Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug

Hee S. Lee, Taejeong Bae, Ji Hyun Lee, Dae G. Kim, Young S. Oh, Yeongjun Jang, Ji Tea Kim, Jong Jun Lee, Alessio Innocenti, Claudiu T. Supuran, Luonan Chen, Kyoohyoung Rho, Sunghoon Kim

Research output: Contribution to journalArticlepeer-review

64 Citations (Scopus)

Abstract

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/).

Original languageEnglish
Article number80
JournalBMC Systems Biology
Volume6
DOIs
Publication statusPublished - 2012 Jul 2

Bibliographical note

Funding Information:
The authors thank to Sangho Oh and Nam-Jin Koo at Korean Bioinformation Center for updating PharmDB data. This study was supported by the grants of the Global Frontier (NRF-M1AXA002-2010-0029785) and the Research Information Center Supporting Program (2012–0000350) and the WCU project (R31-2008-000-10103-0) of the Ministry of Education, Science, and Technology and Korea Healthcare Technology (A092255-0911-1110100), the Ministry of Health and Welfare Affairs, and Gyonggi-do to SK, an EU project of the 7th framework programme (METOXIA) to CTS, and by the Korean Ministry of Education, Science and Technology (MEST) under grant number 20110002321.

All Science Journal Classification (ASJC) codes

  • Structural Biology
  • Modelling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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