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Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models
Authors:Michael T Zimmermann  Sumudu P Leelananda  Pawel Gniewek  Yaping Feng  Robert L Jernigan  " target="_blank">Andrzej Kloczkowski
Institution:(1) Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, IA 50011-0320, USA;(2) L.H.Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011-3020, USA;(3) Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, IA 50011, USA;(4) Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland;(5) Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA;(6) Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH 43205, USA;
Abstract:We propose a novel method of calculation of free energy for coarse grained models of proteins by combining our newly developed multibody potentials with entropies computed from elastic network models of proteins. Multi-body potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Combining four-body non-sequential, four-body sequential and pairwise short range potentials with optimized weights for each term, our coarse-grained potential improved recognition of native structure among misfolded decoys, outperforming all other contact potentials for CASP8 decoy sets and performance comparable to the fully atomic empirical DFIRE potentials. By combing statistical contact potentials with entropies from elastic network models of the same structures we can compute free energy changes and improve coarse-grained modeling of protein structure and dynamics. The consideration of protein flexibility and dynamics should improve protein structure prediction and refinement of computational models. This work is the first to combine coarse-grained multibody potentials with an entropic model that takes into account contributions of the entire structure, investigating native-like decoy selection.
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