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An algorithm-driven intelligent mining and identification strategy for natural product mass spectrometry.

Wenyi Yu1, Xunhao Zheng2, Xiaonong Li2

  • 1Key Laboratory of Phytochemistry and Natural Medicines, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; Jiangxi Provincial Key Laboratory for Pharmacodynamic Material Basis of Traditional Chinese Medicine, Ganjiang Chinese Medicine Innovation Center, Nanchang 330000, China.

Journal of Chromatography. A
|August 30, 2024
PubMed
Summary

MS-SMART efficiently identifies novel natural products from complex plant extracts using intelligent algorithms. This method rapidly discovers new compounds, accelerating natural product research.

Keywords:
AlgorithmsData miningIdentificationMass spectrometryNatural products

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Area of Science:

  • Natural Product Chemistry
  • Analytical Chemistry
  • Computational Chemistry

Background:

  • Identifying new compounds from complex plant extracts using MS/MS data is challenging due to structural diversity.
  • Existing data post-processing techniques for MS/MS data lack specificity and precision, making structure annotation time-consuming.

Purpose of the Study:

  • To introduce MS-SMART, an innovative strategy for efficient mining and identification of new natural products.
  • To demonstrate the feasibility of MS-SMART for rapid discovery of novel compounds, using berberine-type alkaloids as a case study.

Main Methods:

  • MS-SMART integrates three intelligent algorithms: automatic diagnostic ion mining, rapid alkaloid filtration from untargeted MS/MS data, and structural recommendations.
  • Diagnostic ions were extracted and validated against reference data.
  • Berberine-type compounds were filtered, and their structures were recommended using building blocks from known berberines.

Main Results:

  • MS-SMART efficiently identified a large number of berberine-type alkaloids across diverse plant species.
  • A significant proportion of the identified compounds were novel, with many confirmed by reference standards.
  • Specifically, 103, 198, 60, 80, and 51 berberines were identified in Stephaniae Epigaeae Radix, Coptidis Rhizoma, Phellodendri Chinensis Cortex, Phellodendri Amurensis Cortex, and Corydalis Decumbentis Rhizoma, respectively.

Conclusions:

  • MS-SMART offers a novel research paradigm for the rapid discovery and identification of new compounds in complex natural product samples.
  • The strategy significantly enhances the efficiency and accuracy of natural product identification from MS/MS data.