posted on 2024-01-10, 22:05authored byYe Ding, Jing Huang
Zinc-containing proteins are vital for many 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 scheme that 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.
Trained on the difference between MM and QM atomic forces across diverse
zinc coordination groups, the DP/MM model faithfully reproduces structural
characteristics of zinc coordination during simulations, such as the
tetrahedral coordination of Cys4 and Cys3His1 groups.
Furthermore, DP/MM allows water exchange in the zinc coordination
environment. With its unique blend of accuracy, efficiency, flexibility,
and transferability, DP/MM serves as a valuable tool for studying
structures and dynamics of zinc-containing proteins and also represents
a pioneering approach in the evolving landscape of machine learning
potentials for molecular modeling.