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Subtle Monte Carlo Updates in Dense Molecular Systems

Bottaro, Sandro; Boomsma, Wouter LU ; Johansson, Kristoffer E.; Andreetta, Christian; Hamelryck, Thomas and Ferkinghoff-Borg, Jesper (2012) In Journal of Chemical Theory and Computation 8(2). p.695-702
Abstract
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater... (More)
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions. (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
8
issue
2
pages
695 - 702
publisher
The American Chemical Society
external identifiers
  • wos:000300141600031
  • scopus:84857076206
ISSN
1549-9618
DOI
10.1021/ct200641m
language
English
LU publication?
yes
id
f2811ce8-bba3-408c-963d-4ac63cf3ee1b (old id 2406481)
date added to LUP
2012-03-28 12:43:49
date last changed
2017-06-11 03:15:09
@article{f2811ce8-bba3-408c-963d-4ac63cf3ee1b,
  abstract     = {Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.},
  author       = {Bottaro, Sandro and Boomsma, Wouter and Johansson, Kristoffer E. and Andreetta, Christian and Hamelryck, Thomas and Ferkinghoff-Borg, Jesper},
  issn         = {1549-9618},
  language     = {eng},
  number       = {2},
  pages        = {695--702},
  publisher    = {The American Chemical Society},
  series       = {Journal of Chemical Theory and Computation},
  title        = {Subtle Monte Carlo Updates in Dense Molecular Systems},
  url          = {http://dx.doi.org/10.1021/ct200641m},
  volume       = {8},
  year         = {2012},
}