Structure prediction for CASP8 with all-atom refinement using Rosetta

Authors

  • Srivatsan Raman,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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    • Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, and Ruslan Sadreyev contributed equally to this work.

  • Robert Vernon,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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    • Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, and Ruslan Sadreyev contributed equally to this work.

  • James Thompson,

    1. Department of Genome Sciences, University of Washington, Seattle, Washington 98195
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    • Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, and Ruslan Sadreyev contributed equally to this work.

  • Michael Tyka,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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    • Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, and Ruslan Sadreyev contributed equally to this work.

  • Ruslan Sadreyev,

    1. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195
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    • Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, and Ruslan Sadreyev contributed equally to this work.

  • Jimin Pei,

    1. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195
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  • David Kim,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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  • Elizabeth Kellogg,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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  • Frank DiMaio,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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  • Oliver Lange,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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  • Lisa Kinch,

    1. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195
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  • Will Sheffler,

    1. Department of Genome Sciences, University of Washington, Seattle, Washington 98195
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  • Bong-Hyun Kim,

    1. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390
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  • Rhiju Das,

    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
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    • Current address: Department of Biochemistry and Physics, Stanford University, CA 94305.

  • Nick V. Grishin,

    1. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195
    2. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390
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  • David Baker

    Corresponding author
    1. Department of Biochemistry, University of Washington, Seattle, Washington 98195
    2. Department of Genome Sciences, University of Washington, Seattle, Washington 98195
    3. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195
    • Department of Biochemistry, University of Washington, Seattle, WA 98195
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  • The authors state no conflict of interest.

Abstract

We describe predictions made using the Rosetta structure prediction methodology for the Eighth Critical Assessment of Techniques for Protein Structure Prediction. Aggressive sampling and all-atom refinement were carried out for nearly all targets. A combination of alignment methodologies was used to generate starting models from a range of templates, and the models were then subjected to Rosetta all atom refinement. For the 64 domains with readily identified templates, the best submitted model was better than the best alignment to the best template in the Protein Data Bank for 24 cases, and improved over the best starting model for 43 cases. For 13 targets where only very distant sequence relationships to proteins of known structure were detected, models were generated using the Rosetta de novo structure prediction methodology followed by all-atom refinement; in several cases the submitted models were better than those based on the available templates. Of the 12 refinement challenges, the best submitted model improved on the starting model in seven cases. These improvements over the starting template-based models and refinement tests demonstrate the power of Rosetta structure refinement in improving model accuracy. Proteins 2009. © 2009 Wiley-Liss, Inc.

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