Despite significant advancement of computational methods in protein structure prediction during the last decade, these techniques often cannot achieve allowable prediction accuracy to be applied in solving biological problems. Bringing these low-resolution predicted models to high-resolution structures close to their native state, called the protein structure refinement problem, however, has proven to be extremely challenging and a largely unsolved problem in the field of protein structure prediction. Here, we propose a new approach to protein structure refinement by iterative fragment exchange, called REFINEpro. The protocol first identifies the less conserved local regions in the initial model by consensus approach using ensemble of models produced for the same protein target. We call these regions problematic regions (PRs). The qualities of the PRs are then iteratively improved by exchanging better-modeled fragments corresponding to these PRs from structures in the ensemble. This method has been tested on benchmark datasets comprising of decoys generated through both template-based and ab-initio protein structure prediction methods and exhibits promising improvement over the initial models in both global and local model quality measures, indicating a new avenue to solve the protein structure refinement problem. REFINEpro web server is freely available at http://sysbio.rnet.missouri.edu/REFINEpro/.
['Debswapna Bhattacharya', 'Jianlin Cheng']
Protein Structure Refinement by Iterative Fragment Exchange