I'm excited to share *Stoic*, a method for fast and accurate protein complex stoichiometry prediction directly from sequence. Preprint: www.biorxiv.org/content/10.6... 🧵👇(1/10)

Meet Stoic from @daniil-litvinov.bsky.social and @ninjani.bsky.social: embeddings to predict stoichiometry of protein complexes from sequence fast and accurately 🧬🧩💻🤩 www.biorxiv.org/content/10.6...

A fun little idea that worked surprisingly well, using a structure-informed yet structure-independent alphabet for de novo protein design: www.biorxiv.org/content/10.6... 🧵(1/n)

Fresh from bioRxiv our latest work introducing The Embedded Alphabet (TEA), a powerful new representation for protein sequences obtained by discretising ESM2 embeddings into 20 characters. Pre-print: www.biorxiv.org/content/10.1... 🧵👇(1/n)

🧪🧬🔬 Postdoc in Computational Structural Biology at the @biozentrum.unibas.ch & @sib.swiss in Basel, Switzerland. www.biozentrum.unibas.ch/open-positio... The position is initially funded for 3 years, possibility to start immediately. #StructurePrediction, #Bioinformatics, #Uniprot3D, #AI

In case you missed it!

Some very cool stuff from the group now in paper form: “ModelArchive: a deposition database for computational macromolecular structural models” doi.org/10.1016/j.jm... And “Comparing macromolecular complexes - a fully automated benchmarking suite” doi.org/10.21203/rs.... (under review)

Join us tomorrow to hear @peterskrinjar.bsky.social talk about 🌹 Runs N' Poses 🌹! Curious to hear your thoughts on how to keep up with benchmarking in this field.

RT please: Just 1.5 months away from our joint 3DBioinfo/3DSIG amazing conference! These are our two great keynote speakers! @rolanddunbrack.bsky.social & @silviaosuna.bsky.social! Check our preliminary programme here: www.iscb.org/3dbioinfo202... Registration link: www.iscb.org/3dbioinfo202...

We’re hosting @peterskrinjar.bsky.social for a webinar to discuss his latest paper “Have protein co-folding methods moved beyond memorization?”! Join live on Feb 21st at 11 AM ET. Register here: us06web.zoom.us/webinar/regi... Explore Runs N’ Poses on Polaris today: polarishub.io/benchmarks/p...

How long does it take to predict ligand binding sites for all 220k proteins in the PDB? P2Rank 2.5 does it in 3 hours on a single CPU (16-core amd 5950x)—2x faster than the previous version 🚀. (1/n)

We re-ran AF3 without templates, since we noticed it could use any template in the PDB, including the ground truth. We see the performance drops slightly in the lowest bins, but the gap to other methods still exists. We will update the preprint shortly!

We’re extremely excited to host Runs N’ Poses on Polaris! The authors show how current co-folding methods struggle to generalize beyond ligand poses in their training data. Explore the benchmark: polarishub.io/benchmarks/p... Explore the dataset: polarishub.io/datasets/pli...

New leaderboard on @polarishub.io for Runs 'N Poses! 🎸 Anyone has any protein-ligand co-folding methods laying around they would like to put to the test? polarishub.io/benchmarks/p... Great work @peterskrinjar.bsky.social @jeeberhardt.bsky.social @torstenschwede.bsky.social @ninjani.bsky.social

Have #AI methods for protein-ligand co-folding moved beyond memorisation and predict really novel leads for #drugdiscovery? Or do we find “more of the same”? This new benchmark lets you find out… ⬇️⬇️⬇️

Basically, novelty is not defined by time in the PDB.

We’ve been benchmarking deep learning co-folding methods for protein-ligand complex prediction, leading to the creation of 🌹Runs N’ Poses🌹. Great effort by @peterskrinjar.bsky.social and @jeeberhardt.bsky.social putting this together so quickly. Please have a look, excited for community feedback!

Excited to share our latest preprint evaluating AlphaFold3, Boltz-1, Chai-1 and Protenix for predicting protein-ligand interactions, featuring our newly introduced benchmark dataset 🌹Runs N’ Poses🌹! www.biorxiv.org/content/10.1... 🧵👇 (1/n)

Re docking: @workshopmlsb.bsky.social has been piloting a leaderboard for the PLINDER benchmark. It would be awesome to get submissions using existing methods, then everyone can see comparisons better 😁 leaderboard & instructions are on mlsb.io

We actually had a similar benchmark (with LDDT-PLI) in the same CASP15 issue a while ago (onlinelibrary.wiley.com/doi/10.1002/..., Fig3B) conclusions were (1) pocket detection needed for physics-based (2) DL models overfit (3) nothing performs on non "re-docking". Was my main inspiration for PLINDER

AF3 BEST METHOD followed by cluspro but also some conversion errors

@jeeberhardt.bsky.social presenting CASP16 PLI baselines. Big shout out to @jeremywohlwend.bsky.social and @gcorso.bsky.social for helping us with running Boltz-1 on short notice! Pretty weird results on autotaxin.

It is a great privilege and honor to be elected as new President of the SNSF Research Council. I’m very much looking forward to serving the Swiss scientific community in this new role in the coming years. snf.ch/en/xgVKfkp88...