Virtual screening of cytochrome P450 2A6 inhibitors from traditional Chinese medicine using support vector machine and molecular docking

Abstract

Cytochrome P450 2A6 (CYP2A6), which is a member of the cytochrome P450 (CYP450) mixed-function oxidase system and is highly expressed in liver, is involved in the metabolism of drugs in the body. The inhibition of it often reduces the metabolic rate of the corresponding metabolites and then may cause unwanted drug-drug interaction (DDI). In this study, discriminative models of CYP2A6 inhibitors were created by using the support vector machine (SVM) method. And the optimal model was selected based on three assessment criteria, including accuracy, sensitivity and specificity, which were all above 95%. Then, the optimal model was used to distinguish potential inhibitors of CYP2A6 from traditional Chinese medicine database (TCMD), which resulting in a hit list of 619 compounds. These compounds were further refined by using molecular docking and then 23 compounds with higher scores than the original ligand in the crystal structure of CYP2A6 enzyme were retained. Among them, Peucedanin, which has better prediction results, might exhibits inhibition effect on CYP2A6. This paper suggests the applicability of computational methods for obtaining potential inhibitors of CYP2A6 from Natural Products, and also provides guidance for the rational application of drugs in clinical.