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Background <p>Plant metabolomics is currently an emerging science of drugdiscovery from natural products that originated from the traditional use ofplants as a source of biologically active compounds. Although classicalphytochemistry has also revealed many essential metabolites, the scope andcomplexity of plant metabolomes and the ineffectiveness of conventionalapproaches leave a gap for comprehensive prospection of their therapeuticvalue.</p> Objective <p>This review fills that gap by compiling recent developments in theanalytical platforms of NMR, LC-MS, GC-MS, and imaging mass spectrometry withcomputational methods of chemometrics, machine learning, and network-basedmodeling to assess how metabolomics enhances drug discovery. </p> Methods <p>Literature evidence has pointed to the convergence of metabolomicswith genomics, transcriptomics, proteomics, and epigenomics for theinterpretation of biosynthetic pathways, metabolic engineering, and syntheticbiology, as well as for broadened applications in phytopharmaceutical qualitycontrol and herbal medicine authentication. </p> Results <p>Major challenges persist, including workflow reproducibility, poordatabase coverage, and regulatory challenges. However, recent advances likespatial metabolomics, artificial intelligence-informed predictive modeling, andintegration of microbiome and metabolome are expected to strengthentranslational effects.</p> Conclusion <p>Plant metabolomics contributes to the therapeutics discoverypipeline from natural products and places ethnopharmacological knowledge in itscontemporary context, thereby solidifying its central role in drug discovery inthe future.</p>

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Plant Metabolomics in Natural Product Drug Discovery: Emerging Approaches, Challenges, and Translational Potential

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Satish Meshram,
  • Prakash Itankar,
  • Satyendra Prasad,
  • Sameer Sheikh,
  • Ujban Husain,
  • Anil Badnale,
  • Ashwini Ghagare,
  • Shrushti Dhakare

摘要

Background

Plant metabolomics is currently an emerging science of drugdiscovery from natural products that originated from the traditional use ofplants as a source of biologically active compounds. Although classicalphytochemistry has also revealed many essential metabolites, the scope andcomplexity of plant metabolomes and the ineffectiveness of conventionalapproaches leave a gap for comprehensive prospection of their therapeuticvalue.

Objective

This review fills that gap by compiling recent developments in theanalytical platforms of NMR, LC-MS, GC-MS, and imaging mass spectrometry withcomputational methods of chemometrics, machine learning, and network-basedmodeling to assess how metabolomics enhances drug discovery.

Methods

Literature evidence has pointed to the convergence of metabolomicswith genomics, transcriptomics, proteomics, and epigenomics for theinterpretation of biosynthetic pathways, metabolic engineering, and syntheticbiology, as well as for broadened applications in phytopharmaceutical qualitycontrol and herbal medicine authentication.

Results

Major challenges persist, including workflow reproducibility, poordatabase coverage, and regulatory challenges. However, recent advances likespatial metabolomics, artificial intelligence-informed predictive modeling, andintegration of microbiome and metabolome are expected to strengthentranslational effects.

Conclusion

Plant metabolomics contributes to the therapeutics discoverypipeline from natural products and places ethnopharmacological knowledge in itscontemporary context, thereby solidifying its central role in drug discovery inthe future.