Inferring a weighted elastic network from partial unfolding with coarse-grained simulations

被引:10
作者
de Mendonca, Matheus R. [1 ]
Rizzi, Leandro G. [1 ]
Contessoto, Vinicius [2 ]
Leite, Vitor B. P. [2 ]
Alves, Nelson A. [1 ]
机构
[1] Univ Sao Paulo, FFCLRP, Dept Fis, BR-14040901 Ribeirao Preto, SP, Brazil
[2] Univ Estadual Paulista, IBILCE, Dept Fis, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil
关键词
normal mode analysis; GNM; pfGNM; WCN; B-factor; vibrational dynamics; SINGLE-PARAMETER; PROTEINS; DYNAMICS; UBIQUITIN; MODELS; FLUCTUATIONS; CONTACTS; AZURIN;
D O I
10.1002/prot.24381
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:119 / 129
页数:11
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