期刊
BMC SYSTEMS BIOLOGY
卷 6, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1752-0509-6-80
关键词
Tripartite network; Drug repositioning; Shared Neighborhood Scoring (SNS) algorithm
资金
- Global Frontier [NRF-M1AXA002-2010-0029785]
- Research Information Center Supporting Program [2012-0000350]
- WCU project of the Ministry of Education, Science, and Technology [R31-2008-000-10103-0]
- Korea Healthcare Technology [A092255-0911-1110100]
- Ministry of Health and Welfare Affairs
- EU project of the 7th framework programme (METOXIA)
- Korean Ministry of Education, Science and Technology (MEST) [20110002321]
Background: The process of drug discovery and development is time-consuming and costly, and the probability of success is low. Therefore, there is rising interest in repositioning existing drugs for new medical indications. When successful, this process reduces the risk of failure and costs associated with de novo drug development. However, in many cases, new indications of existing drugs have been found serendipitously. Thus there is a clear need for establishment of rational methods for drug repositioning. Results: In this study, we have established a database we call PharmDB which integrates data associated with disease indications, drug development, and associated proteins, and known interactions extracted from various established databases. To explore linkages of known drugs to diseases of interest from within PharmDB, we designed the Shared Neighborhood Scoring (SNS) algorithm. And to facilitate exploration of tripartite (Drug-Protein-Disease) network, we developed a graphical data visualization software program called phExplorer, which allows us to browse PharmDB data in an interactive and dynamic manner. We validated this knowledge-based tool kit, by identifying a potential application of a hypertension drug, benzthiazide (TBZT), to induce lung cancer cell death. Conclusions: By combining PharmDB, an integrated tripartite database, with Shared Neighborhood Scoring (SNS) algorithm, we developed a knowledge platform to rationally identify new indications for known FDA approved drugs, which can be customized to specific projects using manual curation. The data in PharmDB is open access and can be easily explored with phExplorer and accessed via BioMart web service (http://www.i-pharm.org/, http://biomart.i-pharm.org/).
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