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BMC Syst Biol. 2012; 6: 80.
Published online Jul 2, 2012. doi:  10.1186/1752-0509-6-80
PMCID: PMC3443412
Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug
Hee Sook Lee,#1,6 Taejeong Bae,#1,2,6 Ji-Hyun Lee,#1,2,6 Dae Gyu Kim,1 Young Sun Oh,1 Yeongjun Jang,3 Ji-Tea Kim,3 Jong-Jun Lee,1 Alessio Innocenti,4 Claudiu T Supuran,4 Luonan Chen,5 Kyoohyoung Rho,corresponding author3 and Sunghoon Kimcorresponding author1,2
1Medicinal Bioconvergence Research Center, College of Pharmacy, Seoul National University, Seoul, Korea
2World Class University Program Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, 151-742, Korea
3Information Center for Bio-pharmacological Network, Seoul National University, Suwon, Korea
4Dipartimento di Chimica Laboratorio di Chimica Bioinorganica, University of Florence, Via della Lastruccia, 3, Rm. 188 Polo Scientifico, Sesto Fiorentino (Firenze), 50019, Italy
5Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200233, China
6Medicinal Bioconvergence Research Center, Advanced Institutes of Convergence Technology, Suwon, 443-270, Korea
corresponding authorCorresponding author.
#Contributed equally.
Hee Sook Lee: hslpatent/at/gmail.com; Taejeong Bae: baetaej/at/i-pharm.org; Ji-Hyun Lee: jhlee/at/i-pharm.org; Dae Gyu Kim: kimeorb/at/hanmail.net; Young Sun Oh: angelino/at/snu.ac.kr; Yeongjun Jang: yjjang/at/kribb.re.kr; Ji-Tea Kim: kimshinelove/at/gmail.com; Jong-Jun Lee: juni071027/at/i-pharm.org; Alessio Innocenti: alessio.innocenti/at/unifi.it; Claudiu T Supuran: claudiu.supuran/at/unifi.it; Luonan Chen: lnchen/at/sibs.ac.cn; Kyoohyoung Rho: krho/at/kribb.re.kr; Sunghoon Kim: sungkim/at/snu.ac.kr
Received January 5, 2012; Accepted May 31, 2012.
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/).
Keywords: Tripartite network, Drug repositioning, Shared Neighborhood Scoring (SNS) algorithm
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