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Protein structure determination by conformational space annealing using NMR geometric restraints
Author(s) -
Joo Keehyoung,
Joung InSuk,
Lee Jinhyuk,
Lee Jinwoo,
Lee Weontae,
Brooks Bernard,
Lee Sung Jong,
Lee Jooyoung
Publication year - 2015
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.24941
Subject(s) - protein data bank (rcsb pdb) , ramachandran plot , simulated annealing , protein structure , energy minimization , crystallography , protein data bank , chemistry , computer science , biological system , algorithm , computational chemistry , stereochemistry , biochemistry , biology
ABSTRACT We have carried out numerical experiments to investigate the applicability of the global optimization method of conformational space annealing (CSA) to the enhanced NMR protein structure determination over existing PDB structures. The NMR protein structure determination is driven by the optimization of collective multiple restraints arising from experimental data and the basic stereochemical properties of a protein‐like molecule. By rigorous and straightforward application of CSA to the identical NMR experimental data used to generate existing PDB structures, we redetermined 56 recent PDB protein structures starting from fully randomized structures. The quality of CSA‐generated structures and existing PDB structures were assessed by multiobjective functions in terms of their consistencies with experimental data and the requirements of protein‐like stereochemistry. In 54 out of 56 cases, CSA‐generated structures were better than existing PDB structures in the Pareto‐dominant manner, while in the remaining two cases, it was a tie with mixed results. As a whole, all structural features tested improved in a statistically meaningful manner. The most improved feature was the Ramachandran favored portion of backbone torsion angles with about 8.6% improvement from 88.9% to 97.5% ( P ‐value <10 −17 ). We show that by straightforward application of CSA to the efficient global optimization of an energy function, NMR structures will be of better quality than existing PDB structures. Proteins 2015; 83:2251–2262. © 2015 Wiley Periodicals, Inc.