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Anders Irbäck. Photo.

Anders Irbäck

Professor

Anders Irbäck. Photo.

Robust Estimation of Diffusion-Optimized Ensembles for Enhanced Sampling

Author

  • Pengfei Tian
  • Sigurdur Jonsson
  • Jesper Ferkinghoff-Borg
  • Sergi V. Krivov
  • Kresten Lindorff-Larsen
  • Anders Irbäck
  • Wouter Boomsma

Summary, in English

The multicanonical, or flat-histogram, method is a common technique to improve the sampling efficiency of molecular simulations. The idea is that free-energy barriers in a simulation can be removed by simulating from a distribution where all values of a reaction coordinate are equally likely, and subsequently reweight the obtained statistics to recover the Boltzmann distribution at the temperature of interest. While this method has been successful in practice, the choice of a flat distribution is not necessarily optimal. Recently, it was proposed that additional performance gains could be obtained by taking the position-dependent diffusion coefficient into account, thus placing greater emphasis on regions diffusing slowly. Although some promising examples of applications of this approach exist, the practical usefulness of the method has been hindered by the difficulty in obtaining sufficiently accurate estimates of the diffusion coefficient. Here, we present a simple, yet robust solution to this problem. Compared to current state-of-the-art procedures, the new estimation method requires an order of magnitude fewer data to obtain reliable estimates, thus broadening the potential scope in which this technique can be applied in practice.

Department/s

  • Computational Biology and Biological Physics

Publishing year

2014

Language

English

Pages

543-553

Publication/Series

Journal of Chemical Theory and Computation

Volume

10

Issue

2

Document type

Journal article

Publisher

The American Chemical Society (ACS)

Topic

  • Other Physics Topics
  • Biophysics

Status

Published

ISBN/ISSN/Other

  • ISSN: 1549-9618