Interaction of divalent cations and amino acids in bulk water: Molecular simulations with neural network potentials

Abstract

Understanding the interaction mechanism between divalent metal ions with amino acids is of great significance to understand the interaction between metal ions with proteins. In this study, the interaction mechanisms of Mg2+, Ca2+, and Zn2+ with amino acid side chain analogs in water were systematically studied by combining neural network potential energy surface, molecular dynamics simulation and umbrella sampling. The calculated potential mean forces not only reveal the binding process of each ion and amino acid, the most stable coordination structure, but also show the difference between different ions. In addition, we also use the neural network based potential of mean force as a standard to benchmark classical force fields, which is also meaningful for the development of force fields targeting metal ions.