Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism.

• Discussed the significance of in silico CYP450 prediction in drug discovery. • Introduced the major functions and usages of mainstream in silico CYP450 prediction online tools and software packages. • Summarized inhibitor, inducer and substrate information for 52 most frequently prescribed drugs for their interactions with CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 sub-enzymes. • Assessed and compared the performance of four online tools and software package in inhibitor prediction for CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 sub-enzymes. • Provided guidance on selecting suitable in silico tools to predict whether a compound is an inhibitor of a specific CYP450 sub-enzyme. The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme–drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery. [ABSTRACT FROM AUTHOR]