Sören von Bülow

@sobuelow.bsky.social

Senior Researcher at Bind Research, London

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-...

Kresten Lindorff-Larsen@lindorfflarsen.bsky.social · 8mo ago

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 & @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📝

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Kresten Lindorff-Larsen@lindorfflarsen.bsky.social · 10mo ago

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/...

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/...

Figure showing the AF-CALVADOS restraining and simulation protocol based on AF2 structure, PAE and pLDDT
bioRxiv Biophysics@biorxiv-biophys.bsky.social · 10mo ago

AF-CALVADOS: AlphaFold-guided simulations of multi-domain proteins at the proteome level https://www.biorxiv.org/content/10.1101/2025.10.19.683306v1

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...

Figure illustrating the framework for supervised learning across VAMP-seq datasets.
bioRxiv Biophysics@biorxiv-biophys.bsky.social · last yr.

Supervised learning of protein variant effects across large-scale mutagenesis datasets https://www.biorxiv.org/content/10.1101/2025.04.02.646878v1

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.

Kresten Lindorff-Larsen@lindorfflarsen.bsky.social · last yr.

Our paper on prediction of phase-separation propensities of disordered proteins from sequence is now published: www.pnas.org/doi/10.1073/... The paper has been substantially updated compared to the preprint including new experimental data and using the neural network to finetune CALVADOS. 1/n

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 🧬🧶🧪

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bioRxiv Biophysics@biorxiv-biophys.bsky.social · 2y ago

A coarse-grained model of disordered RNA for simulations of biomolecular condensates https://www.biorxiv.org/content/10.1101/2024.11.26.625489v1

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...

structures of six proteins and two (burial-dependent) substitution matrices
bioRxiv Biophysics@biorxiv-biophys.bsky.social · 2y ago

Effects of residue substitutions on the cellular abundance of proteins https://www.biorxiv.org/content/10.1101/2024.09.23.614650v1

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...

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bioRxiv Biophysics@biorxiv-biophys.bsky.social · 2y ago

Prediction of phase separation propensities of disordered proteins from sequence https://www.biorxiv.org/content/10.1101/2024.06.03.597109v1

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. 🧬🧶

Figure from the paper that shows results of simulations of both disordered proteins and multi-domain proteins w flexible linkers in two representations. When the folded domains are represented using beads at the Calpha positions, many multi-domain proteins are too compact. When the beads are located at the centre-of-mass of the residue, much better agreement with Rg data is observed.
bioRxiv Biophysics@biorxiv-biophys.bsky.social · 2y ago

A coarse-grained model for disordered and multi-domain proteins https://www.biorxiv.org/content/10.1101/2024.02.03.578735v1