| Enhanced sampling algorithms. | |
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MedLine Citation:
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PMID: 23034749 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large 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. Enhanced conformational sampling techniques are thus in great demand. 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 in biomolecular systems. Three well-known methods, namely, 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 various extensions of these three generalized-ensemble algorithms. The effectiveness of the methods is tested with short peptide and protein systems. |
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Authors:
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Ayori Mitsutake; Yoshiharu Mori; Yuko Okamoto |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Methods in molecular biology (Clifton, N.J.) Volume: 924 ISSN: 1940-6029 ISO Abbreviation: Methods Mol. Biol. Publication Date: 2013 |
Date Detail:
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Created Date: 2012-10-04 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9214969 Medline TA: Methods Mol Biol Country: United States |
Other Details:
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Languages: eng Pagination: 153-95 Citation Subset: IM |
Affiliation:
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Department of Physics, Keio University, Yokohama, Kanagawa, Japan. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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