Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models. J Struct Funct Genomics 2011 Jul;12(2):137-47
Date
06/16/2011Pubmed ID
21674234Pubmed Central ID
PMC3227679DOI
10.1007/s10969-011-9113-3Scopus ID
2-s2.0-80054031361 (requires institutional sign-in at Scopus site) 14 CitationsAbstract
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.
Author List
Zimmermann MT, Leelananda SP, Gniewek P, Feng Y, Jernigan RL, Kloczkowski AAuthor
Michael T. Zimmermann PhD Director, Assistant Professor in the Clinical and Translational Science Institute department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AlgorithmsAmino Acids
Computer Simulation
Data Interpretation, Statistical
Entropy
Models, Molecular
Protein Conformation
Proteins
Thermodynamics
