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Structure prediction using sparse simulated NOE restraints with Rosetta in CASP 11
Author(s) -
Ovchinnikov Sergey,
Park Hahnbeom,
Kim David E.,
Liu Yuan,
Wang Ray YuRuei,
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.25006
Subject(s) - casp , pairing , folding (dsp implementation) , chemistry , algorithm , biological system , protein folding , protocol (science) , computer science , computational biology , protein structure , protein structure prediction , biophysics , physics , biochemistry , biology , engineering , superconductivity , quantum mechanics , electrical engineering , medicine , alternative medicine , pathology
In CASP11 we generated protein structure models using simulated ambiguous and unambiguous nuclear Overhauser effect (NOE) restraints with a two stage protocol. Low resolution models were generated guided by the unambiguous restraints using continuous chain folding for alpha and alpha‐beta proteins, and iterative annealing for all beta proteins to take advantage of the strand pairing information implicit in the restraints. The Rosetta fragment/model hybridization protocol was then used to recombine and regularize these models, and refine them in the Rosetta full atom energy function guided by both the unambiguous and the ambiguous restraints. Fifteen out of 19 targets were modeled with GDT‐TS quality scores greater than 60 for Model 1, significantly improving upon the non‐assisted predictions. Our results suggest that atomic level accuracy is achievable using sparse NOE data when there is at least one correctly assigned NOE for every residue. Proteins 2016; 84(Suppl 1):181–188. © 2016 Wiley Periodicals, Inc.