1/ We're excited to announce that @rs-station.bsky.social is joining the Open Molecular Software Foundation @omsf.io!
Janani Durairaj (Jay)
@ninjani.bsky.social
Computational biologist @biozentrum.bsky.social. Likes protein structures. https://ninjani.github.io/
Team science preprint, exploring the capabilities and limitations of Alphafold3 across different application areas, including protein-RNA, protein-lipid, ubiquitination,TCR and antibody recognition with @ninjani.bsky.social @labvanni.bsky.social @dgfeller.bsky.social www.biorxiv.org/content/10.6...
Capabilities, specificity gaps and training-data dependence of AlphaFold3 across diverse application areas
Structure prediction models have moved from single proteins to assemblies that include diverse biomolecules and their modifications. AlphaFold3 (AF3) and related models extended structural modelling v...
biorxiv.org
Our lab website is finally online! pacesalab.com You can find information about our research, publications, and on-going developments in the lab.
Why AI-assisted research might have a lower impact that some estimate? I tried to look back at the rise of the internet and its impact on scientific research as a comparison point. I should stop spending time on this but condensing this info also helps me think www.evocellnet.com/2026/06/look...
Looking back at the rise of the internet to gauge the impact of AI-assisted scientific research
There is a lot of debate and some hyperbole around the impact of AI-assisted scientific research. When considering the future impact of gene...
evocellnet.com
Search with TEA 🍵 Against Many! → On the web: pickybinders.org/tea/steam → Locally: github.com/PickyBinders... Feedback welcome!
STEAM - Search with TEA against Many
Generated by create next app
pickybinders.org
Lorenzo Pantolini@lorenzopantolini.bsky.social · 8mo agoFresh 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)
Folddisco is now published @natbiotech.nature.com. It’s a fast motif search for similar 3D DISCOntinuous residues like catalytic sites or zinc fingers across the entire protein universe. 📄 www.nature.com/articles/s41... 💾 folddisco.foldseek.com 🌐 https://search.foldseek.com/folddisco
Structural motif search across the protein universe with Folddisco - Nature Biotechnology
Folddisco enables protein structural motif search in million scale databases.
nature.com
Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · last yr.Folddisco finds similar (dis)continuous 3D motifs in large protein structure databases. Its efficient index enables fast uncharacterized active site annotation, protein conformational state analysis and PPI interface comparison. 1/9🧶🧬 📄 www.biorxiv.org/content/10.1... 🌐 search.foldseek.com/folddisco
Equivariance is dead! 😢 Or is it? 😈 Genie 3 is out! Our latest protein design model achieves SoTA results for binder design and motif scaffolding, greatly improving on BindCraft and Proteina-Complexa. It does so using all-atom SE(3)-equivariance based on a branched polymer representation👇
Yeqing Lin@yeqinglin.bsky.social · 3mo agoIntroducing Genie 3, a generative protein model that substantially advances the state-of-the-art for binder design, increasing in silico success rates by up to 20x on hard multimeric targets. It also debuts a form of inference-time scaling unobserved in other design models. 🧵1/8
@lorenzopantolini.bsky.social and I are headed to @iclr-conf.bsky.social at Rio soon, with talks about this work at @gembioworkshop.bsky.social and LMRL workshops. Reach out to chat about representation learning for de novo protein design! 🫖
Janani Durairaj (Jay)@ninjani.bsky.social · 6mo agoA 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)
ROCKET 🚀 inference-time optimization of AlphaFold to fit structural data is published! rdcu.be/fa9YH Since our preprint, we’ve pushed it to regimes where other methods break: low resolution, weak signal, real experimental edge cases. Here’s what we learned: 1/15
AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network
Nature Methods - ROCKET improves experimental structure elucidation by integrating implicit structural knowledge from OpenFold, a trainable reimplementation of AlphaFold2, with X-ray...
rdcu.be
Very happy to have had a chance to attack an initially very low-resolution #cryo-EM map with #ROCKET! Thank you again @alisiafadini.bsky.social and all other co-authors of this important work, which truly shows the power of combining experimental structural biology and #AI inference. rdcu.be/fa9YH
Alisia Fadini@alisiafadini.bsky.social · 4mo agoROCKET 🚀 inference-time optimization of AlphaFold to fit structural data is published! rdcu.be/fa9YH Since our preprint, we’ve pushed it to regimes where other methods break: low resolution, weak signal, real experimental edge cases. Here’s what we learned: 1/15
Starting from an #AlphaFold-Multimer prediction, we used #ROCKET to build a model of ZPD, a homopolymeric zona pellucida (#ZP) protein, into an initial #cryo-EM map at only ~9 Å resolution. A subsequently obtained 4.6 Å map highlighted how superior the ROCKET model was over the initial prediction:
Stoic 🦾 from our shared student @daniil-litvinov.bsky.social predicts protein complex stoichiometry. A fun collab with @ninjani.bsky.social @torstenschwede.bsky.social - this #AI adventure beyond our core #CryoET methods was made possible by the @biozentrum.unibas.ch PhD Fellowship Program! 🧪 🧶🧬
Ricardo D. Righetto@lifeonthewedge.bsky.social · 5mo agoMeet 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...
