Inferring a weighted elastic network from partial unfolding with coarse-grained simulations
Matheus R de Mendonça1, Leandro G Rizzi, Vinicius Contessoto
1Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, 14040-901, SP, Brazil.
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 Cα coordinates, and they only take the pairs of Cα atoms within a given cutoff distance rc 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 Cα 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.
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