Systems Pharmacology: A Unified Framework for Prediction of Drug-Target Interactions

Author(s): Duc-Hau Le, Ly Le.

Journal Name: Current Pharmaceutical Design

Volume 22 , Issue 23 , 2016

Abstract:

Background: Drug discovery is one important issue in medicine and pharmacology area. Traditional methods using target-based approach are usually time-consuming and ineffective. Recently, the problems are approached in a system-level view and therefore it is called systems pharmacology. This research field deals with the problems in drug discovery by integrating various kinds of biomedical and pharmacological data and using advanced computational methods. Ultimately, the problems are more effectively solved. One of the most important problem in systems pharmacology is prediction of drug-target interactions. Methods: In this review, we are going to summarize various computational methods for this problem. Results: More importantly, we formed a unified framework for the problem. In addition, to study human health and disease in a more systematically and effectively, we also presented an integrated scheme for a wider problem of prediction of disease-gene-drug associations. Conclusion: By presenting the unified framework and the integrated scheme, underlying computational methods for problems in systems pharmacology can be understood and complex relationships among diseases, genes and drugs can be identified effectively.

Keywords: Drug-target interaction, network-based approach, machine learning-based approach, drug-disease association, disease-gene association, drug-gene-disease association.

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Article Details

VOLUME: 22
ISSUE: 23
Year: 2016
Page: [3569 - 3575]
Pages: 7
DOI: 10.2174/1381612822666160418121534
Price: $58

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