Sören von Bülow
@sobuelow.bsky.social
420 followers 230 following 6 posts
Senior Researcher at Bind Research, London
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sobuelow.bsky.social
Huge thanks to @lindorfflarsen.bsky.social and all the members of SBiNLab at the University of Copenhagen for three fantastic postdoctoral years!
sobuelow.bsky.social
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.
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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
sobuelow.bsky.social
They mostly leverage things now
sobuelow.bsky.social
Congratulations! 🙌
Reposted by Sören von Bülow
alexholehouse.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/...
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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.
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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.
sobuelow.bsky.social
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.
lindorfflarsen.bsky.social
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
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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.
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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.
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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. "
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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 🧬🧶🧪
Reposted by Sören von Bülow
alexholehouse.bsky.social
BONUS! If IDPs are your jam, check out an ever-expanding starter pack!
go.bsky.app/J23B51L
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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...
Reposted by Sören von Bülow
lindorfflarsen.bsky.social
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.