Fast MSAs are coming to nucleic acids! Riboseek has been super helpful for some of my own work, very excited to see what people do with this cool new tool! Amazing collaboration as always with @milot.bsky.social @martinsteinegger.bsky.social and co, led by @sukhwanpark.bsky.social!

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · 4d ago

Riboseek is a fast RNA/DNA search. More sensitive than nhmmer at 250x speed. Structure-aware realignment produces MSAs approaching rMSA quality. Plus 1.7M precomputed RNA MSAs, and an API to search your own 📄 www.biorxiv.org/content/10.6... 💾 github.com/steineggerla... 🌐 search.foldseek.com/riboseek

My lab was lucky to be able to help test Proteina-Complexa binders experimentally. We were blown away by the results. Congrats to our colleagues at NVIDIA!

Kieran Didi@kdidi.bsky.social · 5mo ago

📢 We’re launching Proteina-Complexa — and after the Jensen keynote mention, we definitely had to post this thread now ;) Atomistic binder design with generative pretraining + test-time compute, plus large-scale wet-lab validation. Project page: research.nvidia.com/labs/genair/... 🧵 1/n

Efficient protein structure prediction fromcompact computers to datacenters withOpenFold-TRT https://www.biorxiv.org/content/10.64898/2026.03.11.711233v1

📢 We’re launching Proteina-Complexa — and after the Jensen keynote mention, we definitely had to post this thread now ;) Atomistic binder design with generative pretraining + test-time compute, plus large-scale wet-lab validation. Project page: research.nvidia.com/labs/genair/... 🧵 1/n

Too many REPA / RAE / representation alignment papers lately? I was lost too, so I wrote a blog post that organizes the space into phases and zooms in on what actually matters for general/molecular ML. Curious what folks think - link below! 🔗 Blog: kdidi.netlify.app/blog/ml/2025...

The unification of representation learning and generative modelling

A deep dive into the convergence of discriminative and generative AI, covering 4 phases of evolution from REPA to RAE and beyond.

kdidi.netlify.app

GPU-accelerated MMseqs2 offers tremendous speedup for homology retrieval, protein structure prediction with ColabFold, and protein structure search with Foldseek. @martinsteinegger.bsky.social @milot.bsky.social @machine.learning.bio www.nature.com/articles/s41...

GPU-accelerated homology search with MMseqs2 - Nature Methods

Graphics processing unit-accelerated MMseqs2 offers tremendous speedups for homology retrieval from metagenomic databases, query-centered multiple sequence alignment generation for structure predictio...

nature.com

MMseqs2-GPU sets new standards in single query search speed, allows near instant search of big databases, scales to multiple GPUs and is fast beyond VRAM. It enables ColabFold MSA generation in seconds and sub-second Foldseek search against AFDB50. 1/n 📄 www.nature.com/articles/s41... 💿 mmseqs.com

GPU-accelerated homology search with MMseqs2 - Nature Methods

Graphics processing unit-accelerated MMseqs2 offers tremendous speedups for homology retrieval from metagenomic databases, query-centered multiple sequence alignment generation for structure predictio...

nature.com

AtomWorks is out! Building upon @biotite_python, we built a toolkit for all things biomolecules and trained RF3 with it. All open-source, test it via `pip install atomworks`! AtomWorks: github.com/RosettaCommo... RF3: github.com/RosettaCommo... Paper: tinyurl.com/y2w4z65b 1/6

RosettaFold 3 is here! 🧬🚀 AtomWorks (the foundational data pipeline powering it) is perhaps the really most exciting part of this release! Congratulations @simonmathis.bsky.social and team!!! ❤️ bioRxiv preprint: www.biorxiv.org/content/10.1...

(1/7) Training biomolecular foundation models shouldn't be so hard. And open-source structure prediction is important. So today we're releasing two software packages: AtomWorks and RosettaFold3 (RF3) [https://www.biorxiv.org/content/10.1101/2025.08.14.670328v2](www.biorxiv.org/content/10.1...)

Accelerating Biomolecular Modeling with AtomWorks and RF3

Deep learning methods trained on protein structure databases have revolutionized biomolecular structure prediction, but developing and training new models remains a considerable challenge. To facilita...

biorxiv.org

Very excited about our latest all-atom generative model proteina, check out the project page (research.nvidia.com/labs/genair/...) and stay tuned for the code release soon!

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching

research.nvidia.com

Kevin K. Yang 楊凱筌@kevinkaichuang.bsky.social · last yr.

