Subtle Monte Carlo updates in dense molecular systems

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Subtle Monte Carlo updates in dense molecular systems. / Bottaro, Sandro; Boomsma, Wouter Krogh; Johansson, Kristoffer Enøe; Andreetta, Christian; Hamelryck, Thomas Wim; Ferkinghoff-Borg, Jesper.

In: Journal of Chemical Theory and Computation, Vol. 8, No. 2, 2012, p. 695-702.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Bottaro, S, Boomsma, WK, Johansson, KE, Andreetta, C, Hamelryck, TW & Ferkinghoff-Borg, J 2012, 'Subtle Monte Carlo updates in dense molecular systems', Journal of Chemical Theory and Computation, vol. 8, no. 2, pp. 695-702. https://doi.org/10.1021/ct200641m

APA

Bottaro, S., Boomsma, W. K., Johansson, K. E., Andreetta, C., Hamelryck, T. W., & Ferkinghoff-Borg, J. (2012). Subtle Monte Carlo updates in dense molecular systems. Journal of Chemical Theory and Computation, 8(2), 695-702. https://doi.org/10.1021/ct200641m

Vancouver

Bottaro S, Boomsma WK, Johansson KE, Andreetta C, Hamelryck TW, Ferkinghoff-Borg J. Subtle Monte Carlo updates in dense molecular systems. Journal of Chemical Theory and Computation. 2012;8(2):695-702. https://doi.org/10.1021/ct200641m

Author

Bottaro, Sandro ; Boomsma, Wouter Krogh ; Johansson, Kristoffer Enøe ; Andreetta, Christian ; Hamelryck, Thomas Wim ; Ferkinghoff-Borg, Jesper. / Subtle Monte Carlo updates in dense molecular systems. In: Journal of Chemical Theory and Computation. 2012 ; Vol. 8, No. 2. pp. 695-702.

Bibtex

@article{72151105f6dc4bb6ab61c9e6733d215f,
title = "Subtle Monte Carlo updates in dense molecular systems",
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 e¿ciency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classicchain-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 e¿ciency 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, o¿ering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.",
author = "Sandro Bottaro and Boomsma, {Wouter Krogh} and Johansson, {Kristoffer En{\o}e} and Christian Andreetta and Hamelryck, {Thomas Wim} and Jesper Ferkinghoff-Borg",
year = "2012",
doi = "10.1021/ct200641m",
language = "English",
volume = "8",
pages = "695--702",
journal = "Journal of Chemical Theory and Computation",
issn = "1549-9618",
publisher = "American Chemical Society",
number = "2",

}

RIS

TY - JOUR

T1 - Subtle Monte Carlo updates in dense molecular systems

AU - Bottaro, Sandro

AU - Boomsma, Wouter Krogh

AU - Johansson, Kristoffer Enøe

AU - Andreetta, Christian

AU - Hamelryck, Thomas Wim

AU - Ferkinghoff-Borg, Jesper

PY - 2012

Y1 - 2012

N2 - 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 e¿ciency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classicchain-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 e¿ciency 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, o¿ering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.

AB - 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 e¿ciency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classicchain-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 e¿ciency 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, o¿ering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.

U2 - 10.1021/ct200641m

DO - 10.1021/ct200641m

M3 - Journal article

VL - 8

SP - 695

EP - 702

JO - Journal of Chemical Theory and Computation

JF - Journal of Chemical Theory and Computation

SN - 1549-9618

IS - 2

ER -

ID: 37451517