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Allosteric Transitions of Supramolecular Systems Explored by Network Models: Application to Chaperonin GroEL

Yang, Z and Májek, P and Bahar, I (2009) Allosteric Transitions of Supramolecular Systems Explored by Network Models: Application to Chaperonin GroEL. PLoS Computational Biology, 5 (4). ISSN 1553-734X

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Abstract

Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM), for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s), most of which involve conserved residues.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Yang, Z
Májek, P
Bahar, Ibahar@pitt.eduBAHAR
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorPande, Vijay S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 1 April 2009
Date Type: Publication
Journal or Publication Title: PLoS Computational Biology
Volume: 5
Number: 4
DOI or Unique Handle: 10.1371/journal.pcbi.1000360
Schools and Programs: Dietrich School of Arts and Sciences > Astronomy
Dietrich School of Arts and Sciences > Physics
School of Medicine > Computational Biology
Refereed: Yes
ISSN: 1553-734X
PubMed Central ID: PMC2664929
PubMed ID: 19381265
Date Deposited: 25 Jul 2012 14:14
Last Modified: 02 Feb 2019 16:58
URI: http://d-scholarship.pitt.edu/id/eprint/13124

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