Abstract
The low-quality structure refinement is one of important challenges in protein structure prediction. Many studies have been conducted for protein structure refinement; especially refinement of structure derived from NMR spectroscopy is accelerated. In this study, we demonstrate that statistical torsion angle potential (STAP) can drive to refine NMR structures without NOE data. Because NOE data have an ambiguity and uncertainty, we used flat-bottom potential instead of NOE data. The materials of flat-bottom potential are distance and dihedral angle derived from given structures. Instead of the NOE restraints, they prevent a structural dislocation during the refinement process. A simulated annealing protocol was used to optimize energy of structures. The protocol was tested on 134 NMR structures in Protein Data Bank (PDB) that are coexisting in X-ray structures. Among them, 50 structures of training set used to find the optimal “width” parameter in the flat-bottom potential functions. Validations of the “width” for 84 structures, most of 12 quality assessment scores of refined structure are significantly improved.
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