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Equilibrium distribution from distributed computing (simulations of protein folding)


Scalco, R; Caflisch, A (2011). Equilibrium distribution from distributed computing (simulations of protein folding). Journal of Physical Chemistry. B, 115(19):6358-6365.

Abstract

Multiple independent molecular dynamics (MD) simulations are often carried out starting from a single protein structure or a set of conformations that do not correspond to a thermodynamic ensemble. Therefore, a significant statistical bias is usually present in the Markov state model generated by simply combining the whole MD sampling into a network whose nodes and links are clusters of snapshots and transitions between them, respectively. Here, we introduce a depth-first search algorithm to extract from the whole conformation space network the largest ergodic component, i.e., the subset of nodes of the network whose transition matrix corresponds to an ergodic Markov chain. For multiple short MD simulations of a globular protein (as in distributed computing), the steady state, i.e., stationary distribution determined using the largest ergodic component, yields more accurate free energy profiles and mean first passage times than the original network or the ergodic network obtained by imposing detailed balance by means of symmetrization of the transition counts.

Multiple independent molecular dynamics (MD) simulations are often carried out starting from a single protein structure or a set of conformations that do not correspond to a thermodynamic ensemble. Therefore, a significant statistical bias is usually present in the Markov state model generated by simply combining the whole MD sampling into a network whose nodes and links are clusters of snapshots and transitions between them, respectively. Here, we introduce a depth-first search algorithm to extract from the whole conformation space network the largest ergodic component, i.e., the subset of nodes of the network whose transition matrix corresponds to an ergodic Markov chain. For multiple short MD simulations of a globular protein (as in distributed computing), the steady state, i.e., stationary distribution determined using the largest ergodic component, yields more accurate free energy profiles and mean first passage times than the original network or the ergodic network obtained by imposing detailed balance by means of symmetrization of the transition counts.

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10 citations in Web of Science®
10 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Department of Biochemistry
07 Faculty of Science > Department of Biochemistry
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2011
Deposited On:01 Jun 2011 14:02
Last Modified:05 Apr 2016 14:55
Publisher:American Chemical Society
ISSN:1520-5207
Publisher DOI:https://doi.org/10.1021/jp2014918
PubMed ID:21517045
Permanent URL: https://doi.org/10.5167/uzh-48204

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