Lars Malmstroem, Ph.D.

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

Citation	Das, R., Qian, B., Raman, S., Vernon, R., Thompson, J., Bradley, P., Khare, S., Tyka, MD., Bhat, D., Chivian, D., Kim, DE., Sheffler, WH., Malmstrom, L., Wollacott, AM., Wang, C., Andre, I., Baker, D. 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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