Simon Sieber

@simonsieber.bsky.social

PI at the University of Zürich. Natural Products Discovery, Metabolomics, Bacteria Metabolites, Cyanobacteria Blooms, Quorum Sensing, Chemoselective Probes, Diazeniumdiolates. https://www.simonsiebergroup.com/

Excited to share our new preprint: AI-guided Antibiotic Discovery Pipeline from Target Selection to Compound Identification! It includes a comprehensive benchmark of structure-based drug design (SBDD) methods and presents a full, practical pipeline for antibiotic discovery. arxiv.org/abs/2504.11091

AI-guided Antibiotic Discovery Pipeline from Target Selection to Compound Identification

Antibiotic resistance presents a growing global health crisis, demanding new therapeutic strategies that target novel bacterial mechanisms. Recent advances in protein structure prediction and machine ...

arxiv.org

We put together this protocol in part to encourage broader adoption of Multiplexed Activity Metabolomics, an engine for functional metabolomics of all types including specialized metabolite discovery. We enjoy knowing if metabolite is active before isolating it, and so should you! #natprod

Multiplexed cytometry for single cell chemical biology

Flow cytometry has great potential for screening in translational research areas due to its deep quantification of cellular features, ability to colle…

sciencedirect.com

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The newly discovered lariocidine has shown promise against AMR bacteria by targeting ribosomes with a novel mechanism of action. While still years away from market approval, its potential to combat #AMR infections offers hope in addressing the global AMR crisis. www.thevermilion.com/why-could-a-...

Why could a new class of antibiotics really make a difference?

The discovery of penicillin dates back to 1928. And since then, antibiotics have contributed to saving millions of lives all over the world, extending the average duration of human life by 23 years. I...

thevermilion.com

I am excited to share this new paper out in JPR - "MS-RT: A Method for Evaluating MS/MS Clustering Performance for Metabolomics Data." This work introduces the MS-RT method to assess MS/MS clustering accuracy on metabolomics data. doi.org/10.1021/acs....

MS-RT: A Method for Evaluating MS/MS Clustering Performance for Metabolomics Data

The clustering of tandem mass spectra (MS/MS) is a crucial computational step to deduplicate repeated acquisitions in data-dependent experiments. This technique is essential in untargeted metabolomics, particularly with high-throughput mass spectrometers capable of generating hundreds of MS/MS spectra per second. Despite advancements in MS/MS clustering algorithms in proteomics, their performance in metabolomics has not been extensively evaluated due to the lack of database search tools with false discovery rate control for molecule identification. To bridge this gap, this study introduces the MS1-retention time (MS-RT) method to assess MS/MS clustering performance in metabolomics data sets. Here, we validate MS-RT by comparing MS-RT to established proteomics clustering evaluation approaches that utilize database search identifications. Additionally, we evaluate the performance of several MS/MS clustering tools on metabolomics data sets, highlighting their advantages and drawbacks. This MS-RT method and the MS/MS clustering tool benchmarking will provide valuable real world practical recommendations for tools and set the stage for future advancements in metabolomics MS/MS clustering.

doi.org

Dearomative Diels-Alder reactions are currently hot in total synthesis. They go back to Peter Yates (who trained my mentor Sam Danishefsky). And the Wessely reaction was also discovered in Vienna :)

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