Can we program a kinase like a switch? Inspired by natural autoinhibitory complexes, we designed miniproteins against active- and inactive-like conformations of Focal Adhesion Kinase. Depending on the targeted state, the resulting binders either activated or inhibited the kinase.

Today, in collaboration with Anthropic, we’re excited to share rapid initial progress towards an antibody treatment for food allergy, which affects over 200 million people worldwide, discovered with the help of Claude.

At Divergence Labs, we believe that AI can unlock the next therapeutics with more effective mechanisms than before. Such mechanisms are urgently needed in food allergy, which involve overcoming one of the tightest affinity protein pairs in immunology, IgE and its receptor FcεRI, on mast cells.

Treatment with Xolair—the only approved antibody for food allergy—sequesters circulating IgE, but mast cells remain sensitized for weeks to months due to the extraordinarily slow dissociation of IgE from FcεRI.

We envision a treatment that actively pulls IgE off of FcεRI, without waiting for natural dissociation. Like picking a lock, this requires the right combination of geometry and force.

Our research team, working with Claude, ideated on mechanisms to accomplish this disruption, and converged on an antibody format with two arms with different functions and epitopes. Within one month, we designed, synthesized, and experimentally confirmed the biophysical function of the two arms, which we are now assembling into full therapeutic formats.

RFD4-Proteina now runs on @tenstorrent in TT-Bio. The highest throughput, at by far the lowest cost.

Huge thanks to @kinasekid from the Baker Lab. He brought it up on Tenstorrent on day 0.

Live on Japanfold right now for anyone, at super high throughput and low cost.

Thanks to a for releasing it openly.

We're not affected by the HBM shortage. Our hardware is available with almost no wait time at any scale.

Driving down cost and making these models available to everyone feels good.

Tenstorrent is gonna be the default hardware for bio.

At @Xaira_Thera we are closing the loop.

SOTA models for molecular design and biological understanding (X-Design and X-Cell) allow us to design functional molecules for undruggable targets at unprecedented scale, and to increase our ability to decipher complex disease biology. sive data generation efforts in the "X-Lab" fill in the gaps in public data and allow us to ask questions that haven't been asked before, which in turn makes the models themselves, and the harness in which we run them, even better.

Today, I wanted to share my thoughts on two tool layers we're building to accelerate these efforts.

The first tool is a software layer. X-Scientist is a self improving agent harness compatible with many frontier LLMs (including recent Claude models from @AnthropicAI and GPT Astra from @OpenAI). This harness achieves SOTA performance on a number of tasks relevant to our design and data generation efforts, and allows humans to extend their reach to larger experiments and accelerate artisanal data analysis and design pipelines, including large-scale protein design campaigns.

The second tool is a hardware layer that integrates natively with our software stack. X-Automate is a robotics ecosystem that powers the X-Lab. X-Automate combines X-Bots (robots which work alongside human scientists in the wetlab), and X-Scientist, to coordinate workflows and monitor activities. We demonstrate X-Automate in a use case where it helps to bridge the gap between walk-up automation and analytical biochemistry, empowering scientist to hand off routine activities like sample loading.

Both of these two tool layers are truly in their infancy and I expect they may be able to contribute substantially to our goal of bringing 10x more medicine to 10x more patients in the next 10 years.

xaira.com/news/x-automat…

xaira.com/news/x-scienti…

Check out this awesome work by Will 🙌

Always great to talk intracellular binders with you. So glad we got to work together on this, and grateful to have you as a friend in the lab!

🥳 Steffen is the best! 🙌 Check out this awesome work by Long Tran, Steffen and the team!

science.org/doi/10.1126/sc…

💥 Introducing Warp Sciences, a new company applying AI and robotics to help the world develop new medicines faster.

We’ve raised a $215M Series A led by @lightspeedvp to bring frontier AI out of the browser and into the lab, and build scientific capacity here in America.

I co-founded Warp with my long-time friend @dpatil, FAIR co-founder @manohar_paluri, and drug hunter Sol Reisberg. The early team is full of incredible people like @bkspears9, who helped achieve Q>1 fusion at LLNL.

Meet X-Scientist: our step toward a self-improving virtual drug hunter!

Today, we’re introducing Xaira’s agentic AI platform for drug discovery:

🧠 Beats Codex using the same Astra model by 7.4 percentage points on DrugDiscoveryBench.

🧬 Nominates targets ~10× faster than comparable wet-lab hit rate.

🔁 Conducts autonomous research, outperforming AutoResearch and AutoScientists in the PerturbQA benchmark.

Here’s what we built, what we tested, and where we’re going. 🧵

One of the kindest and most thoughtful scientists I had the pleasure of working with. PTMs everywhere watch out, @kinasekid is coming for you!

Protein design doesn’t have to stop at the canonical 20 amino acids! After our work on phosphotyrosine binders, RFD4-Proteina adds phosphoserine and phosphothreonine (below) to the repertoire, with binders that distinguish adjacent H3pS10 and H3pT11 sites in the histone H3 tail!

And a huge thank you to @nscorley, @DidiKieran, @maxkazman and @RafiBrent 😊 So much fun working on this together! Finally pY, pS and pT covered!!!

Huge thanks to @bradyajohnston for #MolecularNodes! Such a fantastic tool for bringing our protein designs to life and making the science easier to share. Super visionary to build it! 🙌

My little Blender plugin I started 4.5 years ago is literally the face of an entire Biotech industry / research sector 🥹

#b3d #GeometryNodes #MolecularNodes

Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org

Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30

Dear god it's inventing German from first principles

Today we are excited to release Artios, a fully open source system for designing functional de novo enzymes.

Enzymes present a new frontier for de novo protein design models due to the challenge of coordinating precise chemistry, rather than binding a target.

Enzymes are life’s by designing them we can truly start to engineer biology.

We believe these fundamental capabilities should be built in the open and shared with the community to progress science faster.

🧵 1/6

We’ve acquired Orchestra Bio, a platform that helps biopharma teams coordinate the complex process of drug development.

Together, we’ll build on Rosalind, our AI models and tools for life sciences research, to streamline those operations and help new treatments reach patients sooner.

Welcome @ashokaraj_ and team!

openai.com/index/openai-t…

New on our Science Blog: designing protein binders against scorpion neurotoxins.

Scorpions sting about 1.2m people every year, and antivenoms are often costly or in short supply. Claude has made an early step toward finding new treatments.

anthropic.com/research/claud…

Public preview of BioEmu2! @MSFTResearch AI for Science’s new foundation model for biomolecular structure, dynamics and function. Open weights, MIT license.
github.com/microsoft/bioe…

Movie: BioEmu2-simulated binding of intrinsically disordered peptide PUMA to MCL-1 receptor. 🧵⬇️

Excited to share what we’ve been building with Chaperone!

In our benchmark, Chaperone reduced token usage by 86%. We also went from hypothesis to sequences ready for wet-lab testing in just two weeks—yielding a 1.32 nM cortisol binder in the first experimental round!

This paper has excellent experiments and pretty mixed α/β folds (6 crystal structures..!) Also proteases are very useful research tools. Great stuff. Congrats @kinasekid and coauthors!