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Bioinformatics Advance Access originally published online on January 19, 2008
Bioinformatics 2008 24(5):652-658; doi:10.1093/bioinformatics/btn022
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein–protein interactions

Julie Bernauer 1,2, Ranjit Prasad Bahadur 2, Francis Rodier 3, Joël Janin 2 and Anne Poupon 2,*

1Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA, 2Yeast Structural Genomics, IBBMC UMR 8619, bâtiment 430, Université Paris-Sud, 91405 Orsay and 3LEBS UPR 9063, CNRS, 91191 Gif-sur-Yvette, France

*To whom correspondence should be addressed.


  Abstract

Motivation: Knowledge of the oligomeric state of a protein is often essential for understanding its function and mechanism. Within a protein crystal, each protein monomer is in contact with many others, forming many small interfaces and a few larger ones that are biologically significant if the protein is a homodimer in solution, but not if the protein is monomeric. Telling such ‘crystal dimers’ from real ones remains a difficult task.

Results: It has already been demonstrated that the interfaces of native and non-native protein–protein complexes can be distinguished using a combination of parameters computed with a method on the Voronoi tessellation. We show in this article that the same parameters highlight significant differences between the interfaces of biological and crystal dimers. Using these parameters as descriptors in machine learning methods leads to accurate classification of specific and non-specific protein–protein interfaces.

Availability: Software is available at http://fifi.ibbmc.u-psud.fr/DiMoVo

Contact: anne{at}rezo.net

Associate Editor: Burkhard Rost

Received on October 30, 2007; revised on January 10, 2008; accepted on January 10, 2008

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