-3-[4-(4-fluorophenyl)-2-methyl-5-(trifluoromethyl)-3-pyrazolyl]urea | | pyrazoles; ring assembly | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
2-(4,6,7-Trimethyl-2-quinazolinyl)guanidine | | quinazolines | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
polysulfide rubber | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
lch-7749944 | | | | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
4-(4-nitrophenyl)-N-prop-2-enyl-1-piperazinecarbothioamide | | piperazines | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
zd 6474 | | aromatic ether; organobromine compound; organofluorine compound; piperidines; quinazolines; secondary amine | antineoplastic agent; tyrosine kinase inhibitor | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
5-bromo-1-(1-oxopropyl)-N,N-dipropyl-2,3-dihydroindole-7-sulfonamide | | indoles | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N-cyclohexyl-5,6,7,8-tetrahydro-4H-cyclohepta[d]isoxazole-3-carboxamide | | aromatic amide; heteroarene | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
2-[(3-ethyl-7-methyl-4-oxo-6,8-dihydro-5H-pyrido[2,3]thieno[2,4-b]pyrimidin-2-yl)thio]-N-(2-phenylethyl)acetamide | | organic heterobicyclic compound; organonitrogen heterocyclic compound; organosulfur heterocyclic compound | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
trichomonacid | | | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
N-(4-bromo-3-methylphenyl)-2,5-dimethyl-[1,2,4]triazolo[1,5-a]pyrimidin-7-amine | | triazolopyrimidines | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
N-(2,3-dihydro-1,4-benzodioxin-6-yl)-2-(2-methoxyethyl)-3-oxo-1H-isoindole-4-carboxamide | | isoindoles | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
cgp 71683 a | | naphthalenes; sulfonic acid derivative | | 2011 | 2011 | 13.0 | medium | 0 | 0 | 0 | 0 | 1 | 0 |
2-(dimethylaminostyryl)-1-ethylpyridinium | | pyridinium ion | | 2011 | 2011 | 13.0 | low | 0 | 0 | 0 | 0 | 1 | 0 |
enalaprilat anhydrous | | dicarboxylic acid; dipeptide | antihypertensive agent; EC 3.4.15.1 (peptidyl-dipeptidase A) inhibitor | 1997 | 1997 | 27.0 | low | 0 | 0 | 1 | 0 | 0 | 0 |
penicillin v | | 1,1'-diethyl-2,2'-cyanine; quinolines | | 2008 | 2008 | 16.0 | medium | 0 | 0 | 0 | 1 | 0 | 0 |
xib 4035 | | | | 2008 | 2011 | 14.5 | medium | 0 | 0 | 0 | 1 | 1 | 0 |
10-hydroxy-3-methyl-8-pentyl-2,4-dihydro-1H-[1]benzopyrano[3,4-c]pyridin-5-one | | pyridochromene | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
lumefantrine | | fluorenes; monochlorobenzenes; secondary alcohol; tertiary amine | antimalarial | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
suloctidil | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
edatrexate | | glutamic acid derivative | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
clavaric acid | | | | 1998 | 1998 | 26.0 | medium | 0 | 0 | 1 | 0 | 0 | 0 |
cgp 71683 a | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
16-methylprogesterone, (16alpha)-isomer | | | | 1997 | 1999 | 26.0 | high | 0 | 0 | 2 | 0 | 0 | 0 |
norketotifen | | organosulfur heterocyclic compound | | 2011 | 2011 | 13.0 | high | 0 | 0 | 0 | 0 | 1 | 0 |
artenimol | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 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 | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
tomaymycin | | tomaymycin | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
amodiaquine hydrochloride | | | | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
gramicidin a | | | | 2008 | 2011 | 14.5 | low | 0 | 0 | 0 | 1 | 1 | 0 |
N-methyl-3-[5-(3-phenylpropyl)-1,3,4-oxadiazol-2-yl]-N-(3-thiophenylmethyl)propanamide | | benzenes | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
rs 39604 | | hydrochloride | serotonergic antagonist | 2008 | 2008 | 16.0 | low | 0 | 0 | 0 | 1 | 0 | 0 |
1-[amino-[(6-methoxy-4-methyl-2-quinazolinyl)amino]methylidene]-3-phenylurea | | quinazolines | | 2008 | 2011 | 14.5 | high | 0 | 0 | 0 | 1 | 1 | 0 |
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Validation of EGSITE2, a mixed integer program for deducing objective site models for experimental binding data.Journal of medicinal chemistry, , Sep-26, Volume: 40, Issue:20, 1997
Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.Journal of medicinal chemistry, , Jul-22, Volume: 37, Issue:15, 1994
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Self-organizing molecular field analysis: a tool for structure-activity studies.Journal of medicinal chemistry, , Feb-25, Volume: 42, Issue:4, 1999
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations.Journal of medicinal chemistry, , Dec-19, Volume: 40, Issue:26, 1997
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061, 2011
In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.Proceedings of the National Academy of Sciences of the United States of America, , Jul-01, Volume: 105, Issue:26, 2008
Bioavailability (3)
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A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein. Molecular pharmacology, , Volume: 96, Issue:5 | 2019 |
Physiologically relevant orthogonal assays for the discovery of small-molecule modulators of WIP1 phosphatase in high-throughput screens. The Journal of biological chemistry, , 11-15, Volume: 294, Issue:46 | 2019 |
Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery. Science (New York, N.Y.), , Dec-09, Volume: 334, Issue:6061 | 2011 |