Chemoproteomics is back at #ASMS2026 with a bang! After the oral session mysteriously vanished last year, now we're not only back on the schedule but kicking off the conference with Ben Cravatt?! 1/n

Proteoforms as the true units of physiological function link.springer.com/ar... --- #proteomics #prot-paper

Did you ever come across a phosphosite in your proteomics data for which nothing was known? - I bet so! We have developed a new strategy termed "potency coherence analysis" that leverages the drug potency dimension in decryptM to decode the kinases that shape the human phosphoproteome. Read more:

Very happy to see that dose-response curves are now super easy to access for everyone in proteomicsDB. Just a few clicks and you can see at which concentrations your favorite drug engages protein target(s), tinkers with signaling pathways, and inhibits cell growth. Read more: doi.org/10.1093/nar/...

Exited to share our latest work! Out now in @natcomms.nature.com Koina aims to transform how #proteomics uses machine learning. You no longer need to be a tech wizard to use ML and now can easily run #ML models. Integrated with FragPipe, Skyline and EncyclopeDIA! www.nature.com/articles/s41...

A very clever approach to learn and predict MS2 spectra for modified peptides. By augmenting modification encodings and combining them with PROSIT, the new model has essentially generalized to ANY PTM - not just those in the training dataset. Super exciting !!

Very excited to see this story out in Science Signaling!! Especially the use of dose-dependent profiling at different time points could clearly separate immediate from late and consequential signaling changes in KRAS-driven (phospho)proteomes.

Assessing error control is fundamental in mass spectrometry-based proteomics. @bo-wen.bsky.social @maccoss.bsky.social @urikeich.bsky.social et al introduce a theoretical foundation for entrapment along with a method for more accurate evaluation of FDR control. www.nature.com/articles/s41...

I am looking forward to discuss with with you: • (phospho)proteome-wide dose-response profiling • statistical analysis of 180 million curves with CurveCurator • mapping kinase-resolved activities changes due to all target engagements • (re-)evaluating the kinase substrate space in humans

🚨Our new paper is online🚨 We use zero-distance⚡photo-crosslinking⚡to reveal direct protein-DNA interactions in living cells, enabling quantitative analysis of the DNA-interacting proteome on a timescale of minutes. #DNA #Chromatin #Proteomics www.cell.com/cell/fulltex...

One algorithm to rule them all? CHIMERYS bridges the gap — DDA,DIA and PRM — together at last! With #CHIMERYS, we can now directly compare DDA and DIA data — 🍎 to 🍎 finally made possible. doi.org/10.1038/s41592-025-02663-w #KusterLab #WilhelmLab #MSAID #Proteomics

🚀 Exciting news from our lab! Our latest paper has been featured on the cover of @molsystbiol.org - "Gemcitabine and ATR inhibitors synergize to kill PDAC cells by blocking DNA damage response" by Höfer et al.! 🧬🎉 doi.org/10.1038/s44320-025-00085-6 (1/4)

That is precisely why we are doing high-throughput, dose-dependent, (PTM)proteome-wide analyses to study MOAs of inhibitors, cell signaling, and cell adaptions. There is such a mess in the literature caused by either low throughput or single-dose perturbation experiments. That needs to be solved!

A very nice implementation of magnetic beads based competition pull-downs with DIA readout. This workflow is well suited for real throughput … CurveCurator is the perfect match for fast and reliable statistical analysis of these dose-response data sets.

Drug synergy is a fascinating phenomenon where 1+1=3. But what molecular mechanisms drive this effect? Our dose-resolved combination treatments with (phospho)proteome-wide readouts provide unprecedented quantitative detail of the DNA damage response. Read more: www.embopress.org/doi/full/10....

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A very cool new tool to make sense out of proteome-wide perturbation data from a pathway perspective is now integrated in proteomicsDB. Especially decryptM data can be visualized well to see drug potencies for each p-site across a pathway of proteins. Check it out !!