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Classification and Exploration of 3D Protein Domain Interactions Using Kbdock

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

Comparing and classifying protein domain interactions according to their three-dimensional (3D) structures can help to understand protein structure-function and evolutionary relationships. Additionally, structural knowledge of existing domain–domain interactions can provide a useful way to find structural templates with which to model the 3D structures of unsolved protein complexes. Here we present a straightforward guide to using the “Kbdock” protein domain structure database and its associated web site for exploring and comparing protein domain–domain interactions (DDIs) and domain–peptide interactions (DPIs) at the Pfam domain family level. We also briefly explain how the Kbdock web site works, and we provide some notes and suggestions which should help to avoid some common pitfalls when working with 3D protein domain structures.

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Acknowledgments

This work was funded in part by the Agence Nationale de la Recherche, grant reference numbers ANR-08-CEXC-017-01 and ANR-MNU-006-02.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Mauritius, 80837, Reduit, Mauritius

    Anisah W. Ghoorah

  2. CNRS, LORIA, Campus Scientifique, BP 239, 54506, Vandoeuvre-lès-Nancy, France

    Marie-Dominique Devignes

  3. University of Lorraine, LORIA, Campus Scientifique, BP 239, 54506, Vandoeuvre-lès-Nancy, France

    Malika Smaïl-Tabbone

  4. Inria Nancy - Grand Est, 615 Rue Du Jardin Botanique, 54600, Villers-lès-Nancy, France

    David W. Ritchie

Authors
  1. Anisah W. Ghoorah
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  2. Marie-Dominique Devignes
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  3. Malika Smaïl-Tabbone
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  4. David W. Ritchie
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Corresponding author

Correspondence to David W. Ritchie .

Editor information

Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

    Oliviero Carugo

  2. Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

    Frank Eisenhaber

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© 2016 Springer Science+Business Media New York

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Ghoorah, A.W., Devignes, MD., Smaïl-Tabbone, M., Ritchie, D.W. (2016). Classification and Exploration of 3D Protein Domain Interactions Using Kbdock. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_5

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_5

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3570-3

  • Online ISBN: 978-1-4939-3572-7

  • eBook Packages: Springer Protocols

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