Literature DB >> 22228562

The effects of rigid motions on elastic network model force constants.

Timothy R Lezon1.   

Abstract

Elastic network models provide an efficient way to quickly calculate protein global dynamics from experimentally determined structures. The model's single parameter, its force constant, determines the physical extent of equilibrium fluctuations. The values of force constants can be calculated by fitting to experimental data, but the results depend on the type of experimental data used. Here, we investigate the differences between calculated values of force constants and data from NMR and X-ray structures. We find that X-ray B factors carry the signature of rigid-body motions, to the extent that B factors can be almost entirely accounted for by rigid motions alone. When fitting to more refined anisotropic temperature factors, the contributions of rigid motions are significantly reduced, indicating that the large contribution of rigid motions to B factors is a result of over-fitting. No correlation is found between force constants fit to NMR data and those fit to X-ray data, possibly due to the inability of NMR data to accurately capture protein dynamics.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22228562      PMCID: PMC3294121          DOI: 10.1002/prot.24014

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  44 in total

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Journal:  Annu Rev Biophys Biomol Struct       Date:  2006

4.  Simulation of the coupling between nucleotide binding and transmembrane domains in the ATP binding cassette transporter BtuCD.

Authors:  Jacob Sonne; Christian Kandt; Günther H Peters; Flemming Y Hansen; Morten Ø Jensen; D Peter Tieleman
Journal:  Biophys J       Date:  2007-01-05       Impact factor: 4.033

5.  vGNM: a better model for understanding the dynamics of proteins in crystals.

Authors:  Guang Song; Robert L Jernigan
Journal:  J Mol Biol       Date:  2007-03-28       Impact factor: 5.469

6.  Anisotropic fluctuations of amino acids in protein structures: insights from X-ray crystallography and elastic network models.

Authors:  Eran Eyal; Chakra Chennubhotla; Lee-Wei Yang; Ivet Bahar
Journal:  Bioinformatics       Date:  2007-07-01       Impact factor: 6.937

7.  Coarse-grained biomolecular simulation with REACH: realistic extension algorithm via covariance Hessian.

Authors:  Kei Moritsugu; Jeremy C Smith
Journal:  Biophys J       Date:  2007-08-10       Impact factor: 4.033

8.  Coarse-grained free energy functions for studying protein conformational changes: a double-well network model.

Authors:  Jhih-Wei Chu; Gregory A Voth
Journal:  Biophys J       Date:  2007-08-17       Impact factor: 4.033

9.  Insights into equilibrium dynamics of proteins from comparison of NMR and X-ray data with computational predictions.

Authors:  Lee-Wei Yang; Eran Eyal; Chakra Chennubhotla; JunGoo Jee; Angela M Gronenborn; Ivet Bahar
Journal:  Structure       Date:  2007-06       Impact factor: 5.006

10.  The MUMO (minimal under-restraining minimal over-restraining) method for the determination of native state ensembles of proteins.

Authors:  Barbara Richter; Joerg Gsponer; Péter Várnai; Xavier Salvatella; Michele Vendruscolo
Journal:  J Biomol NMR       Date:  2007-01-16       Impact factor: 2.835

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