CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes

In silico metabolism prediction requires first predicting whether a specific molecule will interact with one or more specific metabolizing enzymes, then predicting the result of each enzymatic reaction. Here, we provide a computational tool, CypReact, for performing this first task of reactant prediction. Specifically, CypReact takes as input an arbitrary molecule (specified as a SMILES string or a standard SDF file) and any one of the nine of the most important human cytochrome P450 (CYP450) enzymes— CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, or CYP3A4—and accurately predicts whether the query molecule will react with that given CYP450 enzyme. Tests of CypReact, conducted over a data set of 1632 molecules (each considered a “plausible” reactant) show that it is very effective, with a (cross-validation) AUROC (area under the receiver operating characteristiccurve) of 0.83–0.92. We also show that CypReact performs significantly better than other reactant prediction tools such as ADMET...