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Data-driven docking: HADDOCK's adventures in CAPRI

Authors

  • A. D. J. van Dijk,

    1. Department of NMR Spectroscopy, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
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  • S. J. de Vries,

    1. Department of NMR Spectroscopy, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
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  • C. Dominguez,

    1. Department of NMR Spectroscopy, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
    Current affiliation:
    1. Institute for Molecular Biology and Biophysics, ETH Zurich, 8093 Zurich, Switzerland
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  • H. Chen,

    1. Department of Physics, Drexel University, Philadelphia, Pennsylvania
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  • H.-X. Zhou,

    1. Department of Physics and Institute of Molecular Biophysics and School of Computational Science, Florida State University, Tallahassee, Florida
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  • A. M. J. J. Bonvin

    Corresponding author
    1. Department of NMR Spectroscopy, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
    • Department of NMR Spectroscopy, Bijvoet Center for Biomolecular Research, Utrecht University, 3584, Utrecht, The Netherlands
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Abstract

We have shown previously that given high-resolution structures of the unbound molecules, structure determination of protein complexes is possible by including biochemical and/or biophysical data as highly ambiguous distance restraints in a docking approach. We applied this method, implemented in the HADDOCK (High Ambiguity Driven DOCKing) package (Dominguez et al., J Am Chem Soc 2003;125:1731–1737), to the targets in the fourth and fifth rounds of CAPRI. Here we describe our results and analyze them in detail. Special attention is given to the role of flexibility in our docking method and the way in which this improves the docking results. We describe extensions to our approach that were developed as a direct result of our participation in CAPRI. In addition to experimental information, we also included interface residue predictions from PPISP (Protein–Protein Interaction Site Predictor; Zhou and Shan, Proteins 2001;44:336–343), a neural network method. Using HADDOCK we were able to generate acceptable structures for 6 of the 8 targets, and to submit at least 1 acceptable structure for 5 of them. Of these 5 submissions, 3 were of medium quality (Targets 10, 11, and 15) and 2 of high quality (Targets 13 and 14). In all cases, predictions were obtained containing at least 40% of the correct epitope at the interface for both ligand and receptor simultaneously. Proteins 2005;60:232–238. © 2005 Wiley-Liss, Inc.

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