Cytochrome P450 3A4 metabolizes nearly 50% of the drugs currently in clinical use with a broad range of substrate specificity. Early prediction of metabolites of xenobiotic compounds is crucial for cost efficient drug discovery and development. We developed a new combined model, MLite, for the prediction of regioselectivity in the cytochrome P450 3A4 mediated metabolism. In the model, the ensemble catalyticphorebased docking method was implemented for the accessibility prediction, and the activation energy estimation method of Korzekwa et al. was used for the reactivity prediction. Four major metabolic reactions, aliphatic hydroxylation, N-dealkylation, O-dealkylation, and aromatic hydroxylation reaction, were included and the reaction data, metabolite information, were collected for 72 well-known substrates. The 47 drug molecules were used as the training set, and the 25 well-known substrates were used as the test set for the ensemble catalyticphore-based docking method. MLite predicted correctly about 76% of the first two sites in the ranking list of the test set. This predictability is comparable with that of another combined model, MetaSite, and the recently published QSAR model proposed by Sheridan et al. MLite also offers information about binding configurations of the substrate-enzyme complex. This may be useful in drug modification by the structure-based drug design.
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Computer Science Applications
- Library and Information Sciences