Sequence Model-Based Prediction and QM/MM Assessment of CYP2C19 Variant Effects on Mephenytoin Oxidation

Cytochrome P450 2C19 (CYP2C19) genetic variation contributes to interindividual differences in drug metabolism, yet relating sequence-level variation to substrate-specific catalytic mechanisms remains challenging. Here, we combine a generative sequence model based on the maximum entropy (MaxEnt) framework for mutation scoring, published biochemical activity data, molecular dynamics (MD) simulations, and quantum mechanics/molecular mechanics adaptive steered molecular dynamics (QM/MM ASMD) calculations to examine CYP2C19 variant effects on S-mephenytoin oxidation. In the primary correlation analysis, MaxEnt scores showed nonsignificant negative rank trends with Vmax and CLint, whereas Km showed no corresponding rank association. CYP2C19*1A (WT) was used as the reference system, and CYP2C19*23 and CYP2C19*26 were selected as contrasting variants for atomistic analysis. MD simulations revealed variant-dependent changes in conformational sampling, correlated motions, and substrate positioning, but the population of geometries satisfying a predefined reactive distance-angle criterion did not reproduce the experimental activity trend. At the production pulling rate, the Seed 1 QM/MM-ASMD profiles showed a lower C12 oxygen-addition barrier for CYP2C19*23 and a higher barrier for CYP2C19*26 relative to CYP2C19*1A. Additional CYP2C19*1A and CYP2C19*23 starting configurations yielded a lower three-seed mean barrier for CYP2C19*23 at that pulling rate, although the barrier ranges overlapped and starting-configuration dependence was appreciable, and a slower-pulling control showed substantial rate sensitivity. The sampled NIH-shift profiles exhibited apparent low barriers in all three systems; however, substantial discrepancies between partition-level nonequilibrium-work estimators precluded establishing quantitatively converged CV2 barrier magnitudes. Thus, the calculations support qualitative differences among the sampled reaction profiles but do not quantitatively reproduce the magnitude of the experimental kinetic differences. The combined sequence, MD, and QM/MM workflow provides a framework for prioritizing variants and developing substrate-specific mechanistic hypotheses while making the sampling limitations explicit.