A MassQL-Integrated Molecular Networking Approach for the Discovery and Substructure Annotation of Bioactive Cyclic Peptides.
Tim BergerJudith AlenfelderSophie A M SteinmüllerDominik HeimannNamrata GohainDaniel PetrasMingxun WangRobert BergerEvi KostenisRaphael ReherPublished in: Journal of natural products (2024)
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.
Keyphrases
- data analysis
- tandem mass spectrometry
- amino acid
- ultra high performance liquid chromatography
- high performance liquid chromatography
- liquid chromatography
- simultaneous determination
- gas chromatography
- ms ms
- nitric oxide
- small molecule
- autism spectrum disorder
- machine learning
- mass spectrometry
- palliative care
- deep learning
- single molecule
- electronic health record
- high throughput
- high resolution mass spectrometry
- healthcare
- health information
- artificial intelligence
- rna seq
- binding protein