Predicting the interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service

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dc.contributor.authorJ G Kim-
dc.contributor.authorDaeui Park-
dc.contributor.authorByoung Chul Kim-
dc.contributor.authorSeong Woong Cho-
dc.contributor.authorY T Kim-
dc.contributor.authorY J Park-
dc.contributor.authorH J Cho-
dc.contributor.authorH Park-
dc.contributor.authorK B Kim-
dc.contributor.authorK O Yoon-
dc.contributor.authorS J Park-
dc.contributor.authorB M Lee-
dc.contributor.authorJong Bhak-
dc.date.accessioned2017-04-19T09:09:41Z-
dc.date.available2017-04-19T09:09:41Z-
dc.date.issued2008-
dc.identifier.issn1471-2105-
dc.identifier.uri10.1186/1471-2105-9-41ko
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/8336-
dc.description.abstractBackground: Protein-protein interactions (PPIs) play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome) of Xanthomonas oryzae pathovar oryzae (Xoo) that is an important pathogenic bacterium that causes bacterial blight (BB) in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways. Description: A PPI network in Xoo proteome was predicted by bioinformatics algorithms: PSIMAP, PEIMAP, and iPfam. We present the resultant species specific interaction network and host-pathogen interaction, XooNET. It is a comprehensive predicted initial PPI data for Xoo. XooNET can be used by experimentalists to pick up protein targets for blocking pathological interactions. XooNET uses most of the major types of PPI algorithms. They are: 1) Protein Structural Interactome MAP (PSIMAP), a method using structural domain of SCOP, 2) Protein Experimental Interactome MAP (PEIMAP), a common method using public resources of experimental protein interaction information such as HPRD, BIND, DIP, MINT, IntAct, and BioGrid, and 3) Domain-domain interactions, a method using Pfam domains such as iPfam. Additionally, XooNET provides information on network properties of the Xoo interactome. Conclusion: XooNET is an open and free public database server for protein interaction information for Xoo. It contains 4,538 proteins and 26,932 possible interactions consisting of 18,503 (PSIMAP), 3,118 (PEIMAP), and 8,938 (iPfam) pairs. In addition, XooNET provides 3,407 possible interaction pairs between two sets of proteins; 141 Xoo proteins that are predicted as membrane proteins and rice proteomes. The resultant interacting partners of a query protein can be easily retrieved by users as well as the interaction networks in graphical web interfaces. XooNET is freely available from http://bioportal.kobic.kr/ XooNET/.-
dc.publisherSpringer-BMC-
dc.titlePredicting the interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service-
dc.title.alternativePredicting the interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service-
dc.typeArticle-
dc.citation.titleBMC Bioinformatics-
dc.citation.number0-
dc.citation.endPage41-
dc.citation.startPage41-
dc.citation.volume9-
dc.contributor.affiliatedAuthorDaeui Park-
dc.contributor.affiliatedAuthorByoung Chul Kim-
dc.contributor.affiliatedAuthorSeong Woong Cho-
dc.contributor.affiliatedAuthorJong Bhak-
dc.contributor.alternativeName김정구-
dc.contributor.alternativeName박대의-
dc.contributor.alternativeName김병철-
dc.contributor.alternativeName조성웅-
dc.contributor.alternativeName김영태-
dc.contributor.alternativeName박영진-
dc.contributor.alternativeName조희정-
dc.contributor.alternativeName박현석-
dc.contributor.alternativeName김기봉-
dc.contributor.alternativeName윤경오-
dc.contributor.alternativeName박수준-
dc.contributor.alternativeName이병무-
dc.contributor.alternativeName박종화-
dc.identifier.bibliographicCitationBMC Bioinformatics, vol. 9, pp. 41-41-
dc.identifier.doi10.1186/1471-2105-9-41-
dc.description.journalClassY-
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