Run an MD simulation of any protein in the AlphaFold Protein Structure Database using AF-CALVADOS Thanks to @sobuelow.bsky.social AF-CALVADOS is now on Colab colab.research.google.com/github/KULL-...

We (@sobuelow.bsky.social & @kejohansson.bsky.social) tested AF-CALVADOS using the recently described PeptoneBench SAXS benchmark that contains SAXS data for >400 proteins with different amounts of order and disorder. The results look pretty good 😇 so we are sharing here while updating the preprint📝

We (@sobuelow.bsky.social) developed AF-CALVADOS to integrate AlphaFold and CALVADOS to simulate flexible multidomain proteins at scale See preprint for: — Ensembles of >12000 full-length human proteins — Analysis of IDRs in >1500 TFs 📜 doi.org/10.1101/2025... 💾 github.com/KULL-Centre/...

I’m excited to share that I have started a new position as Senior Scientist, Biomolecular Simulation, at @bindresearch.org in London! We are creating experimental and computational tools and public datasets with the goal of making intrinsically disordered proteins druggable.

Arriën & Giulio's paper on A coarse-grained model for disordered proteins under crowded conditions (that is the CALVADOS PEG model) is now published in final form: dx.doi.org/10.1002/pro.... @asrauh.bsky.social @giuliotesei.bsky.social

Now published! Big congrats to first author @gginell.bsky.social We are actively working improving/updating various aspects of FINCHES; don't hesitate to reach out if you run into issues, have questions. www.science.org/doi/10.1126/...

Do you like CALVADOS but are not quite sure how to make it? We’ve got your back! @sobuelow.bsky.social & @giuliotesei.bsky.social—together with the rest of the team—describe our software for simulations using the CALVADOS models incl. recipes for several applications. 1/5 doi.org/10.48550/arX...

Job alert: Join us in Mainz as Max Planck Research Group Leader (W2) in Molecular Design ...and make your own research dreams happen on de novo design, generative models, proteins, materials ... tinyurl.com/r2xjxnuk @mpip-mainz.mpg.de

Supervised training using data generated by multiplexed assays of variant effects is potentially very powerful, but is made difficult by assay- and protein-specific effects Here @tkschulze.bsky.social devised a strategy to take this into account while training models www.biorxiv.org/content/10.1...

Thanks to @lindorfflarsen.bsky.social and all authors for this wonderful project on predicting IDR phase separation from sequence! Check out the published version (including added exp. data from @tanjamittag.bsky.social) and feel free to try out our webserver.

Our review on machine learning methods to study sequence–ensemble–function relationships in disordered proteins is now out in COSB authors.elsevier.com/sd/article/S... Led by @sobuelow.bsky.social and Giulio Tesei

CALVADOS 🤝 PEG Work from @asrauh.bsky.social on a simple model for polyethylene glycol to study the effects of crowding on IDPs

CALVADOS-RNA is now published doi.org/10.1021/acs.... This is a simple model for flexible RNA that complements and works with the CALVADOS protein model. Work led by Ikki Yasuda who visited us from Keio University. Try it yourself using our latest code for CALVADOS github.com/KULL-Centre/...

Check out @rasmusnorrild.bsky.social's work with Alex Buell and Joe Rogers developing and using Condensate Partitioning by mRNA-Display to probe phase separation of ~100.000 sequences, and @sobuelow.bsky.social's simulations to support and analyse the experiments www.biorxiv.org/content/10.1...

Meet the CALVADOS RNA model Ikki Yasuda, Sören von Bülow & Giulio Tesei have parameterized a simple model for disordered RNA. Despite it's simplicity (no sequence, no base pairing) we find that it captures several phenomena that depend on the charge, stickiness and polymer properties of RNA 🧬🧶🧪

BONUS! If IDPs are your jam, check out an ever-expanding starter pack! go.bsky.app/J23B51L

New preprint w @tkschulze.bsky.social who analysed cellular abundance (VAMP-seq) data for ~32,000 variants of six proteins 🧪 We find that much of the variation can be explained and predicted by a burial-dependent substitution matrix Lots more goodies in the paper doi.org/10.1101/2024...

Happy to share work led by @sobuelow.bsky.social on prediction of phase separation of disordered proteins from sequence We combined active learning and coarse-grained simulations to develop a machine learning model for quantitative predictions of IDR phase separation 🧬🧶 doi.org/10.1101/2024...

Updated version of our coarse-grained CALVADOS model 🍎 We show that a Calpha representation of the folded domains can give rise to too compact conformations of multi-domain proteins (MDPs), and that a centre-of-mass representation in the folded domains improves agreement with experiments. 🧬🧶