On the 27th of July Dr Azat Tagirdzhanov is giving a talk at the ISMB/ECCB 2023 conference in Lyon, France. He will present VarMet, a tool for high-throughput annotation of small molecule mass spectra via the modification-tolerant search of chemical databases.

Abstract

Secondary metabolites are a diverse class of small molecules with many applications in medicine and industry. Metabolomics often relies on tandem mass spectrometry to discover novel compounds but interpreting metabolomics mass spectra remains challenging and requires appropriate computational methods. We developed VarMet, a database search tool for identifying variants of secondary metabolites in mass spectrometry data. This approach extends our previous molDiscovery model for small molecule fragmentation with a modification-tolerant search inspired by VarQuest and adapted to a wide range of metabolites, including polyketides, terpenes, and lipids. We evaluated VarMet on 8,765 spectra from the GNPS spectral library and a chemical database consisting of 44,961 molecules from the NP Atlas and GNPS annotations. Correct variant was ranked first for 35% of heavy (precursor mass >500 Da) and 10% of light spectra (precursor mass <500 Da). For 59% and 25% of the spectra groups the correct variant was within the top ten identifications. We applied VarMet to the Smenospongia aurea metabolome and demonstrated how it identified a smenamide variant missed by the molecule network approach. Overall, VarMet fills the gap in the identification of novel variants of small molecules and better addresses the chemical diversity of secondary metabolites.