1. Structural Biology and Molecular Biophysics
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Contacts-based prediction of binding affinity in protein-protein complexes

  1. Anna Vangone
  2. Alexandre M J J Bonvin  Is a corresponding author
  1. Utrecht University, Netherlands
Research Article
  • Cited 66
  • Views 4,668
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Cite this article as: eLife 2015;4:e07454 doi: 10.7554/eLife.07454

Abstract

Almost all critical functions in cells rely on specific protein-protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce a new and simple approach to predict binding affinity based on functional and structural features of the biological system, namely the network of interfacial contacts. We assess its performance against a protein-protein binding affinity benchmark and show that both experimental methods used for affinity measurements and conformational changes have a strong impact on prediction accuracy. Using a subset of complexes with reliable experimental binding affinities and combining our contacts- and contact types-based model with recent observations on the role of the non-interacting surface in protein-protein interactions, we reach a high prediction accuracy for such a diverse dataset outperforming all other tested methods.

Article and author information

Author details

  1. Anna Vangone

    Computational Structural Biology group, Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  2. Alexandre M J J Bonvin

    Computational Structural Biology group, Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht, Netherlands
    For correspondence
    a.m.j.j.bonvin@uu.nl
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Michael Levitt, Stanford University, United States

Publication history

  1. Received: March 12, 2015
  2. Accepted: July 8, 2015
  3. Accepted Manuscript published: July 20, 2015 (version 1)
  4. Accepted Manuscript updated: July 22, 2015 (version 2)
  5. Version of Record published: August 4, 2015 (version 3)
  6. Version of Record updated: April 21, 2017 (version 4)

Copyright

© 2015, Vangone & Bonvin

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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