Simon Sieber

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/

950 followers1.1K following14 posts

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Simon Sieber reposted

Aaand it's out! Meet MITE - the natural product tailoring enzyme database, just published in @narjournal.bsky.social! MITE DB captures the substrate- and reaction-specificity of tailoring enzymes, allowing to capture this information in a human- and machine-readable way! doi.org/10.1093/nar/...

doi.orgMITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesisAbstract. Secondary or specialized metabolites show extraordinary structural diversity and potent biological activities relevant for clinical and industria
Mitja M. Zdouc@mmzdouc.bsky.social

Into natural product biosynthesis & tailoring enzymes? Frustrated by the lack of a dedicated resource to explore their functions? Tired of endless literature searches for reaction info? Meet the MITE database, freely available at mite.bioinformatics.nl. Preprint: doi.org/10.26434/che... (1/8)

Simon Sieber reposted

Thanks to the organisers for a fantastic #ICTC13 and to all the participants for the super fruitful discussions. It was my first ICTC and I had such a wonderful experience 🤩. I'm so looking forward to ICTC14 👀 @ictc13.bsky.social

ICTC13@ictc13.bsky.social

Our group photo ❤️. Big thanks to all participants for their contributions.

Simon Sieber reposted

Simon Sieber reposted

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

arxiv.orgAI-guided Antibiotic Discovery Pipeline from Target Selection to Compound IdentificationAntibiotic resistance presents a growing global health crisis, demanding new therapeutic strategies that target novel bacterial mechanisms. Recent advances in protein structure prediction and machine ...

Simon Sieber reposted

Simon Sieber reposted

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

sciencedirect.comMultiplexed cytometry for single cell chemical biologyFlow cytometry has great potential for screening in translational research areas due to its deep quantification of cellular features, ability to colle…

Simon Sieber reposted

Simon Sieber reposted

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-...

thevermilion.comWhy 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...

Simon Sieber reposted

Simon Sieber reposted

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....

doi.orgMS-RT: A Method for Evaluating MS/MS Clustering Performance for Metabolomics DataThe 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.

Simon Sieber reposted

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 :)

Simon Sieber reposted

Two very nice applications of molecular networking published this week. One for natural compounds doi.org/10.1021/jacs... and one for #PFAS doi.org/10.1038/s414... @gnps2.bsky.social #teammassspec

doi.orgA Systematic Approach to Discover New Natural Product Scaffolds Using Database-Derived Relative Mass Spectral Defects and Molecular NetworkingRapid advances in mass spectrometry (MS) data analysis have accelerated the identification of natural products from complex mixtures such as natural product extracts. However, limitations in MS data in metabolite libraries and dereplication strategies are still lacking for assigning structures to known compounds and searching for unidentified compounds. To overcome these limitations, we present an approach that combines molecular networking with MS database-derived mass defect analysis to preferentially discover new compounds with high structural novelty in the initial stage of a discovery workflow. Specifically, unknown metabolites or clusters generated from molecular networking are assigned to a compound class based on their relative mass defects (RMDs) calculated using open-source databases. If ancillary data such as ultraviolet and MS/MS spectra of the unknown clusters are incongruent with the RMD-assigned compound class, metabolites are considered to have a new skeleton that exhibits a large difference in RMD value due to structural changes. Here, we applied this RMD-assisted method to a desert-derived bacterial strain library and validated it through the discovery of brasiliencin A (1), a new 18-membered macrolide from Nocardia brasiliensis. A putative biosynthetic pathway of brasiliencin A was proposed through whole-genome sequence analysis, and an additional 29 analogs were detected using absolute mass defect filtering (AMDF) based on plausible biosynthetic products. This led to the isolation of three additional macrolides, brasiliencins B–D (2–4). The structures of the brasiliencins (1–4) were fully elucidated through spectroscopic data analysis and quantum chemical calculations including ROE distance and 13C NMR chemical shift calculations, and experimental and theoretical electronic circular dichroism (ECD). Brasiliencin A showed strong activity against Mycobacterium smegmatis and Streptococcus australis (MIC = 31.3 nM and 7.81 μM, respectively) compared to brasiliencin B (MIC = 1000 nM and 62.5 μM, respectively) that differs at a single stereocenter.

Simon Sieber reposted

Simon Sieber reposted

Simon Sieber reposted

Simon Sieber reposted

Great opportunity for a PhD student position. I strongly recommend it!

Simon Sieber reposted

Simon Sieber reposted

TWeeP (This Week's Paper): Happy new year! I'm back with my weekly highlights after the holiday break. Let's kick off 2025 with some nice bioconjugation work by Esteve, Koniev, Lehn et al. in #JACS. Dynamic imine formation triggers proximity-driven SNAr on proteins. pubs.acs.org/doi/abs/10.1...

pubs.acs.orgSelective Protein (Post-)modifications through Dynamic Covalent Chemistry: Self-activated SNAr ReactionsSNAr reactions were remarkably accelerated using a pretargeting and activating unit based on dynamic covalent chemistry (DCvC). A Cys attack at the C–F bond on the aromatic ring of salicylaldehyde derivatives was only observed upon iminium formation with a neighboring Lys residue of model small peptides. Such self-activation was ascribed to the stronger electron-withdrawing capability of the iminium bond with respect to that of the parent aldehyde that stabilized the transition state of the reaction, together with the higher preorganization of the reactive groups in the cationic aldiminium species. This approach was further applied for the functionalization of two antibodies. In both cases, the presence of the aldehyde group in close proximity to the reactive C–F bond resulted in a noteworthy increase in bioconjugation yields, with excellent chemo-selectivity. Whereas the modification of an IgG1 antibody led to stochastic product distributions, microenvironment selectivity was noted when employing IgG4, in line with the lower number of Lys residues in the hinge region of the latter. Additionally, the postfunctionalization of the modified antibodies was attained through the dynamic covalent exchange of the tethered iminium derivative with hydrazides, representing an unprecedented “tag and modify” selective bioconjugation strategy based on DCvC.

Simon Sieber reposted

Simon Sieber reposted

Simon Sieber reposted

Are you working on natural products? We’ve just released version 4.0 of the MIBiG data standard and repository! It now includes 3059 biosynthetic gene clusters, thanks to the combined efforts of 288 expert contributors. A thread: (1/8) academic.oup.com/nar/advance-...

academic.oup.comMIBiG 4.0: advancing biosynthetic gene cluster curation through global collaborationAbstract. Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in ag

Simon Sieber reposted