quinacrine and citalopram

quinacrine has been researched along with citalopram in 9 studies

Research

Studies (9)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's4 (44.44)29.6817
2010's5 (55.56)24.3611
2020's0 (0.00)2.80

Authors

AuthorsStudies
Gao, F; Lombardo, F; Obach, RS; Shalaeva, MY1
Bleich, S; Gulbins, E; Kornhuber, J; Reichel, M; Terfloth, L; Tripal, P; Wiltfang, J1
Lombardo, F; Obach, RS; Waters, NJ1
Barnes, JC; Bradley, P; Day, NC; Fourches, D; Reed, JZ; Tropsha, A1
Choi, SS; Contrera, JF; Hastings, KL; Kruhlak, NL; Sancilio, LF; Weaver, JL; Willard, JM1
García-Mera, X; González-Díaz, H; Prado-Prado, FJ1
Glen, RC; Lowe, R; Mitchell, JB1
Atzpodien, EA; Csato, M; Doessegger, L; Fischer, H; Lenz, B; Schmitt, G; Singer, T1
Fijorek, K; Glinka, A; Mendyk, A; Polak, S; Wiśniowska, B1

Other Studies

9 other study(ies) available for quinacrine and citalopram

ArticleYear
Prediction of human volume of distribution values for neutral and basic drugs. 2. Extended data set and leave-class-out statistics.
    Journal of medicinal chemistry, 2004, Feb-26, Volume: 47, Issue:5

    Topics: Algorithms; Blood Proteins; Half-Life; Humans; Hydrogen-Ion Concentration; Models, Biological; Pharmaceutical Preparations; Pharmacokinetics; Protein Binding; Statistics as Topic; Tissue Distribution

2004
Identification of new functional inhibitors of acid sphingomyelinase using a structure-property-activity relation model.
    Journal of medicinal chemistry, 2008, Jan-24, Volume: 51, Issue:2

    Topics: Algorithms; Animals; Cell Line; Cell Line, Tumor; Chemical Phenomena; Chemistry, Physical; Enzyme Inhibitors; Humans; Hydrogen-Ion Concentration; Molecular Conformation; Quantitative Structure-Activity Relationship; Rats; Sphingomyelin Phosphodiesterase

2008
Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.
    Drug metabolism and disposition: the biological fate of chemicals, 2008, Volume: 36, Issue:7

    Topics: Blood Proteins; Half-Life; Humans; Hydrogen Bonding; Infusions, Intravenous; Pharmacokinetics; Protein Binding

2008
Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.
    Chemical research in toxicology, 2010, Volume: 23, Issue:1

    Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

2010
Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models.
    Toxicology mechanisms and methods, 2008, Volume: 18, Issue:2-3

    Topics:

2008
Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species.
    Bioorganic & medicinal chemistry, 2010, Mar-15, Volume: 18, Issue:6

    Topics: Antiparasitic Agents; Molecular Structure; Neural Networks, Computer; Parasitic Diseases; Quantitative Structure-Activity Relationship; Species Specificity; Thermodynamics

2010
Predicting phospholipidosis using machine learning.
    Molecular pharmaceutics, 2010, Oct-04, Volume: 7, Issue:5

    Topics: Animals; Artificial Intelligence; Databases, Factual; Drug Discovery; Humans; Lipidoses; Models, Biological; Phospholipids; Support Vector Machine

2010
In silico assay for assessing phospholipidosis potential of small druglike molecules: training, validation, and refinement using several data sets.
    Journal of medicinal chemistry, 2012, Jan-12, Volume: 55, Issue:1

    Topics: Animals; Cattle; Cells, Cultured; Computer Simulation; Cornea; Drug-Related Side Effects and Adverse Reactions; Fibroblasts; Lipidoses; Lysosomal Storage Diseases; Models, Molecular; Pharmaceutical Preparations; Phospholipids; Structure-Activity Relationship; Thermodynamics

2012
Predictive model for L-type channel inhibition: multichannel block in QT prolongation risk assessment.
    Journal of applied toxicology : JAT, 2012, Volume: 32, Issue:10

    Topics: Artificial Intelligence; Calcium Channel Blockers; Calcium Channels, L-Type; Cell Line; Computational Biology; Computer Simulation; Drugs, Investigational; Ether-A-Go-Go Potassium Channels; Expert Systems; Heart Rate; Humans; Models, Biological; Myocytes, Cardiac; NAV1.5 Voltage-Gated Sodium Channel; Potassium Channel Blockers; Quantitative Structure-Activity Relationship; Risk Assessment; Shaker Superfamily of Potassium Channels; Torsades de Pointes; Voltage-Gated Sodium Channel Blockers

2012