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Robust Estimation of Diffusion-Optimized Ensembles for Enhanced Sampling

Tian, Pengfei; Jonsson, Sigurdur LU ; Ferkinghoff-Borg, Jesper; Krivov, Sergi V.; Lindorff-Larsen, Kresten; Irbäck, Anders LU and Boomsma, Wouter (2014) In Journal of Chemical Theory and Computation 10(2). p.543-553
Abstract
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Chemical Theory and Computation
volume
10
issue
2
pages
543 - 553
publisher
The American Chemical Society
external identifiers
  • wos:000331342400007
  • scopus:84894149420
ISSN
1549-9618
DOI
10.1021/ct400844x
language
English
LU publication?
yes
id
8735235b-cb27-4ea7-b9c1-786365a43f79 (old id 4368401)
date added to LUP
2014-04-16 13:11:16
date last changed
2017-01-01 03:36:31
@article{8735235b-cb27-4ea7-b9c1-786365a43f79,
  abstract     = {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.},
  author       = {Tian, Pengfei and Jonsson, Sigurdur and Ferkinghoff-Borg, Jesper and Krivov, Sergi V. and Lindorff-Larsen, Kresten and Irbäck, Anders and Boomsma, Wouter},
  issn         = {1549-9618},
  language     = {eng},
  number       = {2},
  pages        = {543--553},
  publisher    = {The American Chemical Society},
  series       = {Journal of Chemical Theory and Computation},
  title        = {Robust Estimation of Diffusion-Optimized Ensembles for Enhanced Sampling},
  url          = {http://dx.doi.org/10.1021/ct400844x},
  volume       = {10},
  year         = {2014},
}