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A Systematic Approach to Discover New Natural Product Scaffolds Using Database-Derived Relative Mass Spectral Defects

Hyo Moon Cho1, Eleonora Boccia2, Rahim Rajwani1

  • 1Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States.

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Summary
This summary is machine-generated.

This study introduces a novel approach combining molecular networking and mass defect analysis to discover new natural products. The method led to the identification of brasiliencin A and related compounds from desert bacteria, showcasing enhanced structural novelty discovery.

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Area of Science:

  • Natural Product Discovery
  • Mass Spectrometry
  • Cheminformatics

Background:

  • Mass spectrometry (MS) advances accelerate natural product identification from complex mixtures.
  • Limitations persist in metabolite libraries and dereplication for identifying known and unknown compounds.
  • Existing strategies struggle with assigning structures and searching for novel metabolites.

Purpose of the Study:

  • To develop an improved workflow for discovering novel natural products with high structural novelty.
  • To overcome limitations in current MS data analysis and dereplication strategies.
  • To preferentially identify new compounds in the early stages of discovery.

Main Methods:

  • Combined molecular networking with MS database-derived mass defect analysis.
  • Utilized relative mass defects (RMDs) calculated from open-source databases to classify unknown metabolites.
  • Employed incongruence between ancillary data (UV, MS/MS) and RMDs to flag potential new skeletons.

Main Results:

  • Discovered brasiliencin A, a novel 18-membered macrolide from *Nocardia brasiliensis*.
  • Proposed a putative biosynthetic pathway for brasiliencin A via whole-genome sequencing.
  • Identified 29 analogs using absolute mass defect filtering (AMDF), leading to isolation of brasiliencins B-D.
  • Fully elucidated structures of brasiliencins (1-4) using spectroscopic data and quantum chemical calculations.
  • Brasiliencin A demonstrated potent activity against *Mycobacterium smegmatis* and *Streptococcus australis*.

Conclusions:

  • The RMD-assisted method effectively prioritizes the discovery of structurally novel natural products.
  • This approach enhances the identification of new compounds, including macrolides like brasiliencin A.
  • The discovered brasiliencins exhibit significant antimicrobial activities, highlighting their therapeutic potential.