Prediction of Small‐Molecule Binding to Cytochrome P450 3A4: Flexible Docking Combined with Multidimensional QSAR

Abstract

The inhibition of cytochrome P450 3A4 (CYP3A4) by small molecules is a major mechanism associated with undesired drug-drug interactions, which are responsible for a substantial number of late-stage failures in the pharmaceutical drug-development process. For a quantitative prediction of associated pharmacokinetic parameters, a computational model was developed that allows prediction of the inhibitory potential of 48 structurally diverse molecules. Based on the experimental structure of CYP3A4, possible binding modes were first sampled by using automated docking (Yeti software) taking protein flexibility into account. The results are consistent with both X-ray crystallographic data and data from metabolic studies. Next, an ensemble of energetically favorable orientations was composed into a 4D dataset for use as input for a multidimensional QSAR technique (Raptor software). A dual-shell binding-site model that allows an explicit induced fit was then generated by using hydrophobicity scoring and hydrogen-bond propensity. The simulation reached a cross-validated r2 value of 0.825 and a predictive r2 value of 0.659. On average, the predicted binding affinity of the training ligands deviates by a factor of 2.7 from the experiment; those of the test set deviate by a factor of 3.8 in Ki.