A MassQL-Integrated Molecular Networking Approach for the Discovery and Substructure Annotation of Bioactive Cyclic Peptides
Tim Berger, Judith Alenfelder, Sophie A. M. Steinmüller, Dominik Heimann, Namrata Gohain, Daniel Petras, Mingxun Wang, Robert Berger, Evi Kostenis, Raphael Reher
Abstract
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 V 1A receptor, a member of the G protein-coupled receptor superfamily.