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HERO ID
7219638
Reference Type
Journal Article
Subtype
Review
Title
Metabolically re-modeling the drug pipeline
Author(s)
Oberhardt, MA; Yizhak, K; Ruppin, E; ,
Year
2013
Is Peer Reviewed?
Yes
Journal
Current Opinion in Pharmacology
ISSN:
1471-4892
Volume
13
Issue
5
Page Numbers
778-785
Language
English
PMID
23731523
DOI
10.1016/j.coph.2013.05.006
Web of Science Id
WOS:000326140500012
Abstract
Costs for drug development have soared, exposing a clear need for new R&D strategies. Systems biology has meanwhile emerged as an attractive vehicle for integrating omics data and other post-genomic technologies into the drug pipeline. One of the emerging areas of computational systems biology is constraint-based modeling (CBM), which uses genome-scale metabolic models (GSMMs) as platforms for integrating and interpreting diverse omics datasets. Here we review current uses of GSMMs in drug discovery, focusing on prediction of novel drug targets and promising lead compounds. We then expand our discussion to prediction of toxicity and selectivity of potential drug targets. We discuss successes as well as limitations of GSMMs in these areas. Finally, we suggest new ways in which GSMMs may contribute to drug discovery, offering our vision of how GSMMs may re-model the drug pipeline in years to come.
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