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

ABSTRACT: Rapid advances in mass spectrometry (MS) data analysis have accelerated the identification of natural products from complex mixtures such as natural product extracts. However, limitations in MS data in metabolite libraries and dereplication strategies are still lacking for assigning structures to known compounds and searching for unidentified compounds. To overcome these limitations, we present an approach that combines molecular networking with MS database-derived mass defect analysis to preferentially discover new compounds with high structural novelty in the initial stage of a discovery workflow. Specifically, unknown metabolites or clusters generated from molecular networking are assigned to a compound class based on their relative mass defects (RMDs) calculated using open-source datab

SUBMITTER: Cho HM 

PROVIDER: S-EPMC11862952 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature