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

Abstract

The marine sponge-derived fungus <i>Stachylidium bicolor</i> 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 <i>N</i>-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 (<b>1</b>) and F (<b>2</b>). We showed that endolide F (but not E) is a moderate antagonist of the arginine vasopressin V_1A receptor, a member of the G protein-coupled receptor superfamily.