Page last updated: 2024-08-21

emetine and thioridazine

emetine has been researched along with thioridazine in 5 studies

Research

Studies (5)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's3 (60.00)29.6817
2010's2 (40.00)24.3611
2020's0 (0.00)2.80

Authors

AuthorsStudies
Johans, C; Kinnunen, PK; Söderlund, T; Suomalainen, P1
Cianchetta, G; Cruciani, G; Fravolini, A; Giesing, D; Singleton, RW; Vaz, RJ; Wildgoose, M; Zhang, M1
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

Other Studies

5 other study(ies) available for emetine and thioridazine

ArticleYear
Surface activity profiling of drugs applied to the prediction of blood-brain barrier permeability.
    Journal of medicinal chemistry, 2004, Mar-25, Volume: 47, Issue:7

    Topics: Blood-Brain Barrier; Lipid Bilayers; Micelles; Permeability; Pharmaceutical Preparations; Structure-Activity Relationship; Surface Properties

2004
A pharmacophore hypothesis for P-glycoprotein substrate recognition using GRIND-based 3D-QSAR.
    Journal of medicinal chemistry, 2005, Apr-21, Volume: 48, Issue:8

    Topics: ATP Binding Cassette Transporter, Subfamily B, Member 1; Biological Transport; Caco-2 Cells; Fluoresceins; Fluorescent Dyes; Humans; Models, Molecular; Multivariate Analysis; Permeability; Quantitative Structure-Activity Relationship

2005
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