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Analyzing the effect of homogeneous frustration in protein folding
Authors:Ronaldo J Oliveira  Aline T Bruni  Jorge Chahine  Vitor B P Leite
Institution:1. Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista, Sao José do Rio Preto, , S?o Paulo, 15054‐000 Brazil;2. Laboratório Nacional de Ciência e Tecnologia do Bioetanol, Campinas, , S?o Paulo, 13083‐970 Brazil;3. Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeir?o Preto, Universidade de S?o Paulo, , S?o Paulo, Brazil
Abstract:The energy landscape theory has been an invaluable theoretical framework in the understanding of biological processes such as protein folding, oligomerization, and functional transitions. According to the theory, the energy landscape of protein folding is funneled toward the native state, a conformational state that is consistent with the principle of minimal frustration. It has been accepted that real proteins are selected through natural evolution, satisfying the minimum frustration criterion. However, there is evidence that a low degree of frustration accelerates folding. We examined the interplay between topological and energetic protein frustration. We employed a Cα structure‐based model for simulations with a controlled nonspecific energetic frustration added to the potential energy function. Thermodynamics and kinetics of a group of 19 proteins are completely characterized as a function of increasing level of energetic frustration. We observed two well‐separated groups of proteins: one group where a little frustration enhances folding rates to an optimal value and another where any energetic frustration slows down folding. Protein energetic frustration regimes and their mechanisms are explained by the role of non‐native contact interactions in different folding scenarios. These findings strongly correlate with the protein free‐energy folding barrier and the absolute contact order parameters. These computational results are corroborated by principal component analysis and partial least square techniques. One simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins.Proteins 2013; 81:1727–1737. © 2013 Wiley Periodicals, Inc.
Keywords:structure‐based model  multivariate analysis  molecular dynamics  C‐alpha model
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