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  Effective Harmonic Potentials: Insights into the Internal Cooperativity and Sequence-Specificity of Protein Dynamics

Dehouck, Y., & Mikhailov, A. S. (2013). Effective Harmonic Potentials: Insights into the Internal Cooperativity and Sequence-Specificity of Protein Dynamics. PLoS Computational Biology, 9(8): 1003209. doi:10.1371/journal.pcbi.1003209.

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1304.1385v1.pdf (Preprint), 2MB
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arXiv:1304.1385v1 [q-bio.BM] 4 Apr 2013
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 Urheber:
Dehouck, Yves1, 2, Autor           
Mikhailov, Alexander S.1, Autor           
Affiliations:
1Physical Chemistry, Fritz Haber Institute, Max Planck Society, ou_634546              
2Department of BioModelling, BioInformatics and BioProcesses, Université Libre de Bruxelles (ULB), Brussels, Belgium, ou_persistent22              

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 Zusammenfassung: The proper biological functioning of proteins often relies on the occurrence of coordinated fluctuations around their native structure, or on their ability to perform wider and sometimes highly elaborated motions. Hence, there is considerable interest in the definition of accurate coarse-grained descriptions of protein dynamics, as an alternative to more computationally expensive approaches. In particular, the elastic network model, in which residue motions are subjected to pairwise harmonic potentials, is known to capture essential aspects of conformational dynamics in proteins, but has so far remained mostly phenomenological, and unable to account for the chemical specificities of amino acids. We propose, for the first time, a method to derive residue- and distance-specific effective harmonic potentials from the statistical analysis of an extensive dataset of NMR conformational ensembles. These potentials constitute dynamical counterparts to the mean-force statistical potentials commonly used for static analyses of protein structures. In the context of the elastic network model, they yield a strongly improved description of the cooperative aspects of residue motions, and give the opportunity to systematically explore the influence of sequence details on protein dynamics.

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Sprache(n): eng - English
 Datum: 2013-05-082013-07-192013
 Publikationsstatus: Online veröffentlicht
 Seiten: 12
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1371/journal.pcbi.1003209
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Titel: PLoS Computational Biology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : PLoS
Seiten: - Band / Heft: 9 (8) Artikelnummer: 1003209 Start- / Endseite: - Identifikator: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1