Protein-protein docking based on shape complementarity and Voronoi fingerprint
Identifieur interne : 001D32 ( Hal/Checkpoint ); précédent : 001D31; suivant : 001D33Protein-protein docking based on shape complementarity and Voronoi fingerprint
Auteurs : Thomas Bourquard [France] ; Jérôme Azé [France] ; Anne Poupon [France] ; David Ritchie [France]Source :
English descriptors
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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Hal:inria-00613186Le document en format XML
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nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>CAPRI</term><term>Evolutionary Algorithms</term><term>Hex</term><term>Protein-protein Docking</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Protein-protein docking based on shape complementarity and Voronoi fingerprint</title><author role="aut"><persName><forename type="first">Thomas</forename><surname>Bourquard</surname></persName><email>Thomas.Bourquard@inria.fr</email><idno type="halauthor">630788</idno><affiliation ref="#struct-2358"></affiliation></author><author role="crp"><persName><forename type="first">Jérôme</forename><surname>Azé</surname></persName><email>jerome.aze@lri.fr</email><idno type="idhal">jerome-aze</idno><idno type="halauthor">444687</idno><affiliation ref="#struct-103784"></affiliation></author><author role="aut"><persName><forename type="first">Anne</forename><surname>Poupon</surname></persName><email>anne.poupon@tours.inria.fr</email><idno type="halauthor">444688</idno><affiliation ref="#struct-199335"></affiliation></author><author role="aut"><persName><forename type="first">David</forename><surname>Ritchie</surname></persName><email>Dave.Ritchie@inria.fr</email><idno type="idhal">david-ritchie</idno><idno type="halauthor">560570</idno><affiliation ref="#struct-2358"></affiliation></author><editor role="depositor"><persName><forename>David</forename><surname>Ritchie</surname></persName><email>Dave.Ritchie@inria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2011-08-03 11:53:42</date><date type="whenModified">2016-05-18 08:54:11</date><date type="whenReleased">2011-08-04 11:43:26</date><date type="whenProduced">2011-06-28</date><date type="whenEndEmbargoed">2011-08-03</date><ref type="file" target="https://hal.inria.fr/inria-00613186/document"><date notBefore="2011-08-03"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/inria-00613186/file/bourquard_etal_jobim_2011.pdf"><date notBefore="2011-08-03"></date></ref></edition><respStmt><resp>contributor</resp><name key="145516"><persName><forename>David</forename><surname>Ritchie</surname></persName><email>Dave.Ritchie@inria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00613186</idno><idno type="halUri">https://hal.inria.fr/inria-00613186</idno><idno type="halBibtex">bourquard:inria-00613186</idno><idno type="halRefHtml">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</idno><idno type="halRef">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</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-TOURS">Université François Rabelais</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="INRA">INRA - Institut national de la recherche agronomique</idno><idno type="stamp" n="LIX">Laboratoire d'informatique de l'école polytechnique</idno><idno type="stamp" n="INRIA-SACLAY">INRIA Saclay - Ile de France</idno><idno type="stamp" n="X" p="PARISTECH">Ecole Polytechnique</idno><idno type="stamp" n="PARISTECH">ParisTech</idno><idno type="stamp" n="X-LIX" p="X">Laboratoire d'informatique de l'X (LIX)</idno><idno type="stamp" n="X-DEP">Polytechnique</idno><idno type="stamp" n="X-DEP-INFO" p="X-DEP">Département d'informatique</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="UMR8623">Laboratoire de Recherche en Informatique</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="3">National</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Protein-protein docking based on shape complementarity and Voronoi fingerprint</title><author role="aut"><persName><forename type="first">Thomas</forename><surname>Bourquard</surname></persName><email>Thomas.Bourquard@inria.fr</email><idno type="halAuthorId">630788</idno><affiliation ref="#struct-2358"></affiliation></author><author role="crp"><persName><forename type="first">Jérôme</forename><surname>Azé</surname></persName><email>jerome.aze@lri.fr</email><idno type="idHal">jerome-aze</idno><idno type="halAuthorId">444687</idno><affiliation ref="#struct-103784"></affiliation></author><author role="aut"><persName><forename type="first">Anne</forename><surname>Poupon</surname></persName><email>anne.poupon@tours.inria.fr</email><idno type="halAuthorId">444688</idno><affiliation ref="#struct-199335"></affiliation></author><author role="aut"><persName><forename type="first">David</forename><surname>Ritchie</surname></persName><email>Dave.Ritchie@inria.fr</email><idno type="idHal">david-ritchie</idno><idno type="halAuthorId">560570</idno><affiliation ref="#struct-2358"></affiliation></author></analytic><monogr><meeting><title>Journées Ouvertes Biologie Informatique Mathématiques</title><date type="start">2011-06-28</date><date type="end">2011-07-01</date><settlement>Paris</settlement><country key="FR">France</country></meeting><editor>Emmanuel BARILLOT, Christine F ROIDEVAUX, Eduardo PC ROCHA</editor><imprint><publisher>Institut Pasteur</publisher><biblScope unit="serie">JOBIM 2011</biblScope><biblScope unit="pp">9-16</biblScope><date type="datePub">2011-07-28</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="fr">French</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Protein-protein Docking</term><term xml:lang="en">Evolutionary Algorithms</term><term xml:lang="en">Hex</term><term xml:lang="en">CAPRI</term></keywords><classCode scheme="halDomain" n="info.info-bi">Computer Science [cs]/Bioinformatics [q-bio.QM]</classCode><classCode scheme="halDomain" n="sdv.bibs">Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">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.</abstract><abstract xml:lang="fr">La prédiction de la structure tri-dimensionnelle des complexes protéine-protéine est un enjeu majeur pour la bioinformatique. Nous avions montré dans des travaux précédents que grâce à la modélisation par un diagramme de Voronoï de la structure des protéines, et à l'utilisation d'algorithmes génétiques, il était possible d'optimiser des fonctions de score permettant de distinguer avec une bonne fiabilité les conformations natives des conformations non-natives. Nous montrons dans cet article que cette approche peut être sensiblement améliorée en combinant celle-ci avec des modèles en corps rigide générés par l'algorithme de docking Hex. Cette nouvelle approche, testée sur les cibles CAPRI des rounds 8 à 18, permet de classer dans les 10 meilleures, une conformation quasi-native pour 7 cibles sur les 9 disponibles.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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