Subtle Monte Carlo Updates in Dense Molecular Systems
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2406481
- author
- Bottaro, Sandro ; Boomsma, Wouter LU ; Johansson, Kristoffer E. ; Andreetta, Christian ; Hamelryck, Thomas and Ferkinghoff-Borg, Jesper
- organization
- publishing date
- 2012
- 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 (ACS)
- external identifiers
-
- wos:000300141600031
- scopus:84857076206
- pmid:26596617
- 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
- 2016-04-01 10:40:25
- date last changed
- 2024-01-06 22:18:16
@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 (ACS)}}, series = {{Journal of Chemical Theory and Computation}}, title = {{Subtle Monte Carlo Updates in Dense Molecular Systems}}, url = {{http://dx.doi.org/10.1021/ct200641m}}, doi = {{10.1021/ct200641m}}, volume = {{8}}, year = {{2012}}, }