Generalized-Ensemble Algorithms for Molecular Simulations of Biopolymers

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dc.creatorMitsutake, Ayori
dc.creatorSugita, Yuji
dc.creatorOkamoto, Yuko
dc.date2000-12-01
dc.date.accessioned2026-07-07T02:39:38Z
dc.date.available2026-07-07T02:39:38Z
dc.descriptionIn complex systems with many degrees of freedom such as peptides and proteins there exist a huge number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms. Three well-known methods, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present three new generalized-ensemble algorithms which combine the merits of the above methods. The effectiveness of the methods for molecular simulations in the protein folding problem is tested with short peptide systems.
dc.description45 pages, (LaTeX2e), 25 figures, Biopolymers (Peptide Science), submitted
dc.identifierhttps://arxiv.org/abs/cond-mat/0012021
dc.identifierhttp://arxiv.org/abs/cond-mat/0012021
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/17091
dc.subjectStatistical Mechanics
dc.subjectQuantitative Biology
dc.titleGeneralized-Ensemble Algorithms for Molecular Simulations of Biopolymers
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