A MassQL-Integrated Molecular Networking Approach for the Discovery and Substructure Annotation of Bioactive Cyclic Peptides.

The marine sponge-derived fungus 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 -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 () and F (). We showed that endolide F (but not E) is a moderate antagonist of the arginine vasopressin V receptor, a member of the G protein-coupled receptor superfamily.