Q-RepEx: A Python Pipeline to Increase the Sampling of Empirical Valence Bond Simulations

18 November 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation / umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate.


Enhanced Sampling
Empirical Valence Bond
Free Energy Perturbation
Replica Exchange Molecular Dynamics

Supplementary materials

Supporting Information
Supporting Information for: Q-RepEx: A Python Pipeline to Increase the Sampling of Empirical Valence Bond Simulations

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