Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes
CYPlebrity is a collection of machine learning models for the prediction of whether or not a small organic compound is an inhibitor of different human CYPs. Currently, CYPlebrity covers CYPs 1A2, 2C9, 2C19, 2D6 and 3A4. The models are characterized by their wide applicability domain, a result of the training on a comprehensive bioactivity database compiled from the PubChem Bioassay database (AIDs 1851, 410, 883, 884, 899 and 891), the ChEMBL database and the ADME Database (Fujitsu).
The research was funded by Fujitsu and the WEB SERVICE IS PROVIDED FREE OF CHARGE FOR ACADEMIC RESEARCH.
If you are using
for your research, please cite all of the following publications:
Will follow soon ...
Stork, C.; Embruch, G.; Šícho, M.; de Bruyn Kops, C.; Chen, Y.;
Svozil, D.; Kirchmair, J. NERDD: a web portal providing access to in
silico tools for drug discovery. Bioinformatics2020.