期刊
ADVANCED DRUG DELIVERY REVIEWS
卷 86, 期 -, 页码 61-71出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.addr.2015.04.020
关键词
Cytochrome P450; Site of metabolism; Machine learning; Ligand-based models; Structure-based models; Reactivity; Docking; Molecular dynamics
资金
- European Research Council (ERC) [260408]
- Vienna Science and Technology Fund (WWTF) [LS08-QM03]
Cytochrome P450 enzymes (CYPs) form one of the most important enzyme families involved in the metabolism of xenobiotics. CYPs comprise many isoforms, which catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be formed. However, it is often hard to rationalize what metabolites these enzymes generate. In recent years, many different in silico approaches have been developed to predict binding or regioselective product formation for the different CYP isoforms. These comprise ligand-based methods that are trained on experimental CYP data and structure-based methods that consider how the substrate is oriented in the active site or/and how reactive the part of the substrate that is accessible to the heme group is. We will review key aspects for various approaches that are available to predict binding and site of metabolism (SOM), what outcome can be expected from the predictions, and how they could potentially be improved. (C) 2015 Elsevier B.V. All rights reserved.
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