Document Detail

Coarse Grained Normal Mode Analysis vs. Refined Gaussian Network Model for Protein Residue-Level Structural Fluctuations.
MedLine Citation:
PMID:  23296997     Owner:  NLM     Status:  Publisher    
We investigate several approaches to coarse grained normal mode analysis on protein residual-level structural fluctuations by choosing different ways of representing the residues and the forces among them. Single-atom representations using the backbone atoms C( α ), C, N, and C( β ) are considered. Combinations of some of these atoms are also tested. The force constants between the representative atoms are extracted from the Hessian matrix of the energy function and served as the force constants between the corresponding residues. The residue mean-square-fluctuations and their correlations with the experimental B-factors are calculated for a large set of proteins. The results are compared with all-atom normal mode analysis and the residue-level Gaussian Network Model. The coarse-grained methods perform more efficiently than all-atom normal mode analysis, while their B-factor correlations are also higher. Their B-factor correlations are comparable with those estimated by the Gaussian Network Model and in many cases better. The extracted force constants are surveyed for different pairs of residues with different numbers of separation residues in sequence. The statistical averages are used to build a refined Gaussian Network Model, which is able to predict residue-level structural fluctuations significantly better than the conventional Gaussian Network Model in many test cases.
Jun-Koo Park; Robert Jernigan; Zhijun Wu
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-8
Journal Detail:
Title:  Bulletin of mathematical biology     Volume:  -     ISSN:  1522-9602     ISO Abbreviation:  Bull. Math. Biol.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401404     Medline TA:  Bull Math Biol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Department of Mathematics, Iowa State University, Ames, IA, 50010, USA,
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