Generalized-Ensemble Algorithms for Protein Folding Simulations

  • Yuji Sugita
  • Ayori Mitsutake
  • Yuko Okamoto
Chapter
Part of the Lecture Notes in Physics book series (LNP, volume 736)

Abstract

Conventional simulations of complex systems in the canonical ensemble suffer from the quasi-ergodicity problem. A simulation in generalized ensemble overcomes this difficulty by performing a random walk in potential energy space and other parameter space. 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 the generalized-ensemble algorithms. 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 further extensions of the above three methods.

Keywords

Random Walk Simulated Tempering Weight Factor Monte Carlo Replica Exchange 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yuji Sugita
    • 1
  • Ayori Mitsutake
    • 2
  • Yuko Okamoto
    • 3
  1. 1.Theoretical Biochemistry LaboratoryDiscovery Research Institute RIKENWako-shiJapan
  2. 2.Department of PhysicsKeio UniversityYokohamaJapan
  3. 3.Department of PhysicsNagoya UniversityNagoyaJapan

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