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Updated: Jan 11, 2026

Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
Published on: March 12, 2020
LC-MS-based proteomics: insights into natural product-directed cellular targeting.
Bhargav Ranapangu1, Monika Sandhu2, Atish T Paul1
1Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani campus, Pilani 333031 Rajasthan, India.
Natural products (NPs) offer therapeutic potential, investigated via proteomics. This review outlines methods using liquid chromatography-mass spectrometry (LC-MS) to understand NP effects on proteins for drug discovery.
Area of Science:
- Biochemistry
- Pharmacology
- Proteomics
Background:
- Natural products (NPs) are a rich source of bioactive molecules with significant therapeutic potential.
- Understanding the complex molecular mechanisms of NPs is crucial for drug discovery and development.
Purpose of the Study:
- To provide a comprehensive framework for investigating protein-level alterations induced by NPs using proteomics.
- To highlight key considerations and strategies for applying liquid chromatography-mass spectrometry (LC-MS) based proteomics to NP research.
Main Methods:
- Review of top-down and bottom-up proteomic methodologies.
- Discussion of critical experimental parameters: instrument selection, sample preparation, protein digestion, and quantification strategies (label-free and label-based).
- Emphasis on bioinformatics and data standardization for robust NP proteomics.
Main Results:
- Detailed framework for applying LC-MS proteomics to study NP-protein interactions.
- Case studies demonstrating the utility of proteomics in elucidating NP-affected cellular pathways.
- Identification of crucial factors for successful NP proteomics studies.
Conclusions:
- LC-MS-based proteomics provides essential insights into the molecular mechanisms of NPs.
- This approach significantly aids in identifying new therapeutic strategies and accelerating drug discovery.
- Standardized methods and careful experimental design are key to maximizing the impact of NP proteomics research.
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