Multi-Overlap Simulations for Transitions between Reference Configurations

TL;DR

This paper presents a novel simulation method that constructs weight factors to facilitate transitions between reference configurations by flattening overlap probability densities, enabling detailed free energy landscape analysis.

Contribution

The authors introduce a new procedure for constructing weight factors to overcome free energy barriers in overlap variables, extending to transitions between two reference states.

Findings

Successfully simulated transitions in Met-enkephalin between two energy minima.

Identified transition states and estimated free energy barriers.

Provided free energy profiles as functions of dihedral and RMS distances.

Abstract

We introduce a new procedure to construct weight factors, which flatten the probability density of the overlap with respect to some pre-defined reference configuration. This allows one to overcome free energy barriers in the overlap variable. Subsequently, we generalize the approach to deal with the overlaps with respect to two reference configurations so that transitions between them are induced. We illustrate our approach by simulations of the brainpeptide Met-enkephalin with the ECEPP/2 energy function using the global-energy-minimum and the second lowest-energy states as reference configurations. The free energy is obtained as functions of the dihedral and the root-mean-square distances from these two configurations. The latter allows one to identify the transition state and to estimate its associated free energy barrier.