GNPS - molecular networking of Trillium tschonoskii.
Ontology highlight
ABSTRACT: This is a dataset used for the orchestration of molecular networking which led the discovery of polyacetylated 18-norspirostanol saponins from Trillium tschonoskii.
Project description:This is a dataset used for the orchestration of molecular networking which led the discovery of polyacetylated 18-norspirostanol saponins from Trillium tschonoskii.
Project description:This dataset contains the raw data used for MZmine processing and Feature-based molecular networking of semi-purified fractions obtained from A. timonensis used for bioactive molecular networking to reveal contribution of sulfonolipids to observed biological activity.
Project description:mgf files, quantification tables and metadata files used in the publication Buedenbender et al., "Bioactive Molecular Networking for Mapping the Antimicrobial Constituents of the Baltic Brown Alga Fucus vesiculosus", Marine Drugs, 2020
Project description:GNPS Feature-Based Molecular Networking Workshop - American Gut subset with metadata for plant consumption
See manuscript here: https://msystems.asm.org/content/3/3/e00031-18
Project description:Mass spectrometry is the current technique of choice in studying drug metabolism. High-resolution mass spectrometry (HR-MS) in combination with fragment analysis (MS/MS) has the potential to contribute to rapid advances in this field. However, the data emerging from such fragmentation spectra pose challenges to downstream analysis, given their complexity and size. Here we apply a molecular networking approach to seek drugs and their metabolites, in fragmentation spectra from urine derived from a cohort of 26 patients on antihypertensive therapy. In total, 165 separate drug metabolites were found and structurally annotated (17 by spectral matching and 122 by classification based on a clustered fragmentation pattern). The clusters could be traced to 13 drugs including the known antihypertensives verapamil, losartan and amlopidine. The molecular networking approach also generated networks of endogenous metabolites, including carnitine derivatives, and conjugates containing glutamine, glutamate and trigonelline. The approach offers unprecedented capability in the untargeted identification of drugs and their metabolites at the population level and has great potential to contribute to understanding stratified responses to drugs where differences in drug metabolism may determine treatment outcome. Keywords: Antihypertensive drugs, Drug metabolism, Fragmentation, High-resolution mass spectrometry, Metabolomics, Urine.
Project description:Example dataset for Methods in Molecular Biology Chapter - Feature Based Molecular Networking for Metabolite Annotation. This dataset includes the LC-MS/MS raw data (Bruker .d file format and centroided mzXML file format), metadata table used for the ste-by-step instructions, a batch file for MZmine2 data processing, and all resulting files from the MZmine2 and GNPS processing.