Exploring drug combinations in genetic interaction network

Yin-Ying Wang, Ke-Jia Xu, Jiangning Song, Xing-Ming Zhao

Research output: Contribution to journalArticleResearchpeer-review

30 Citations (Scopus)

Abstract

Drug combination that consists of distinctive agents is an attractive strategy to combat complex diseases and has been widely used clinically with improved therapeutic effects. However, the identification of efficacious drug combinations remains a non-trivial and challenging task due to the huge number of possible combinations among the candidate drugs. As an important factor, the molecular context in which drugs exert their functions can provide crucial insights into the mechanism underlying drug combinations. RESULTS: In this work, we present a network biology approach to investigate drug combinations and their target proteins in the context of genetic interaction networks and the related human pathways, in order to better understand the underlying rules of effective drug combinations. Our results indicate that combinatorial drugs tend to have a smaller effect radius in the genetic interaction networks, which is an important parameter to describe the therapeutic effect of a drug combination from the network perspective. We also find that drug combinations are more likely to modulate functionally related pathways. CONCLUSIONS: This study confirms that the molecular networks where drug combinations exert their functions can indeed provide important insights into the underlying rules of effective drug combinations. We hope that our findings can help shortcut the expedition of the future discovery of novel drug combinations.
Original languageEnglish
Pages (from-to)1 - 7
Number of pages7
JournalBMC Bioinformatics
Volume13
Issue numberSuppl 7 (S7)
DOIs
Publication statusPublished - 2012

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