Partially-latent flow matching enables sequence-structure codesign of large proteins and functional motif scaffolding. @kdidi.bsky.social @machine.learning.bio @karstenkreis.bsky.social @arashv.bsky.social arxiv.org/html/2507.09...

Excited to present my first paper officially as a PhD student now as an ICLR Oral this week! Super fun work with the GenAIR team at NVIDIA. Talk: Fr 10:54 - 11:06 (Oral Session 3B, Garnet 213-215) Poster: Fr 15:00-17:30 (Hall 3 + Hall 2B #5) Come by the poster/reach out to chat

Such a fun project to work on with a stellar team! Stay tuned for other things to come here, and see you all in Singapore!

Karsten Kreis@karstenkreis.bsky.social · last yr.

📢📢 "Proteina: Scaling Flow-based Protein Structure Generative Models" #ICLR2025 (Oral Presentation) 🔥 Project page: research.nvidia.com/labs/genair/... 📜 Paper: arxiv.org/abs/2503.00710 🛠️ Code and weights: github.com/NVIDIA-Digit... 🧵Details in thread... (1/n)

Yet another story of issues with benchmarks and evaluations in ML4bio + a much stronger and fair benchmark #bioMLeval

@briantrippe.bsky.social · last yr.

🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods in motif scaffolding. Why does this matter? Reproducibility & fair comparison have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/Moti... A thread ⬇️

Have a look at our shiny new benchmark for motif-scaffolding in computational protein design! New (and harder) tasks, including a reproducible evaluation pipeline

@briantrippe.bsky.social · last yr.

🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods in motif scaffolding. Why does this matter? Reproducibility & fair comparison have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/Moti... A thread ⬇️

This! Also well put in this editorial in PLOS Comp Biol: Putting benchmarks in their rightful place: The heart of computational biology doi.org/10.1371/jour...

Joe Greener@jgreener64.bsky.social · 2y ago

I have a lot of time for benchmarking studies that don't try to sell a new method as well, it increases the credibility of the results. The thought of installing 55 pieces of bioinformatics software fills me with dread. (3/4)

Our paper on computational design of chemically induced protein interactions is out in @natureportfolio.bsky.social. Big thanks to all co-authors, especially Anthony Marchand, Stephen Buckley and Bruno Correia! t.co/vtYlhi8aQm

After two years, our paper on generative models for structure-based drug design is finally out in @natcomputsci.bsky.social www.nature.com/articles/s43...

Structure-based drug design with equivariant diffusion models - Nature Computational Science

This work applies diffusion models to conditional molecule generation and shows how they can be used to tackle various structure-based drug design problems

nature.com

Thanks Jascha 🫶 We’re working hard to create sustainable funding mechanisms for open source scientific tooling - understanding the challenge landscape is a key first step!

Jascha Achterberg@achterbrain.bsky.social · 2y ago

Rory @rory.bio is working on a large project to accelerate science 🧪 through high-quality & open-source software. To steer the project it would be amazing to hear from scientists across fields about problems in the scientific process *you* want to see solved! Tell Rory here flywhl-ideas.notion.site

Love PyMOL Remote, one of these tools that does one thing and does it well!

Simon Mathis@simonmathis.bsky.social · 2y ago

For some more guidance on how to use this, Martin Buttenschön wrote a nice blogpost: www.blopig.com/blog/2024/11...

This should go chiral

estella newcombe@estellaan.bsky.social · 2y ago

We did this crazy project where we tried to see if proteins could interact with their mirror image ligand. Seems impossible when proteins need to form 3D structures to interact. But what about if the interaction remains disordered??? www.nature.com/articles/s41...

MSAs go brrr with MMseqs2-GPU! Super fun project, happy to work with and learn from a stellar team of engineers and scientists. Try it out and stay tuned! 📄 Preprint: www.biorxiv.org/content/10.1... 💾 Code: mmseqs.com 🗞️ Blog: developer.nvidia.com/blog/boost-a...

GitHub - soedinglab/MMseqs2: MMseqs2: ultra fast and sensitive search and clustering suite

MMseqs2: ultra fast and sensitive search and clustering suite - soedinglab/MMseqs2

mmseqs.com

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · 2y ago

New GPU-based MMseqs2: 20x faster searches on a single L40S (approx. as fast as a RTX 4090) vs. a 128-core CPU. This work enables to set up a very cost-efficient ColabFold MSA GPU server. 🧵🧵 📄 www.biorxiv.org/content/10.1... 💾 mmseqs.com 🗞️ developer.nvidia.com/blog/boost-a...