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Photo Lynn Kamerlin

Lynn Kamerlin

Professor

Photo Lynn Kamerlin

Q-RepEx : A Python pipeline to increase the sampling of empirical valence bond simulations

Author

  • Sebastian Brickel
  • Andrey O Demkiv
  • Rory M Crean
  • Gaspar P Pinto
  • Shina Caroline Lynn Kamerlin

Summary, in English

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.

Publishing year

2023-03

Language

English

Publication/Series

Journal of Molecular Graphics and Modelling

Volume

119

Document type

Journal article

Publisher

Elsevier

Keywords

  • Molecular Dynamics Simulation
  • Molecular Conformation
  • Entropy

Status

Published

ISBN/ISSN/Other

  • ISSN: 1093-3263