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

Authors :
Chu Wang
David Baker
Sagar D. Khare
Philip Bradley
Rhiju Das
William Sheffler
Ingemar André
Lars Malmström
Dylan Chivian
Robert B. Vernon
David E. Kim
Divya Bhat
James Thompson
Andrew M. Wollacott
Michael D. Tyka
Srivatsan Raman
Bin Qian
Source :
Proteins. 69
Publication Year :
2007

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.

Details

ISSN :
10970134
Volume :
69
Database :
OpenAIRE
Journal :
Proteins
Accession number :
edsair.doi.dedup.....6d84822543e4b068687fa6e2e9fc1f1d