DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Abstract

Zinc-containing proteins are essential to a variety of biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field model that combines ab initio accuracy with MM-level efficiency for modeling zinc-protein interactions. The DP/MM scheme utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. The model is trained on the difference in atomic forces between MM and QM calculations across diverse zinc coordination groups. Simulations on a variety of zinccontaining proteins demonstrate that DP/MM faithfully reproduces their coordination geometry and structural characteristics, for example, the tetrahedral coordination structures for the Cys4 and the Cys3His1 groups. Furthermore, DP/MM is capable of handling exchangeable water molecules in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM not only serves as a valuable tool for studying zinc-containing proteins but also represents a pioneering approach that augments the growing landscape of machine learning potentials in molecular modeling.