title: Predicting the in vivo mechanism of action for drug leads using NMR metabolomics.
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. Toward this end, we describe an unbiased approach to predict in vivo mechanisms of action from NMR metabolomics data. Mycobacterium smegmatis, a non-pathogenic 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.
authors: Steven
authors: S
authors: Halouska
authors: Robert J
authors: RJ
authors: Fenton
authors: Raúl G
authors: RG
authors: Barletta
authors: Robert
authors: R
authors: Powers
mesh_terms: D000995:Antitubercular Agents / Q000737:chemistry / Q000494:pharmacology*; D016000:Cluster Analysis; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D055442:Metabolome / Q000187:drug effects; D055432:Metabolomics / Q000379:methods*; D009165:Mycobacterium Infections, Nontuberculous / Q000188:drug therapy* / Q000382:microbiology; D020102:Mycobacterium smegmatis / Q000187:drug effects / Q000378:metabolism; D009169:Mycobacterium tuberculosis / Q000187:drug effects / Q000378:metabolism; D011237:Predictive Value of Tests; D014376:Tuberculosis / Q000188:drug therapy / Q000382:microbiology
chemical_list: D000995:Antitubercular Agents