Published Research - Department of Chemistry

 

Date of this Version

2012

Citation

ACS Chem Biol. 2012 January 20; 7(1): 166–171. doi:10.1021/cb200348m.

Comments

Copyright 2011 Am Chem Soc; used by permission.

Abstract

New strategies are needed to circumvent increasing outbreaks of resistant strains of pathogens and to expand the dwindling supply of effective antimicrobials. A common impediment to drug development is the lack of an easy approach to determine the in vivo mechanism of action and efficacy of novel drug leads. Towards this end, we describe an unbiased approach to predict in vivo mechanisms of action from NMR metabolomics data. Mycobacterium smegmatis, a nonpathogenic model organism for Mycobacterium tuberculosis, was treated with 12 known drugs and 3 chemical leads identified from a cell-based assay. NMR analysis of drug-induced changes to the M. smegmatis metabolome resulted in distinct clustering patterns correlating with in vivo drug activity. The clustering of novel chemical leads relative to known drugs provides a mean to identify a protein target or predict in vivo activity.

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