PyRETIS 2: An improbability drive for rare events

• Published in: Journal of computational chemistry Vol. 41; no. 4; pp. 370 - 377
• Main Authors: Riccardi, Enrico, Lervik, Anders, Roet, Sander, Aarøen, Ola, Erp, Titus S.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 05-02-2020; Wiley Subscription Services, Inc
• Subjects: Computational chemistry; kinetics; Molecular dynamics; Organic chemistry; path sampling; PyRETIS; python; rare event; Sampling methods; Software; python; path sampling; PyRETIS; rare event; kinetics
• ISSN: 0192-8651; 1096-987X
• DOI: 10.1002/jcc.26112

The algorithmic development in the field of path sampling has made tremendous progress in recent years. Although the original transition path sampling method was mostly used as a qualitative tool to sample reaction paths, the more recent family of interface‐based path sampling methods has paved the way for more quantitative rate calculation studies. Of the exact methods, the replica exchange transition interface sampling (RETIS) method is the most efficient, but rather difficult to implement. This has been the main motivation to develop the open‐source Python‐based computer library PyRETIS that was released in 2017. PyRETIS is designed to be easily interfaced with any molecular dynamics (MD) package using either classical or ab initio MD. In this study, we report on the principles and the software enhancements that are now included in PyRETIS 2, as well as the recent developments on the user interface, improvements of the efficiency via the implementation of new shooting moves, easier initialization procedures, analysis methods, and supported interfaced software. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
Transition path sampling techniques are a mix of Monte Carlo and molecular dynamics simulations which allow the investigation of rare events at molecular level, e.g. chemical reactions and structural/morphological transitions, in a reasonable computationaltime. Here, the authors present PyRETIS 2, the second edition of our Python library for performing advanced path sampling with common packages such as GROMACS, OPENMM, LAMMPS and CP2K. PyRETIS 2 contains algorithmic improvements and an extended user‐interface to furtherfacilitate the users in performing path sampling simulations and path data analysis.