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Bhak, Jong
KOrean GenomIcs Center(KOGIC)
Research Interests
  • Geromics, genomics, bioinformatics, protein Engineering, OMICS

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Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection

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dc.contributor.author Florez, Andres F. ko
dc.contributor.author Park, Daeui ko
dc.contributor.author Bhak, Jong Hwa ko
dc.contributor.author Kim, Byoung-Chul ko
dc.contributor.author Kuchinsky, Allan ko
dc.contributor.author Morris, John H. ko
dc.contributor.author Espinosa, Jairo ko
dc.contributor.author Muskus, Carlos ko
dc.date.available 2014-12-26T00:13:49Z -
dc.date.created 2014-12-24 ko
dc.date.issued 2010-09 -
dc.identifier.citation BMC BIOINFORMATICS, v.11, no., pp. - ko
dc.identifier.issn 1471-2105 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/9653 -
dc.identifier.uri http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=77957108545 ko
dc.description.abstract Background: Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease.Results: We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets.Conclusion: We have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources. ko
dc.description.statementofresponsibility close -
dc.language ENG ko
dc.publisher BIOMED CENTRAL LTD ko
dc.subject Betweenness centrality ko
dc.subject Biological process ko
dc.subject Computational approach ko
dc.subject Experimental validations ko
dc.subject Parasitic infections ko
dc.subject Potential drug targets ko
dc.subject Protein interaction networks ko
dc.subject Topological analysis ko
dc.title Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-77957108545 ko
dc.identifier.wosid 000283062500001 ko
dc.type.rims ART ko
dc.description.wostc 22 *
dc.description.scopustc 30 *
dc.date.tcdate 2015-05-06 *
dc.date.scptcdate 2014-12-24 *
dc.identifier.doi 10.1186/1471-2105-11-484 ko
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