Blog - Bright Giant

Collaborations

Going Barcode-Free: Screening Massive Small Molecule Libraries for Early Drug Discovery

Our recent study co-authored by researchers at Bright Giant, FSU Jena, Leiden University and Oncode Institute introduces a major leap forward in affinity selection screening for early drug discovery: Self-Encoded Libraries. Our approach uses advanced mass spectrometry to screen hundreds of thousands of small molecules in a single experiment, bypassing the significant limitations of traditional high-throughput screening as well as affinity selection with barcoded libraries. It allows drug discovery teams to identify high-affinity drug candidates faster, more affordably, and against targets previously inaccessible to common screening methods.

Franziska Hufsky 2025-11-04 No Comments

Discoveries

Uncovering Hidden Contaminants in Human Milk: Non-Targeted Biomonitoring with SIRIUS

Human milk is the ideal source of nutrition for infants, but growing concerns exist about the presence of chemical contaminants that can find their way into it. For years, scientists have relied on targeted analysis, a method that can only find what they are already looking for. In this non-targeted approach utilizing SIRIUS, researcher successfully identify common and previously unreported chemical contaminants and gain a more comprehensive understanding of the chemical exposures mothers and infants face.

Franziska Hufsky 2025-10-22 No Comments

Collaborations

How to Constrain the Molecular Structure Search Space with Chemical Labeling

Unlocking the chemical ‘dark matter’ in metabolomics is a persistent challenge. A new approach addresses this by integrating derivatisation reactions for chemical labeling directly into the mass spectrometry workflow. It provides crucial structural information which is fed into small molecule annotation tools like SIRIUS to significantly constrain the molecular structure search space and boost annotation accuracy, even for previously undiscovered compounds. This powerful approach offers a scalable solution to unlock the vast, uncharted chemical space of the metabolome.

Franziska Hufsky 2025-09-15 No Comments

Tutorials

How to Manually Refine Structures for Better Annotation

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.

Franziska Hufsky 2025-08-25 No Comments

Tutorials

How to Screen for Transformation Products with SIRIUS

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.

Franziska Hufsky 2025-04-28 1 Comment

Wooden pipe in the forest from which spring water flows

Application Notes

Detecting pharmaceuticals and their transformation products with SIRIUS

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.

Franziska Hufsky 2025-04-28 1 Comment

Collaborations

Unlocking a Greater Perspective: Mapping the Chemical Space of Biomes Using SIRIUS

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.

Franziska Hufsky 2025-02-13 No Comments

Collaborations

Why Training Data Matters: Exploring Coverage Bias in Small Molecule Machine Learning

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.

Franziska Hufsky 2025-01-20 No Comments

Discoveries

a-MAIZE-ing: Sustainable Pest Control Investigated with SIRIUS

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.

Franziska Hufsky 2024-10-28 No Comments