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Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home

Citation Das, Rhiju; Qian, Bin; Raman, Srivatsan; Vernon, Robert; Thompson, James; Bradley, Philip; Khare, Sagar; Tyka, Michael; Bhat, Divya; Chivian, Dylan; Kim, David; Sheffler, William; Malmstrom, Lars; Wollacott, Andrew; Wang, Chu; Andre, Ingemar; Baker, David; Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home. Proteins (2007), 1: 118-128.
Abstract We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions. (c) 2007 Wiley-Liss, Inc.
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