PyRETIS 3: Conquering rare and slow events without boundaries

Wouter Vervust; Daniel T Zhang; An Ghysels; Sander Roet; Titus S van Erp; Enrico Riccardi

doi:10.1002/jcc.27319

PyRETIS 3: Conquering rare and slow events without boundaries

J Comput Chem. 2024 Jun 5;45(15):1224-1234. doi: 10.1002/jcc.27319. Epub 2024 Feb 12.

Authors

Wouter Vervust¹, Daniel T Zhang², An Ghysels¹, Sander Roet³, Titus S van Erp², Enrico Riccardi⁴

Affiliations

¹ IBiTech-BioMMedA Group, Ghent University, Ghent, Belgium.
² Department of Chemistry, Norwegian University of Science and Technology, Trondheim, Norway.
³ Department of Chemistry, Utrecht University, Utrecht, The Netherlands.
⁴ Department of Energy Resources, University of Stavanger, Stavanger, Norway.

PMID: 38345082
DOI: 10.1002/jcc.27319

Abstract

We present and discuss the advancements made in PyRETIS 3, the third instalment of our Python library for an efficient and user-friendly rare event simulation, focused to execute molecular simulations with replica exchange transition interface sampling (RETIS) and its variations. Apart from a general rewiring of the internal code towards a more modular structure, several recently developed sampling strategies have been implemented. These include recently developed Monte Carlo moves to increase path decorrelation and convergence rate, and new ensemble definitions to handle the challenges of long-lived metastable states and transitions with unbounded reactant and product states. Additionally, the post-analysis software PyVisa is now embedded in the main code, allowing fast use of machine-learning algorithms for clustering and visualising collective variables in the simulation data.

Keywords: PyRETIS; Python; kinetics; path sampling; rare event; slow event.