Protein-protein docking based on shape complementarity and Voronoi fingerprint

Thomas Bourquard 1 Jérôme Azé 2, * Anne Poupon 3 David Ritchie 1
* Corresponding author
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 AMIB - Algorithms and Models for Integrative Biology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France
Abstract : Predicting the three-dimensional structures of protein-protein complexes is a major challenge for computational biology. Using a Voronoi tessellation model of protein structure, we showed previously that it was possible to use an evolutionary algorithm to train a scoring function to distinguish reliably between native and non-native docking conformations. Here, we show that this approach can be further improved by combining it with rigid body docking predictions generated by the Hex docking algorithm. This new approach is able to rank an acceptable or better conformation within the top 10 predictions for 7 out of the 9 targets available from rounds 8 to 18 of the CAPRI docking experiment.
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Thomas Bourquard, Jérôme Azé, Anne Poupon, David Ritchie. Protein-protein docking based on shape complementarity and Voronoi fingerprint. Emmanuel BARILLOT, Christine F ROIDEVAUX, Eduardo PC ROCHA. Journées Ouvertes Biologie Informatique Mathématiques, Jun 2011, Paris, France. Institut Pasteur, pp.9-16, 2011, JOBIM 2011. 〈inria-00613186〉

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