Effective sampling algorithms and analysis method for biomolecular simulations

Ayori Mitsutake

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Conventional simulations of complex systems, which have many degrees of freedom, are hampered by multiple-minima problem. One way to overcome the multiple-minima problem is to perform a simulation in a generalized ensemble where each state is weighted by an artificial, non-Boltzmann weight factor so that a random walk in potential energy space may be realized. Three of well-known generalized-ensemble algorithms are multicanonical, simulated-tempering, and replica exchange method. In previous works, the methods combined with simulated-tempering and replica-exchange method, the one-dimensional replica-exchange simulated-tempering and simulated-tempering replica-exchange method, were developed. For the former method, the weight factor of the one-dimensional simulated-tempering is determined by a short replica-exchange simulation and multiple histogram reweighting techniques. For the latter method, the production run is a replica-exchange simulation with a few replicas not in the canonical ensembles but in the simulated-tempering ensembles. In this article, the general formulation of the multidimensional replica-exchange simulated-tempering and simulated-tempering replica exchange method is reviewed.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Pages598-601
Number of pages4
Volume1518
DOIs
Publication statusPublished - 2013
Event4th International Symposium on Slow Dynamics in Complex Systems: Keep Going Tohoku - Sendai, Japan
Duration: 2012 Dec 22012 Dec 7

Other

Other4th International Symposium on Slow Dynamics in Complex Systems: Keep Going Tohoku
CountryJapan
CitySendai
Period12/12/212/12/7

Fingerprint

tempering
replicas
sampling
simulation
weight (mass)
complex systems
random walk
histograms
degrees of freedom
potential energy
formulations

Keywords

  • biomolecular
  • Generalized ensemble
  • simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Mitsutake, A. (2013). Effective sampling algorithms and analysis method for biomolecular simulations. In AIP Conference Proceedings (Vol. 1518, pp. 598-601) https://doi.org/10.1063/1.4794640

Effective sampling algorithms and analysis method for biomolecular simulations. / Mitsutake, Ayori.

AIP Conference Proceedings. Vol. 1518 2013. p. 598-601.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mitsutake, A 2013, Effective sampling algorithms and analysis method for biomolecular simulations. in AIP Conference Proceedings. vol. 1518, pp. 598-601, 4th International Symposium on Slow Dynamics in Complex Systems: Keep Going Tohoku, Sendai, Japan, 12/12/2. https://doi.org/10.1063/1.4794640
Mitsutake A. Effective sampling algorithms and analysis method for biomolecular simulations. In AIP Conference Proceedings. Vol. 1518. 2013. p. 598-601 https://doi.org/10.1063/1.4794640
Mitsutake, Ayori. / Effective sampling algorithms and analysis method for biomolecular simulations. AIP Conference Proceedings. Vol. 1518 2013. pp. 598-601
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