Cytochrome P450 (CYP) is the most important drug-metabolizing enzyme in human beings. Each CYP isoform is able to metabolize a large number of compounds, and if patients take more than one drugs during the treatment, it is possible that some drugs would be metabolized by the same CYP isoform, leading to potential drug-drug interactions and side effects. Therefore, it is necessary to investigate the isoform specificity of CYP substrates. In this study, we constructed a data set consisting of 10

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... ajor CYP isoforms associated with 776 substrates, and used machine learning methods to construct the predictive models based on the features of structural and physicochemical properties of substrates. We also proposed a new method called Improved Bayesian method, which is suitable for small data sets and is able to construct more stable and accurate predictive models compared with other traditional machine learning models. Based on this method, the predictive performance of our method got the accuracy of 86% for the independent test, which was significantly better to the existing models. We believe that our proposed method will facilitate the understanding of drug metabolisms and help the large-scale analysis of drug-drug interactions. Deliv Rev 2002, 54(3):367-383. 18. Ekins S, de Groot MJ, Jones JP: Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome P450 active sites. Drug Metab Dispos 2001, 29(7):936-944. 19. Liu B, Long R, Chou KC: iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an