Design protein binders for a scorpion neurotoxin

A finance research firm asked Anthropic whether non-experts could tackle a health problem. A research model ran for 64 hours on four prompts, generated 318,484 protein designs, and 17 of the 211 lab-tested ones bound.

Done withClaude· Nov 1, 2026 · 3 accounts

What they did

Citrini Research, an investment research firm with no biology background, approached Anthropic with a question: could Claude help motivated non-experts make progress on a real health problem. They settled on scorpion neurotoxins, on the idea that a protein that binds the toxin could one day lead to an antivenom. Per Anthropic's write-up, an internal research model then worked mostly on its own for 64 hours with four follow-up prompts from the team. It generated 318,484 candidate protein designs and selected 180 for the lab. The team added 31 more with Claude's help, and Adaptyv Bio and Twist Bioscience synthesised and tested all 211.

How it went

Seventeen of the 211 designs met Anthropic's criteria for a binder, and the two strongest bind tightly to Cn2, a toxin from a Mexican scorpion. Anthropic says it has not shown that any of them neutralise venom in a cellular environment and does not claim to have made an antivenom. All 211 designs and the data are being released. The write-up does not split the 17 hits between the model's own 180 and the 31 the team added, which a commenter on the thread asked for and the poster could not find either.

Worth knowing

The account comes from the vendor, and the firm that commissioned it sells investment research on AI, so read the framing with that in mind. The Verge spoke to outside scientists who said the result is a set of starting points and nothing close to a drug. Binding is not neutralising: the test that matters has not been run. Commenters also noted the wet lab, not the model, was the bottleneck, and that the token spend behind 318,484 designs is not something a hobbyist reproduces.

Try it

With Claude· 4 parts to fill in

I want to screen candidate [binder or inhibitor] designs against [target protein, with its sequence or PDB id]. Work from the published structures and literature on that target. Propose a design strategy first and wait for my go-ahead. Then generate candidates in batches, score them with [the structure prediction or docking tool I have], and shortlist at most [number] for synthesis, with the reason each one made the list and the confidence you have in it. State plainly what your scores do not tell us, and which wet-lab test would be the first real check.

Square brackets are the parts to fill in. The prompt is ours; the story is theirs.

Where they said it

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