Enhanced sampling algorithms

Ayori Mitsutake, Yoshiharu Mori, Yuko Okamoto

Research output: Chapter in Book/Report/Conference proceedingChapter


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
Number of pages43
Publication statusPublished - 2013

Publication series

NameMethods in Molecular Biology
ISSN (Print)10643745


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

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • General Medicine


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