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Information-Driven Structural Modelling of Protein–Protein Interactions

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Book cover Molecular Modeling of Proteins

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1215))

Abstract

Protein–protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called “information-driven” approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a “classical” protein–protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes.

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Author information

Authors and Affiliations

  1. Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Faculty of Science – Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands

    João P. G. L. M. Rodrigues, Ezgi Karaca & Alexandre M. J. J. Bonvin

Authors
  1. João P. G. L. M. Rodrigues
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  2. Ezgi Karaca
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  3. Alexandre M. J. J. Bonvin
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Corresponding author

Correspondence to Alexandre M. J. J. Bonvin .

Editor information

Editors and Affiliations

  1. University of Hertfordshire, Hatfield, Hertfordshire, United Kingdom

    Andreas Kukol

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Rodrigues, J.P.G.L.M., Karaca, E., Bonvin, A.M.J.J. (2015). Information-Driven Structural Modelling of Protein–Protein Interactions. In: Kukol, A. (eds) Molecular Modeling of Proteins. Methods in Molecular Biology, vol 1215. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1465-4_18

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  • DOI: https://doi.org/10.1007/978-1-4939-1465-4_18

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1464-7

  • Online ISBN: 978-1-4939-1465-4

  • eBook Packages: Springer Protocols

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