SIRIUS is setting new standards in molecular identification, enabling the elucidation of previously uncharted compounds, and making a valuable contribution to both science and industry. Here you’ll find a variety of posts showcasing how SIRIUS advances metabolomics and molecular identification.
SIRIUS is setting new standards in molecular identification, enabling the elucidation of previously uncharted compounds, and making a valuable contribution to both science and industry. Here you’ll find a variety of posts showcasing how SIRIUS advances metabolomics and molecular identification.
Do you ever look at the best hit from a structure database search and instantly know how to improve it? In SIRIUS, your chemical intuition just got a powerful new tool: the Structure Sketcher. This tutorial will demonstrate how you can leverage your own chemical knowledge to manually modify a candidate structure to achieve even better annotation results.
Detecting transformation products is crucial for environmental monitoring, as these byproducts can be more toxic and persistent than their precursor compounds. This tutorial walks you through using SIRIUS for a non-targeted combined precursor and transformation product screening, from generating a transformation product database to analysing LC-HRMS data in SIRIUS and validating results.
Pharmaceutical pollution poses risks to ecosystems and human health, yet traditional annotation methods often miss transformation products—drug breakdown compounds that may be even more persistent. We demonstrate how SIRIUS enhances annotation of pharmaceuticals in Luxembourgish rivers, from precursor drug screening to transformation product screening. Our approach for environmental monitoring is relevant not only for pharmaceuticals but also for pesticides and industrial chemicals, whose degradation products may have significant environmental impacts.
Untargeted mass spectrometry is a powerful tool for analyzing the immense chemical complexity of natural environments. However, interpreting such large datasets remains a significant challenge. To overcome this, researchers have developed an innovative approach using SIRIUS that prioritizes chemical profiling over exhaustive identification. This method allows for more effective comparisons of (micro-)biomes, providing deeper insights into biochemical diversity across different environments.
Machine learning is transforming analytical chemistry by enabling predictions of small molecule properties, crucial for drug development and other applications. However, ensuring reliable results requires careful selection of training data to avoid biases that can mislead models. Here, we explain why it was important to prepare high-quality training datasets for the machine learning methods in SIRIUS, especially given that many widely used datasets fail to evenly represent the diversity of biomolecular structures.
Agriculture has always been a dance with nature, requiring farmers to constantly adapt to changing conditions. One particularly promising method that has emerged over recent decades is push-pull technology, a strategy that uses nature’s own defenses to protect crops and boost yields. Using SIRIUS, researchers uncovered metabolites in push-pull maize that enhance its natural defense against pests.
In a world where we’re becoming increasingly conscious of what we consume, understanding the potential presence of unexpected extractables and leachables in our food and drinks is paramount. Alcoholic beverages are of particular concern due to their increased affinity and extended storage periods. A non-targeted approach to analysis is essential for uncovering both known and unknown contaminants in our drinks. By analysing fragmentation patterns, SIRIUS predicts chemical structures of unknowns to identify unexpected contaminants and ensure safety of our food.
Thawing permafrost, caused by climate change, releases stored carbon into the atmosphere, accelerating global warming. The enzyme latch hypothesis suggests that low-oxygen conditions in wetlands slow down enzymatic polyphenol degradation and carbon release. But are oxygen-dependent phenol oxidases really the only enzymes that microbial communities have in their arsenal? Or should we perhaps take a closer (metatranscriptomic and metabolomic) look at the microbially catalysed carbon cycle?
Ketamine is known for its dual role as an anesthetic and an emerging antidepressant. Despite its long-standing clinical use, the metabolic pathways and pharmacokinetics of ketamine remain poorly understood. A study of ketamine metabolism in the pig brain using SIRIUS provides valuable insights into the distribution of ketamine and its metabolites in different areas of the brain.
