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dc.contributor.authorLo, Yu-Shuen_US
dc.contributor.authorChen, Yung-Chiangen_US
dc.contributor.authorYang, Jinn-Moonen_US
dc.date.accessioned2014-12-08T15:38:20Z-
dc.date.available2014-12-08T15:38:20Z-
dc.date.issued2010-12-01en_US
dc.identifier.issn1471-2164en_US
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2164-11-S3-S7en_US
dc.identifier.urihttp://hdl.handle.net/11536/26257-
dc.description.abstractBackground: Comprehensive exploration of protein-protein interactions is a challenging route to understand biological processes. For efficiently enlarging protein interactions annotated with residue-based binding models, we proposed a new concept "3D-domain interolog mapping" with a scoring system to explore all possible protein pairs between the two homolog families, derived from a known 3D-structure dimmer (template), across multiple species. Each family consists of homologous proteins which have interacting domains of the template for studying domain interface evolution of two interacting homolog families. Results: The 3D-interologs database records the evolution of protein-protein interactions database across multiple species. Based on "3D-domain interolog mapping" and a new scoring function, we infer 173,294 protein-protein interactions by using 1,895 three-dimensional (3D) structure heterodimers to search the UniProt database (4,826,134 protein sequences). The 3D-interologs database comprises 15,124 species and 283,980 protein-protein interactions, including 173,294 interactions (61%) and 110,686 interactions (39%) summarized from the IntAct database. For a protein-protein interaction, the 3D-interologs database shows functional annotations (e. g. Gene Ontology), interacting domains and binding models (e. g. hydrogen-bond interactions and conserved residues). Additionally, this database provides couple-conserved residues and the interacting evolution by exploring the interologs across multiple species. Experimental results reveal that the proposed scoring function obtains good agreement for the binding affinity of 275 mutated residues from the ASEdb. The precision and recall of our method are 0.52 and 0.34, respectively, by using 563 non-redundant heterodimers to search on the Integr8 database (549 complete genomes). Conclusions: Experimental results demonstrate that the proposed method can infer reliable physical protein-protein interactions and be useful for studying the protein-protein interaction evolution across multiple species. In addition, the top-ranked strategy and template interface score are able to significantly improve the accuracies of identifying protein-protein interactions in a complete genome. The 3D-interologs database is available at http://3D-interologs.life.nctu.edu.tw.en_US
dc.language.isoen_USen_US
dc.title3D-interologs: an evolution database of physical protein- protein interactions across multiple genomesen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/1471-2164-11-S3-S7en_US
dc.identifier.journalBMC GENOMICSen_US
dc.citation.volume11en_US
dc.citation.issueen_US
dc.citation.epageen_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000289200400008-
dc.citation.woscount9-
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