Yihan Shao

Accurate and Time-Efficient Condensed-Phase Free Energy Simulations with Reaction Specific Δ‑Machine Learning Potentials in CHARMM

An integrated workflow for MLP/ΔMLP-assisted QM/MM simulations that achieves ab initio (ai) or density functional theory (DFT)-level accuracy in predicting enzyme reaction thermodynamics and incorporates an iterative model refinement strategy that systematically improves predictive performance through successive rounds of sampling, high-level labeling, and retraining.