Introduction: Preclinical research involves the in vitro monitoring of metabolic stability to deliver compounds with improved ADME profiles. Prediction of the metabolically vulnerable points can substantially help in analyzing CYP-mediated metabolism data and support optimization efforts in drug discovery programs. Moreover, fast and reliable in silico predictions could accelerate the characterization of in vitro/in vivo metabolites.
Areas covered: This paper reviews in silico methods available for CYP-mediated site of metabolism (SOM) prediction. Comprehensive and practical knowledge in this field can guide the identification of best practice and may inspire ideas for the development of novel approaches.
Expert opinion: Comparison of the efficacy of SOM prediction methodologies revealed the general dependency on the studied isoform and substrate set. Increasing knowledge on P450 X-ray structures, on biotransformations and on the mechanistic details of the catalytic cycle revolutionized the prediction of SOM. Although no ultimate solution exits, combined methods covering both steric and electronic effects are preferred on most of the pharmaceutically relevant isoforms.