A MassQL-Integrated Molecular Networking Approach for the Discovery and Substructure Annotation of Bioactive Cyclic Peptides
- J Nat Prod. 2024 Feb 22. doi: 10.1021/acs.jnatprod.3c00750.
- 1. Institute for Pharmaceutical Biology and Biotechnology, Department of Pharmacy, Philipps-University Marburg, Robert-Koch-Straße 4, 35037 Marburg, Germany.
- 2. Section of Molecular, Cellular and Pharmacobiology, Institute of Pharmaceutical Biology, Nussallee 6, 53115 Bonn, Germany.
- 3. Department of Chemical Biology, Helmholtz Centre for Infection Research (HZI), Inhoffenstraße 7, 38124 Braunschweig, Germany.
- 4. Department of Chemistry, Philipps-University Marburg, Hans-Meerwein-Straße 4, 35032 Marburg, Germany.
- 5. Interfaculty of Microbiology and Infection Medicine, University of Tübingen, 72076 Tübingen, Germany.
- 6. Department of Computer Science, University of California Riverside, Riverside, California 92507, United States.
The marine sponge-derived fungus Stachylidium bicolor 293 K04 is a prolific producer of specialized metabolites, including certain cyclic tetrapeptides called endolides, which are characterized by the presence of the unusual amino acid N-methyl-3-(3-furyl)-alanine. This rare feature can be used as bait to detect new endolide-like analogs through customized fragment pattern searches of tandem mass spectrometry data using the Mass Spec Query Language (MassQL). Here, we integrate endolide-specific MassQL queries with molecular networking to obtain substructural information guiding the targeted isolation and structure elucidation of the new proline-containing endolides E (1) and F (2). We showed that endolide F (but not E) is a moderate antagonist of the arginine vasopressin V1A receptor, a member of the G protein-coupled receptor superfamily.
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Cat. No.Product NameDescriptionTargetResearch Area
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target: Vasopressin ReceptorResearch Areas: Endocrinology