Computational methods and tools to predict cytochrome P450 metabolism for drug discovery

Jonathan D. Tyzack, Johannes Kirchmair
2019 Chemical Biology and Drug Design  
In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, including CYP substrate and inhibitor predictors, site of metabolism predictors (i.e., metabolically labile sites within potential substrates) and metabolite structure predictors. We summarize the different approaches taken by these models, such as
more » ... methods, machine learning, data mining, quantum chemical methods, molecular interaction fields, and docking. We highlight the scope and limitations of each method and discuss future implications for the field of metabolism prediction in drug discovery. K E Y W O R D S cytochrome P450, drug discovery, enzyme-ligand interaction, machine learning, metabolism, metabolite structures, prediction, reactivity, sites of metabolism This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
doi:10.1111/cbdd.13445 pmid:30471192 fatcat:n63v527reffeblghwdh5v4v4my