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

BMC Bioinformatics

Research Article

Allan Kuchinsky¹  John H Morris²  Jairo Espinosa³  Daeui Park⁴  Byoung-Chul Kim⁴  Jong Bhak⁴  Andrés F Flórez⁵  Carlos Muskus⁵ 

[1] Agilent Technologies, Santa Clara, California, USA;Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA;Grupo de Automática-GAUNAL, Universidad Nacional Sede Medellín, Medellín, Colombia;Korean BioInformation Center (KOBIC), KRIBB, 305-806, Daejeon, Korea;Programa de Estudio y Control de Enfermedades Tropicales-PECET, Universidad de Antioquia, Calle 62 No 52-59, Lab. 632, Medellín, Colombia;

关键词: Gene Ontology;    Visceral Leishmaniasis;    Leishmaniasis;    Cluster Coefficient;    Betweenness Centrality;   

DOI  :  10.1186/1471-2105-11-484

 received in 2010-01-24, accepted in 2010-09-27,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundLeishmaniasis 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.ResultsWe 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.ConclusionWe 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.

【 授权许可】

Unknown   
© Flórez et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.