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Sampling of near‐native protein conformations during protein structure refinement using a coarse‐grained model, normal modes, and molecular dynamics simulations
Author(s) -
StumpffKane Andrew W.,
Maksimiak Katarzyna,
Lee Michael S.,
Feig Michael
Publication year - 2008
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.21674
Subject(s) - sampling (signal processing) , computer science , context (archaeology) , molecular dynamics , protocol (science) , protein structure , biological system , protein structure prediction , algorithm , statistical physics , computational chemistry , physics , chemistry , biology , filter (signal processing) , pathology , computer vision , medicine , paleontology , alternative medicine , nuclear magnetic resonance
Protein structure refinement from comparative models with the goal of predicting structures at near‐experimental accuracy remains an unsolved problem. Structure refinement might be achieved with an iterative protocol where the most native‐like structure from a set of decoys generated from an initial model in one cycle is used as the starting structure for the next cycle. Conformational sampling based on the coarse‐grained SICHO model, atomic level of detail molecular dynamics simulations, and normal‐mode analysis is compared in the context of such a protocol. All of the sampling methods can achieve significant refinement close to experimental structures, although the distribution of structures and the ability to reach native‐like structures differs greatly. Implications for the practical application of such sampling methods and the requirements for scoring functions in an iterative refinement protocol are analyzed in the context of theoretical predictions for the distribution of protein‐like conformations with a random sampling protocol. Proteins 2008. © 2007 Wiley‐Liss, Inc.