A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations

TL;DR

This paper introduces a novel method to incorporate experimental interconversion rate constants as constraints in molecular dynamics simulations, enabling more accurate modeling of kinetic processes and transition states.

Contribution

It presents a new approach combining maximum entropy and maximum caliber principles to include known rate constants in molecular dynamics, improving kinetic and free energy landscape predictions.

Findings

Successfully applied to peptide systems and protein folding.

Revealed shifts in transition states with different folding rates.

Enhanced understanding of reaction mechanisms and free energies.

Abstract

From the point of view of statistical mechanics, a full characterisation of a molecular system requires the experimental determination of its possible states, their populations and the respective interconversion rates. Well-established methods can incorporate in molecular dynamics simulations experimental information about states using structural restraints, and about populations using thermodynamic restraints. However, it is still unclear how to include experimental knowledge of interconversion rates. Here we introduce a method of imposing known rate constants as constraints in molecular dynamics simulations, which is based on a combination of the maximum entropy and maximum caliber principles. Starting from an existing ensemble of trajectories, obtained from either molecular dynamics or enhanced trajectory sampling, this method provides a minimally perturbed path distribution consistent with the kinetic constraints, as well as a modified free energy and committor landscape. We illustrate the application of the method to simple toy systems, as well as to all atom molecular simulations of peptide association and folding. We find that by combining experimental rate coefficient data and molecular dynamics simulations we are able to determine new transition states, reaction mechanisms and free energies. For instance, in the case of chignolin protein folding we find that imposing a slower folding rate shifts the transition state to more native like conformations, while it increases the stability of the unfolded region.