Development of Robust QSAR Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition

Cytochrome P450 (CYP) enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual CYPs to the total clearance of a new candidate drug. Overreliance on one CYP for clearance levies a high risk of drug-drug interactions; and considering that several human CYP enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major CYP enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific CYPs responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ~5,000 compounds for the three most prominent xenobiotic metabolizing human CYPs, i.e., CYP2C9, CYP2D6 and CYP3A4, and used the datasets to develop quantitative structure-activity relationship models for the prediction of high clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprised of clinically approved low molecular weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based CYP inhibition assay; and through cross-referencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (Balanced accuracies ~0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. Significance Statement In drug discovery and development, a drug candidate with an indiscriminate CYP metabolic profile is considered advantageous, since they provide less risk of potential issues with CYP polymorphisms and drug-drug interactions. In this study, we have developed robust substrate and inhibitor QSAR models for the three major xenobiotic metabolizing CYPs, i.e. CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.