ArticleACS chemical biology2012
Predicting the in vivo mechanism of action for drug leads using NMR metabolomics.
Article in ACS chemical biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
46 citing papers in PubMed.
- Untargeted metabolomics for triaging of cytochrome b inhibitors during Chagas' disease drug discovery.PLoS neglected tropical diseases · 2026Article
- Article
- Integrated metabolomics and network pharmacology to investigate the anti-hyperlipidemia effect of geniposidic acid on high-fat diet induced mice.Frontiers in cell and developmental biology · 2025Article
- Review
- Decompression Mechanism of Radish Seed in Prehypertension Rats through Integration of Transcriptomics and Metabolomics Methods.Evidence-based complementary and alternative medicine : eCAM · 2023Article
- Multi-omics Investigation into the Mechanism of Action of an Anti-tubercular Fatty Acid Analogue.Journal of the American Chemical Society · 2022Article
- Integrated genomics and chemical biology herald an era of sophisticated antibacterial discovery, from defining essential genes to target elucidation.Cell chemical biology · 2022Review
- Extending the Scope ofAnalytical chemistry · 2021Article
- Elucidating the Antimycobacterial Mechanism of Action of Ciprofloxacin Using Metabolomics.Microorganisms · 2021Article
- Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning.Applied microbiology and biotechnology · 2021Article
- Deciphering the mechanism of action of antitubercular compounds with metabolomics.Computational and structural biotechnology journal · 2021Review
- The Effect of Chlorogenic Acid onMolecules (Basel, Switzerland) · 2020Article
- Phosphorus NMR and Its Application to Metabolomics.Analytical chemistry · 2020Article
- Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era.Frontiers in microbiology · 2020Review
- Metabolomics, lipidomics and proteomics profiling of myoblasts infected with Trypanosoma cruzi after treatment with different drugs against Chagas disease.Metabolomics : Official journal of the Metabolomic Society · 2019Article
- Extending the Scope ofAnalytical chemistry · 2019Article
- NMR Metabolomics Protocols for Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Mass spectrometry-based metabolomics for irritable bowel syndrome biomarkers.Therapeutic advances in gastroenterology · 2019Article
- Drug permeation and metabolism in Mycobacterium tuberculosis: Prioritising local exposure as essential criterion in new TB drug development.IUBMB life · 2018Review
- Profiling Redox and Energy Coenzymes in Whole Blood, Tissue and Cells Using NMR Spectroscopy.Metabolites · 2018Review
Corrections and comments
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Authors and funding
4 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.