Predicting the <i>in Vivo</i> Mechanism
of Action for Drug Leads Using NMR Metabolomics
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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 <i>in vivo</i> mechanism of action and efficacy of novel drug leads. Toward this
end, we describe an unbiased approach to predict <i>in vivo</i> mechanisms of action from NMR metabolomics data. <i>Mycobacterium
smegmatis</i>, a non-pathogenic model organism for <i>Mycobacterium
tuberculosis</i>, was treated with 12 known drugs and 3 chemical
leads identified from a cell-based assay. NMR analysis of drug-induced
changes to the <i>M. smegmatis</i> metabolome resulted in
distinct clustering patterns correlating with <i>in vivo</i> drug activity. The clustering of novel chemical leads relative to
known drugs provides a mean to identify a protein target or predict <i>in vivo</i> activity
