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Reposted by Sören von Bülow

Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 10/07/2026

AF-CALVADOS is now published doi.org/10.1002/pro.... We combine AlphaFold and CALVADOS to simulate flexible multidomain proteins at scale: — Ensembles of >12000 full-length human proteins — Comparison of IDRs alone and I n context for >1500 TFs @sobuelow.bsky.social @kejohansson.bsky.social

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 14/04/2026

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-...

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 16/12/2025

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 · 20/10/2025

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

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Sören von Bülow @sobuelow.bsky.social · 02/09/2025

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.

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 17/07/2025

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

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 15/04/2025

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...

Figure showing the architecture of the CALVADOS package.

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Gräter lab @graeterlab.bsky.social · 04/04/2025

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

tinyurl.com

Max Planck Research Group Leader (W2) in Molecular Design

We are looking for exceptional early-career scientists conducting computational research with a proven record of accomplishment. The primary focus of this call is on candidates proposing research on b...

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 03/04/2025

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.

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Sören von Bülow @sobuelow.bsky.social · 25/03/2025

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.

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 12/03/2025

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

Figure from the paper illustrating sequence–ensemble–function relationships for disordered proteins. ML prediction (black) and design (orange) approaches are highlighted on the connecting arrows. Prediction of properties/functions from sequence (or vice versa, design) can include biophysics approaches via structural ensembles, or bioinformatics approaches via other hetero- geneous sources. The lower panels show examples of properties and functions of IDRs for predictions or design targets. ML, machine learning; IDRs, intrinsically disordered proteins and regions.

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 06/03/2025

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

Figure 3 from the paper showing how the phase separation propensity of WT and aromatic variants of the hnRNPA1-LCD responds linearly to PEG concentration. Panel C shows a "slab" simulation of A1-LCD with 0%, 5% and 10% PEG.

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 26/02/2025

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/...

Table of Contents figure showing the CALVADOS-RNA model and a snapshot from a mixed protein-RNA condensate

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 21/12/2024

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...

Figure 1a from the paper that outlines the method. Caption: "Peptides from the N-terminal IDR of DDX4 were encoded in a DNA library for mRNA display and transcribed using purified T7 RNA polymerase. The resulting mRNA contains a ribosomal binding site (RBS), a coding sequence (CDS) for peptide of interest, and a HA-tag for purification via the translated peptide. The synthetic mRNA (pink) is ligated to a puromycin-containing PEG-linker (black) containing a DNA sequence (blue) that forms a hetero duplex with the mRNA to facilitate single stranded RNA ligation. The resulting mRNA display molecule is purified using the HA-tag and added to an excess of DDX4N1 to measure partitioning of all library members through RNA/DNA sequencing. "

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 29/11/2024

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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Alex Holehouse @alexholehouse.bsky.social · 10/11/2024

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

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 25/09/2024

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

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 03/06/2024

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...

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · 08/02/2024

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. 🧬🧶

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.

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