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Replica state exchange metadynamics for improving the convergence of free energy estimates
Author(s) -
Galvelis Raimondas,
Sugita Yuji
Publication year - 2015
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.23945
Subject(s) - metadynamics , replica , convergence (economics) , statistical physics , state (computer science) , energy (signal processing) , energy exchange , energy landscape , computational chemistry , mathematics , chemistry , thermodynamics , physics , molecular dynamics , algorithm , statistics , economics , atmospheric sciences , art , economic growth , visual arts
Metadynamics (MTD) is a powerful enhanced sampling method for systems with rugged energy landscapes. It constructs a bias potential in a predefined collective variable (CV) space to overcome barriers between metastable states. In bias‐exchange MTD (BE‐MTD), multiple replicas approximate the CV space by exchanging bias potentials (replica conditions) with the Metropolis–Hastings (MH) algorithm. We demonstrate that the replica‐exchange rates and the convergence of free energy estimates of BE‐MTD are improved by introducing the infinite swapping (IS) or the Suwa‐Todo (ST) algorithms. Conceptually, IS and ST perform transitions in a replica state space rather than exchanges in a replica condition space. To emphasize this, the proposed scheme is called the replica state exchange MTD (RSE‐MTD). Benchmarks were performed with alanine polypeptides in vacuum and water. For the systems tested in this work, there is no significant performance difference between IS and ST. © 2015 Wiley Periodicals, Inc.