Volume 69, Issue 4 pp. 758-763
Research Article

RosettaDock in CAPRI rounds 6–12

Chu Wang

Chu Wang

Department of Biochemistry, University of Washington, Seattle, Washington

Chu Wang and Ora Schueler-Furman contributed equally to this work.

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Ora Schueler-Furman

Ora Schueler-Furman

Department of Biochemistry, University of Washington, Seattle, Washington

Department of Molecular Genetics and Biotechnology, Hebrew University, Hadassah Medical School, Jerusalem, Israel

Chu Wang and Ora Schueler-Furman contributed equally to this work.

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Ingemar Andre

Ingemar Andre

Department of Biochemistry, University of Washington, Seattle, Washington

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Nir London

Nir London

Department of Molecular Genetics and Biotechnology, Hebrew University, Hadassah Medical School, Jerusalem, Israel

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Sarel J. Fleishman

Sarel J. Fleishman

Department of Biochemistry, University of Washington, Seattle, Washington

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Philip Bradley

Philip Bradley

Department of Biochemistry, University of Washington, Seattle, Washington

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Bin Qian

Bin Qian

Department of Biochemistry, University of Washington, Seattle, Washington

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David Baker

Corresponding Author

David Baker

Department of Biochemistry, University of Washington, Seattle, Washington

Howard Hughes Medical Institute, University of Washington, Seattle, Washington

Department of Biochemistry, University of Washington, Seattle, Box 357350, WA 98195===Search for more papers by this author
First published: 31 October 2007
Citations: 29

Abstract

A challenge in protein–protein docking is to account for the conformational changes in the monomers that occur upon binding. The RosettaDock method, which incorporates sidechain flexibility but keeps the backbone fixed, was found in previous CAPRI rounds (4 and 5) to generate docking models with atomic accuracy, provided that conformational changes were mainly restricted to protein sidechains. In the recent rounds of CAPRI (6–12), large backbone conformational changes occur upon binding for several target complexes. To address these challenges, we explicitly introduced backbone flexibility in our modeling procedures by combining rigid-body docking with protein structure prediction techniques such as modeling variable loops and building homology models. Encouragingly, using this approach we were able to correctly predict a significant backbone conformational change of an interface loop for Target 20 (12 Å rmsd between those in the unbound monomer and complex structures), but accounting for backbone flexibility in protein–protein docking is still very challenging because of the significantly larger conformational space, which must be surveyed. Motivated by these CAPRI challenges, we have made progress in reformulating RosettaDock using a “fold-tree” representation, which provides a general framework for treating a wide variety of flexible-backbone docking problems. Proteins 2007. © 2007 Wiley-Liss, Inc.

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