When we eat deep-fried food, we expose ourselves to a complex mix of reactive chemical species. To protect us, our bodies neutralize these toxicants through glutathione conjugation, eventually excreting them in urine as mercapturic acid conjugates (MACs). However, mapping these urinary biomarkers has long been a challenge because many escape standard screening methods or aren’t registered in public databases.

Using SIRIUS molecular structure annotation, researchers identified 847 features—including 581 novel metabolites entirely missing from HMDB and PubChem. They proved that consuming deep-fried foods leads to a spike in urinary MACs derived from toxic reactive aldehydes, lipid oxidation products, and metabolic intermediates.

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Y.-C. Chen et al. Anal. Chem. (2026) 10.1021/acs.analchem.5c08181

Understanding the metabolic fate of pharmaceutical drugs is a critical component of modern drug discovery and safety testing. Tracking these metabolic changes is notoriously difficult. Identifying the precise structures of drug metabolites within complex mixtures remains a massive analytical bottleneck. To overcome this hurdle, we have integrated BioTransformer in SIRIUS. Researchers have benchmarked this approach using six diverse model drugs and found that it not only bypasses the need for exhaustive manual identification but actively expands our structural coverage of the metabolome.

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V. Pozo Garcia et al. Arch. Toxicol. (2026) 10.1007/s00204-025-04248-0

Diterpenoid alkaloids are an exceptionally complex class of plant metabolites heavily valued for their therapeutic potential. However, their intricate architectures render chemical synthesis unfeasible, while their trace abundance in wild plants, like wolfsbane, limits pharmaceutical scaling. Biosynthetic production in heterologous hosts offers an appealing alternative, but the specific enzymatic steps assembling these compounds have remained uncharacterized.

In a recent study published in Molecular Plant, researchers deployed a combination of comparative transcriptomics and advanced computational metabolomics to solve the entry steps of diterpenoid alkaloid biosynthesis. The team utilized SIRIUS within their untargeted LC-MS/MS pipeline to systematically annotate molecular formulas and predict compound classes to unlock the nitrogen-tracking pathway.

Key discoveries:
✨ Ethanolamine, rather than ethylamine, serves as the primary nitrogen donor for this class of metabolites—even when the final structures prominently display an ethyl group.
✨ Elucidation of six conserved enzymatic steps that form a minimal biosynthetic pathway sufficient for the de novo production of the foundational diterpenoid alkaloid atisinium.

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G.P. Miller et al. Molecular Plant (2026) 10.1016/j.molp.2026.05.022

Identifying the botanical origins of yellow dyes in ancient textiles is a notorious challenge due to the chemical overlap of common pigments across different plant species. This study introduces a robust metabolomics workflow designed to move beyond ubiquitous molecules like quercetin to find species-specific “Gold” chemical markers using SIRIUS.

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L. Mas-Normand et al. Microchem. J. (2025) doi: 10.1016/j.microc.2025.115621

The specialized metabolism of ferns remains a largely untapped frontier in the search for natural medicinal compounds. Using SIRIUS molecular structure annotation, researchers successfully identified a previously unknown lignan named blechnic acid B. This novel compound, found in Neoblechnum brasiliense, highlights the chemical diversity hidden within under-investigated plant lineages.

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M. Ufland et al. Plant Biol. (2026) doi: 10.1111/plb.70116

Deep within the aphotic zones of the Amazon’s ferruginous caves, a hidden world of microbial “dark matter” holds immense potential as a source for pharmacological innovation. A pioneering metabolomic survey of these extreme environments isolates rare bacterial genera that thrive in these iron-rich landscapes. They use SIRIUS to identify and classify chemical features, including potent cyclopeptides demonstrating growth inhibition against cancer cell lines.

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N. N. Kato et al. Chem. Biodivers. (2026) doi: 10.1002/cbdv.202502912