Master Regulators Connectivity Map: A Transcription Factors-Centered Approach to Drug Repositioning

Drug discovery is a very expensive and time-consuming endeavor. Fortunately, recent omics technologies and Systems Biology approaches introduced interesting new tools to achieve this task, facilitating the repurposing of already known drugs to new therapeutic assignments using gene expression data a...

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Published in:Frontiers in pharmacology Vol. 9; p. 697
Main Authors: De Bastiani, Marco A, Pfaffenseller, Bianca, Klamt, Fabio
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 02-07-2018
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Summary:Drug discovery is a very expensive and time-consuming endeavor. Fortunately, recent omics technologies and Systems Biology approaches introduced interesting new tools to achieve this task, facilitating the repurposing of already known drugs to new therapeutic assignments using gene expression data and bioinformatics. The inherent role of transcription factors in gene expression modulation makes them strong candidates for master regulators of phenotypic transitions. However, transcription factors expression itself usually does not reflect its activity changes due to post-transcriptional modifications and other complications. In this aspect, the use of high-throughput transcriptomic data may be employed to infer transcription factors-targets interactions and assess their activity through co-expression networks, which can be further used to search for drugs capable of reverting the gene expression profile of pathological phenotypes employing the connectivity maps paradigm. Following this idea, we argue that a module-oriented connectivity map approach using transcription factors-centered networks would aid the query for new repositioning candidates. Through a brief case study, we explored this idea in bipolar disorder, retrieving known drugs used in the usual clinical scenario as well as new candidates with potential therapeutic application in this disease. Indeed, the results of the case study indicate just how promising our approach may be to drug repositioning.
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Reviewed by: Ka-Chun Wong, City University of Hong Kong, Hong Kong; Rui Benfeitas, Science for Life Laboratory (SciLifeLab), Sweden; Alfredo Pulvirenti, Università degli Studi di Catania, Italy
This article was submitted to Experimental Pharmacology and Drug Discovery, a section of the journal Frontiers in Pharmacology
Edited by: Andres Trostchansky, Universidad de la República, Uruguay
ISSN:1663-9812
1663-9812
DOI:10.3389/fphar.2018.00697