Inferring a weighted elastic network from partial unfolding with coarse-grained simulations
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Undergraduate course
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Wiley-Blackwell
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Article
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Abstract
A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.
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Keywords
normal mode analysis, GNM, pfGNM, WCN, B-factor, vibrational dynamics
Language
English
Citation
Proteins-structure Function And Bioinformatics. Hoboken: Wiley-blackwell, v. 82, n. 1, p. 119-129, 2014.





