Drug-repurposing identified the combination of Trolox C and Cytisine for the treatment of type 2 diabetes
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RESEARCH
Open Access
Drug-repurposing identified the combination of Trolox C and Cytisine for the treatment of type 2 diabetes Ling Jin1,2†, Jian Tu2,3†, Jianwei Jia1,2, Wenbin An3, Huanran Tan1,2*, Qinghua Cui2,4* and Zhixin Li5*
Abstract Background: Drug-induced gene expression dataset (for example Connectivity Map, CMap) represent a valuable resource for drug-repurposing, a class of methods for identifying novel indications for approved drugs. Recently, CMap-based methods have successfully applied to identifying drugs for a number of diseases. However, currently few gene expression based methods are available for the repurposing of combined drugs. Increasing evidence has shown that the combination of drugs may valid for novel indications. Method: Here, for this purpose, we presented a simple CMap-based scoring system to predict novel indications for the combination of two drugs. We then confirmed the effectiveness of the predicted drug combination in an animal model of type 2 diabetes. Results: We applied the presented scoring system to type 2 diabetes and identified a candidate combination of two drugs, Trolox C and Cytisine. Finally, we confirmed that the predicted combined drugs are effective for the treatment of type 2 diabetes. Conclusion: The presented scoring system represents one novel method for drug repurposing, which would provide helps for greatly extended the space of drugs.
Introduction Drug repurposing or drug repositioning, which aims to find new therapeutic indications for approved drugs and experimental drugs that fail approval in their initial indication, has offered several advantages over traditional drug development including rescuing stalled pharmaceutical projects, finding therapies for neglected diseases and reducing the time, cost and risk of drug development [1,2]. During the past decade, a number of computational strategies for drug repurposing have been developed [1], including strategies based on the chemical similarity of drugs [3], similarity of drug side effects * Correspondence: [email protected]; [email protected]; [email protected] † Equal contributors 1 Department of Pharmacology, Peking University Health Science Center, Beijing 100191, China 2 State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Beijing 100191, China 5 Department of Integrated Chinese and Western Medicine, Peking University Health Science Center, Beijing 100191, China Full list of author information is available at the end of the article
[4], molecular activity similarity [5], and shared molecular pathology [6]. Among these strategies, the method based on similarity of molecular activity generated from global gene expression profiling now emerges as a promising approach for drug repurposing [5]. Based on the premises of this technology, Connectivity Map (CMap) provides a data-driven and systematic approach for identifying associations among genes, drugs and disease. The publicity funded CMap reference catalogue initially contained profiles of 164 dru
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