Check out this awesome work from @daniil-litvinov.bsky.social: Protein complex stoichiometry prediction (both homomers and heteromers) from sequence, with some nice ablations showing what makes the difference!
Daniil Litvinov@daniil-litvinov.bsky.social · 5mo agoI'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)
New OpenFold3 preview out! (OF3p2) It closes the gap to AlphaFold3 for most modalities. Most critically, we're releasing everything, including training sets & configs, making OF3p2 the only current AF3-based model that is functionally trainable & reproducible from scratch🧵1/9
Is #AI hitting a plateau in structure prediction? Help us find out at CASP17! 🧪🧬 Calling for Targets: Immune Complexes, protein - ligand complexes, RNA/DNA, conformational ensembles, membrane proteins, viral origins, and large complexes. The Rule of Thumb: If AF3 can’t model it, we want it.
Five years ago, we released FLIP. The core question was: can ML models for protein fitness prediction generalize in the ways that actually matter for protein engineering, i.e. low data, extrapolation to more mutations, out-of-distribution sequences?
Remote homology and protein design: two sides of the same coin. Instead of finding remote homologs, we used TEA to design completely de novo proteins, folding into desired TEA sequences. I always love working with Jay, and “speed-running” this proof of concept was no exception.
Janani Durairaj (Jay)@ninjani.bsky.social · 6mo agoA 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)
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)
biorxiv.org
My time in @martinsteinegger.bsky.social's group is ending, but I’m staying in Korea to build a lab at Sungkyunkwan University School of Medicine. If you or someone you know is interested in molecular machine learning and open-source bioinformatics, please reach out. I am hiring! mirdita.org
Mirdita Lab - Laboratory for Computational Biology & Molecular Machine Learning
Mirdita Lab builds scalable bioinformatics methods.
mirdita.org
I'm really excited to break up the holiday relaxation time with a new preprint that benchmarks AlphaFold3 (AF3)/“co-folding” methods with 2 new stringent performance tests. Thread below - but first some links: A longer take: fraserlab.com/2025/12/29/k... Preprint: www.biorxiv.org/content/10.6...
Know when to co-fold'em
This is the official web page for the James Fraser Lab at UCSF.
fraserlab.com
🚀 New paper in @natmethods.nature.com! We present OpenStructure's powerful scoring capabilities, used to assess predictionsin CAMEO and CASP. Read the full study here: 🔗 doi.org/10.1038/s415... #StructuralBiology #Bioinformatics #OpenStructure #CASP #CAMEO #ProteinStructure
doi.org
Been excited about this one for a while! What would you do with a new alphabet and the wealth of protein sequence bioinformatics at your disposal? We're also around at #EMBOComp3D Heidelberg and MLSB Copenhagen this week to discuss
Lorenzo Pantolini@lorenzopantolini.bsky.social · 8mo agoFresh 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)
OpenFold3-preview (OF3p) is out: a sneak peek of our AF3-based structure prediction model. Our aim for OF3 is full AF3-parity for every modality. We now believe we have a clear path towards this goal and are releasing OF3p to enable building in the OF3 ecosystem. More👇
This October I’m drawing one molecule a day inspired by proteins in pdb @rcsbpdb.bsky.social Day 2/31 Prompt WEAVE N-terminal domain of a Fibrion - a building block of silk fiber produced by silkworms. Pdb: 3UA0 Next prompt is CROWN and I would love your suggestions!
Viral AlphaFold Database (VAD) is live in Science Advances ~27,000 predicted viral protein monomers & homodimers Conserved folds across bacteria, archaea & eukaryotic viruses New toxin–antitoxin system KreTA uncovered Vast “functional darkness” remains uncharted www.science.org/doi/10.1126/...
The Viral AlphaFold Database of monomers and homodimers reveals conserved protein folds in viruses of bacteria, archaea, and eukaryotes
VAD is a Viral AlphaFold Database of protein monomers and homodimers from viruses infecting hosts across the tree of life.
science.org
Océane Follonier @oceanef.bsky.social for “From bytes to binders: design, score and optimize” #bc2basel #posterprize
Critical benchmarking of structure prediction methods has been crucial for measuring progress and detecting breakthroughs. But how will the future look like? Join the discussion at our workshop in Basel on September 8 - just before the [BC]2 conference. @sib.swiss @biozentrum.unibas.ch ⬇️⬇️⬇️
CAMEO-3D@cameo3d.org · 11mo ago🔬 Workshop: Future of Structure Prediction Benchmarking 📅 Sept 8, 2025 | Basel 💡 Talks + breakout sessions on #CASP #CAPRI #CAMEO & benchmarking for drug discovery 🎟️ Free registration (limited spots): lu.ma/ws9nu1xf Join us to explore how benchmarking can drive breakthroughs in structure prediction.
Exciting to see our protein binder design pipeline BindCraft published in its final form in @Nature ! This has been an amazing collaborative effort with Lennart, Christian, @sokrypton.org, Bruno and many other amazing lab members and collaborators. www.nature.com/articles/s41...