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Effective protein model structure refinement by loop modeling and overall relaxation
Author(s) -
Lee Gyu Rie,
Heo Lim,
Seok Chaok
Publication year - 2016
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.24858
Subject(s) - template , loop modeling , computer science , relaxation (psychology) , protein structure prediction , loop (graph theory) , casp , ab initio , protein structure , quality (philosophy) , algorithm , biological system , mathematics , physics , biology , nuclear magnetic resonance , combinatorics , quantum mechanics , neuroscience , programming language
Protein structures predicted by state‐of‐the‐art template‐based methods may still have errors when the template proteins are not similar enough to the target protein. Overall target structure may deviate from the template structures owing to differences in sequences. Structural information for some local regions such as loops may not be available when there are sequence insertions or deletions. Those structural aspects that originate from deviations from templates can be dealt with by ab initio structure refinement methods to further improve model accuracy. In the CASP11 refinement experiment, we tested three different refinement methods that utilize overall structure relaxation, loop modeling, and quality assessment of multiple initial structures. From this experiment, we conclude that the overall relaxation method can consistently improve model quality. Loop modeling is the most useful when the initial model structure is high quality, with GDT‐HA >60. The method that used multiple initial structures further refined the already refined models; the minor improvements with this method raise the issue of problem with the current energy function. Future research directions are also discussed. Proteins 2016; 84(Suppl 1):293–301. © 2015 Wiley Periodicals, Inc.