Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home.
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.
Das
Rhiju
R
Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.
Qian
Bin
B
Raman
Srivatsan
S
Vernon
Robert
R
Thompson
James
J
Bradley
Philip
P
Khare
Sagar
S
Tyka
Michael D
MD
Bhat
Divya
D
Chivian
Dylan
D
Kim
David E
DE
Sheffler
William H
WH
Malmström
Lars
L
Wollacott
Andrew M
AM
Wang
Chu
C
Andre
Ingemar
I
Baker
David
D
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry; D012984:Software; D013816:Thermodynamics
D011506:Proteins