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CASP 11 refinement experiments with ROSETTA
Author(s) -
Park Hahnbeom,
DiMaio Frank,
Baker David
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.24862
Subject(s) - casp , computer science , selection (genetic algorithm) , computation , resolution (logic) , scale (ratio) , fragment (logic) , protocol (science) , protein structure prediction , algorithm , artificial intelligence , protein structure , medicine , alternative medicine , nuclear magnetic resonance , pathology , physics , quantum mechanics
ABSTRACT We report new Rosetta‐based approaches to tackling the major issues that confound protein structure refinement, and the testing of these approaches in the CASP11 experiment. Automated refinement protocols were developed that integrate a range of sampling methods using parallel computation and multiobjective optimization. In CASP11, we used a more aggressive large‐scale structure rebuilding approach for poor starting models, and a less aggressive local rebuilding plus core refinement approach for starting models likely to be closer to the native structure. The more incorrectly modeled a structure was predicted to be, the more it was allowed to vary during refinement. The CASP11 experiment revealed strengths and weaknesses of the approaches: the high‐resolution strategy incorporating local rebuilding with core refinement consistently improved starting structures, while the low‐resolution strategy incorporating the reconstruction of large parts of the structures improved starting models in some cases but often considerably worsened them, largely because of model selection issues. Overall, the results suggest the high‐resolution refinement protocol is a promising method orthogonal to other approaches, while the low‐resolution refinement method clearly requires further development. Proteins 2016; 84(Suppl 1):314–322. © 2015 Wiley Periodicals, Inc.