InforLorV4, PascalFrancis, Corpus, bibRecord, 000136

Spatial clustering of protein binding sites for template based protein docking

Identifieur interne : 000136 ( PascalFrancis/Corpus ); précédent : 000135; suivant : 000137

Spatial clustering of protein binding sites for template based protein docking

Auteurs : Anisah W. Ghoorah ; Marie-Dominique Devignes ; Malika Smaïl-Tabbone ; David W. Ritchie

Source :

Bioinformatics : (Oxford. Print) [ 1367-4803 ] ; 2011.

RBID : Pascal:11-0455632

Descripteurs français

Pascal (Inist)
- Analyse amas, Classification automatique, Protéine liaison, Site fixation, Arrimage.

English descriptors

KwdEn :
- Automatic classification, Binding protein, Binding site, Cluster analysis, Docking.

Abstract

Motivation: In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. Results: This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homology to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes. Availability: http://kbdock.loria.fr/ Contact: Dave.Ritchie@inria.fr Supplementary Information: Supplementary data are available at Bioinformatics online.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A11	`02`	`1`		`@1 DEVIGNES (Marie-Dominique)`
A11	`03`	`1`		`@1 SMAÏL-TABBONE (Malika)`
A11	`04`	`1`		`@1 RITCHIE (David W.)`
A14	`01`			`@1 INRIA, Campus Scientifique, BP 239 @2 54506 Vandoeuvre-lès-Nancy @3 FRA @Z 1 aut. @Z 4 aut.`
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A43	`01`			`@1 INIST @2 21331 @5 354000509195630070`
A44				`@0 0000 @1 © 2011 INIST-CNRS. All rights reserved.`
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C01	`01`		`ENG`	@0 Motivation: In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. Results: This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homology to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes. Availability: http://kbdock.loria.fr/ Contact: Dave.Ritchie@inria.fr Supplementary Information: Supplementary data are available at Bioinformatics online.
C02	`01`	`X`		`@0 002A01B`
C03	`01`	`X`	`FRE`	`@0 Analyse amas @5 05`
C03	`01`	`X`	`ENG`	`@0 Cluster analysis @5 05`
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C03	`05`	`X`	`FRE`	`@0 Arrimage @5 09`
C03	`05`	`X`	`ENG`	`@0 Docking @5 09`
C03	`05`	`X`	`SPA`	`@0 Estiba @5 09`
N21				`@1 311`
N44	`01`			`@1 OTO`
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Format Inist (serveur)

NO :	PASCAL 11-0455632 INIST
ET :	Spatial clustering of protein binding sites for template based protein docking
AU :	GHOORAH (Anisah W.); DEVIGNES (Marie-Dominique); SMAÏL-TABBONE (Malika); RITCHIE (David W.)
AF :	INRIA, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (1 aut., 4 aut.); CNRS, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (2 aut.); Nancy Université, Orpailleur Team, LORIA, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	Bioinformatics : (Oxford. Print); ISSN 1367-4803; Royaume-Uni; Da. 2011; Vol. 27; No. 20; Pp. 2820-2827; Bibl. 1 p.
LA :	Anglais
EA :	Motivation: In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. Results: This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homology to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes. Availability: http://kbdock.loria.fr/ Contact: Dave.Ritchie@inria.fr Supplementary Information: Supplementary data are available at Bioinformatics online.
CC :	002A01B
FD :	Analyse amas; Classification automatique; Protéine liaison; Site fixation; Arrimage
ED :	Cluster analysis; Automatic classification; Binding protein; Binding site; Docking
SD :	Analisis cluster; Clasificación automática; Proteína enlace; Sitio fijación; Estiba
LO :	INIST-21331.354000509195630070
ID :	11-0455632

Links to Exploration step

Pascal:11-0455632

Le document en format XML

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<front><div type="abstract" xml:lang="en">Motivation: In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. Results: This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homology to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes. Availability: http://kbdock.loria.fr/ Contact: Dave.Ritchie@inria.fr Supplementary Information: Supplementary data are available at Bioinformatics online.</div>
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<server><NO>PASCAL 11-0455632 INIST</NO>
<ET>Spatial clustering of protein binding sites for template based protein docking</ET>
<AU>GHOORAH (Anisah W.); DEVIGNES (Marie-Dominique); SMAÏL-TABBONE (Malika); RITCHIE (David W.)</AU>
<AF>INRIA, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (1 aut., 4 aut.); CNRS, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (2 aut.); Nancy Université, Orpailleur Team, LORIA, Campus Scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (3 aut.)</AF>
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   |texte=   Spatial clustering of protein binding sites for template based protein docking
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Spatial clustering of protein binding sites for template based protein docking

Spatial clustering of protein binding sites for template based protein docking

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