gen.parRep: a first implementation of the Generalized Parallel Replica dynamics for the long time simulation of metastable biochemical systems

TL;DR

This paper introduces gen.parRep, the first publicly available implementation of the Generalized Parallel Replica method, enabling efficient long-time simulations of metastable biochemical systems with high scalability on multiple CPUs.

Contribution

It provides the first implementation of the Generalized ParRep method tailored for biochemical systems, demonstrating its scalability and applicability.

Findings

Achieves up to 70% of maximum speedup on hundreds of CPUs.

Successfully applied to conformational equilibria and protein-ligand dissociation.

Demonstrates linear scalability of the implementation.

Abstract

Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge. The "Parallel Replica" (ParRep) dynamics is known for allowing to simulate very long trajectories of metastable Langevin dynamics in the materials science community, but it relies on assumptions that can hardly be transposed to the world of biochemical simulations. The later developed "Generalized ParRep" variant solves those issues, but it was not applied to significant systems of interest so far. In this article, we present the program gen.parRep, the first publicly available implementation of the Generalized Parallel Replica method (BSD 3-Clause license), targeting frequently encountered metastable biochemical systems, such as conformational equilibria or dissociation of protein-ligand complexes. It will be shown that the resulting C++ implementation exhibits a strong linear scalability, providing up to 70 % of the maximum possible speedup on several hundreds of CPUs.