DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing

BMC Bioinformatics

Research Article

Jordan Kruger¹  Naiem T. Issa²  Stephen W. Byers³  Sivanesan Dakshanamurthy³  Rajarajan Raja⁴  Henri Wathieu⁵ 

[1] Department of Biochemistry & Molecular Biology, Georgetown University, 20057, Washington DC, USA;Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 20057, Washington DC, USA;Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 20057, Washington DC, USA;Department of Biochemistry & Molecular Biology, Georgetown University, 20057, Washington DC, USA;George Mason University, 4400 University Dr, 22030, Fairfax, VA, USA;Georgetown University Medical Center, 20057, Washington DC, USA;

关键词: DrugGenEx-NET;    TMFS;    Polypharmacology;    Gene expression analysis;    Rheumatoid arthritis;    Inflammatory bowel disease;    Parkinson’s disease;    Alzheimer’s disease;   

DOI  :  10.1186/s12859-016-1065-y

 received in 2015-12-29, accepted in 2016-04-29,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThe targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation.ResultsWe present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, −signaling pathway, −molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity.When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases.ConclusionsDGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing.

【 授权许可】

CC BY   
© Issa et al. 2016