Enhanced sampling algorithms

Ayori Mitsutake, Yoshiharu Mori, Yuko Okamoto

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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 wellknown 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.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
Pages153-195
Number of pages43
Volume924
DOIs
Publication statusPublished - 2013

Publication series

NameMethods in Molecular Biology
Volume924
ISSN (Print)10643745

Keywords

  • Generalized-ensemble algorithm
  • Molecular dynamics
  • Monte Carlo
  • Multicanonical algorithm
  • Replica-exchange method
  • Simulated tempering

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Medicine(all)

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  • Cite this

    Mitsutake, A., Mori, Y., & Okamoto, Y. (2013). Enhanced sampling algorithms. In Methods in Molecular Biology (Vol. 924, pp. 153-195). (Methods in Molecular Biology; Vol. 924). https://doi.org/10.1007/978-1-62703-017-5-7