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

نویسندگان

  • Rhiju Das
  • Bin Qian
  • Srivatsan Raman
  • Robert Vernon
  • James Thompson
  • Philip Bradley
  • Sagar Khare
  • Michael D Tyka
  • Divya Bhat
  • Dylan Chivian
  • David E Kim
  • William H Sheffler
  • Lars Malmström
  • Andrew M Wollacott
  • Chu Wang
  • Ingemar Andre
  • David Baker
چکیده

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.

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عنوان ژورنال:
  • Proteins

دوره 69 Suppl 8  شماره 

صفحات  -

تاریخ انتشار 2007