We are excited to announce our new tutorials on YouTube! Whether you’re a new user or looking to refresh your skills, our tutorials will guide you through the essential features of SIRIUS 6 to help you get the most out of your data.

What began as an academic project for molecular formula identification has grown into an all-in-one software solution for small molecule identification that combines powerful structure annotation methods with multiple validation levels.

SIRIUS is widely recognized and trusted within the global scientific community, processing millions of queries each year. A huge thank you to all the users for years of collaborative development and contributions and for the trust and value you are placing in SIRIUS.

Would you like to get started or are you curious about how SIRIUS can support your work? This is a great time to get involved.

Chemical breakdown products of pharmaceuticals, pesticides, or industrial chemicals can be more persistent, bioaccumulative, and even more harmful than the original compounds. As most of them are not contained in spectral libraries or structure databases, they remain unidentified, posing long-term risks to ecosystems and public health.

Our latest tutorial walks you through non-targeted screening of transformation products using SIRIUS.

Pharmaceuticals in wastewater aren’t just about the active drugs—they break down into transformation products that can be even more toxic, persistent, and bioactive. These hidden contaminants often escape detection by traditional methods. With SIRIUS, we screened 92 river water samples for precursor drugs and transformation products. We found 80 drugs and 292 transformation products, many invisible to traditional methods.

Mass spectrometry does produce different ion forms, but claiming the metabolome is mostly known is misleading. Analysis LC-MS data of 30,000 chemical standards found fewer in-source fragments than expected, suggesting they’re not as prevalent in biological samples as some argue. Even within a well-studied US National Institute of Standards and Technology (NIST) human fecal reference standard dataset, a staggering 82% of molecules lacked annotations for any ion form when carefully grouped by retention time, MS/MS data, and peak shape. This compelling finding underscores that the dark metabolome remains a significant frontier for discovery, holding countless unannotated features that could potentially represent novel molecules or provide crucial biochemical insights.

Y El Abiead et al. Nat. Metab. (2025) doi: 10.1038/s42255-025-01239-4