Markov State Model Reveals Folding and Functional Dynamics in Ultra-Long MD Trajectories.
Two strategies have been recently employed to push molecular simulation to long, biologically relevant time scales: projection-based analysis of results from specialized hardware producing a small number of ultralong trajectories and the statistical interpretation of massive parallel sampling perfor...
| Publicado en: | Journal of the American Chemical Society Vol. 133; no. 45; pp. 18413 - 18420 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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American Chemical Society
11/16/2011
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=67615592&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 67615592 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00027863 ACS jtl: Journal of the American Chemical Society issn: 00027863 maglogo: N pubinfo: dt: 11/16/2011 vid: 133 iid: 45 pid: 997 pub: American Chemical Society artinfo: ui: 67615592 10.1021/ja207470h ppf: 18413 ppct: 7 formats: tig: atl: Markov State Model Reveals Folding and Functional Dynamics in Ultra-Long MD Trajectories. aug: au: Lane, Thomas J. Bowman, Gregory R. Beauchamp, Kyle Voelz, Vincent A. Pande, Vijay S. affil: Department of Chemistry, Stanford University, Stanford, California 94305, United States Biophysics Program, Stanford University, Stanford, California 94305, United States Department of Chemistry, Temple University, Philadelphia, Pennsylvania, 19121, United States su: Molecular dynamics Markov processes Sampling (Process) Eigenvectors Eigenvalues Nuclear magnetic resonance sug: subj: Molecular dynamics Markov processes Sampling (Process) Eigenvectors Eigenvalues Nuclear magnetic resonance ab: Two strategies have been recently employed to push molecular simulation to long, biologically relevant time scales: projection-based analysis of results from specialized hardware producing a small number of ultralong trajectories and the statistical interpretation of massive parallel sampling performed with Markov state models (MSMs). Here, we assess the MSM as an analysis method by constructing a Markov model from ultralong trajectories, specifically two previously reported 100 µs trajectories of the FiP35 WW domain (Shaw, D. E. Science 2010, 330, 341-346). We find that the MSM approach yields novel insights. It discovers new statistically significant folding pathways, in which either beta-hairpin of the WW domain can form first. The rates of this process approach experimental values in a direct quantitative comparison (time scales of 5.0 µs and 100 ns), within a factor of ~2. Finally, the hub-like topology of the MSM and identification of a holo conformation predicts how WW domains may function through a conformational selection mechanism. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2011 holdings: @attributes: islocal: N |
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