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Claude Designed 17 Scorpion Antivenom Binders in 64 Hours

At a glanceQuick answers
What did Claude actually do?
It chose the target sites on five scorpion toxins, set its own scoring thresholds, generated 318,484 candidate proteins with 12 design tools, and picked 180 to send to two labs for testing.
Did it work?
Partly. 17 of 211 tested designs bound their toxin tightly enough to meet Anthropic’s criteria, a hit rate in line with normal protein design campaigns. No design bound two toxins.
Is this an antivenom?
No. Anthropic says it has not tested whether any design neutralizes venom in cells or protects animals, so it makes no antivenom claim.
Data illustration on a near-white ground: a funnel narrowing from a dense field of small protein shapes to a few highlighted ones, under the figures 318,484 designs, 211 tested and 17 bound
Fig 0Hundreds of thousands designed, 211 tested, 17 bound. Made by CellCog's image agent, running GPT Image 2.5.

Anthropic gave Claude a prompt and four follow-ups, and 64 hours later it had designed 180 candidate proteins aimed at scorpion neurotoxins. Two labs tested 211 designs; 17 of them bound. The write-up went up at 13:01 UTC on October 20, 2026, with a 69-page technical report and all 211 designs released as data.

The honest headline is in Anthropic’s own sentence: “We have not confirmed whether these binders neutralize scorpion venom in a cellular environment, so we do not claim to have produced an antivenom.” What the run does show is how much of a design campaign an agent now runs on its own.

On this page · 8 sectionsOpen
  1. What Claude ran
  2. What the labs found
  3. The part that failed
  4. Why scorpions
  5. What is not proven
  6. Where CellCog stands
  7. What we are watching for
  8. Sources
Key points5 · 6 min full read
  1. A scorpion outline beside a protein shape.
    Anthropic published the results on October 20, 2026: it asked an internal Claude research model to design protein binders against five scorpion neurotoxins.
  2. A funnel narrowing from many shapes to a few.
    Claude generated 318,484 designs and screened 553,052 design-toxin pairs, then produced its final list of 180 designs 64 hours after the first prompt, with four follow-ups.
  3. A lab flask with a check mark.
    Adaptyv Bio and Twist Bioscience lab-tested 211 designs. 17 met Anthropic’s binding criteria: seven against Cn2, four each against AaH II and AaH I, two against LqhIII, none against Ts1.
  4. Three targets with one crossed out.
    None of the 151 designs aimed at more than one toxin bound more than one, so the cheap universal cocktail Anthropic was testing for did not come out of this run.
  5. An open folder of data with a caution mark.
    Anthropic does not claim an antivenom: nothing was tested in cells or animals, and all 211 designs and their data are released publicly.

§ 01What Claude ran

The target was five sodium-channel toxins from four regions: Cn2 (Mexico), Ts1 (Brazil), AaH I and AaH II (North Africa) and LqhIII (the Middle East). Claude picked the toxin structures from the Protein Data Bank and the AlphaFold database, chose five hotspot positions on each, set the quality thresholds a design had to clear, and decided how much to lean on each design tool.

Step Number
Designs generated with 12 design tools 318,484
Design-toxin pairs screened 553,052
Pairs ranked with at least five seeds 28,451
Designs Claude selected for testing 180
Designs added later by the team, with Claude’s help 31
Designs lab-tested 211
Designs meeting the binding criteria 17
Table 1Claude’s design campaign, end to end (Anthropic technical report, October 20, 2026)
Animation: a funnel filled with hundreds of protein shapes narrows through 553,052 pairs screened and 28,451 ranked to a box of 180 selected plus 31 added, into two lab dishes and a final amber box holding 17 dots
Fig 1318,484 designs narrowed to 180 sent to two labs, and 17 that met the criteria

The campaign used on the order of 10,000 H100 GPU hours, which Anthropic concedes is “much more than most researchers have access to.” A footnote adds the more interesting number for everyone else: with faster models and “a simplified prompt using a single agent and a single GPU over 24 hours,” Claude reached comparable in-silico scores.

§ 02What the labs found

Adaptyv Bio made the proteins in a cell-free system; Twist Bioscience made them in human kidney cells as antibody-stem fusions. Both measured binding by surface plasmon resonance. A design counted as a binder only if it was a hit at both labs in every replicate, every dissociation constant was 1 micromolar or tighter, and it showed no signal against CLEC12A, an unrelated human protein used to catch stickiness.

Designs that met the binding criteria, by toxin, of 211 tested in two labsBar chart of binders per toxin: Cn2 seven, AaH II four, AaH I four, LqhIII two, Ts1 zero, with Cn2 highlightedCn27AaH II4AaH I4LqhIII2Ts10Designs that met the binding criteria, by toxin, of 211 tested in two labsBar chart of binders per toxin: Cn2 seven, AaH II four, AaH I four, LqhIII two, Ts1 zero, with Cn2 highlightedCn27AaH II4AaH I4LqhIII2Ts10
Fig 2Designs that met the binding criteria, by toxin, of 211 tested in two labs

Among the 60 designs aimed at a single toxin, 11 bound, an 18% hit rate that Anthropic calls “consistent with typical protein design campaigns, including our previous work.”

Animation: five toxin cards fill with their binder counts, seven for Cn2, four for AaH II, four for AaH I, two for LqhIII and none for Ts1, above a grey band reading 151 designs aimed at more than one toxin, 0 bound two
Fig 3Seven binders against Cn2, none against Ts1, and none at all across two toxins

The two strongest, Cn2-B1 and Cn2-B2, bound at single-digit nanomolar affinity and competed with LR, an antibody fragment reported to neutralize Cn2 in mice, which suggests they land on the same part of the toxin that grabs the sodium channel.

§ 03The part that failed

The commercially interesting goal was one protein that neutralizes several toxins at once, because that is what a cheap universal cocktail would need. It did not happen.

Design group Designs Binders
Single toxin 60 11 (18%)
Two beta-family toxins 30 part of 5 across both groups (8%)
Three alpha-family toxins 30 part of 5 across both groups (8%)
All five toxins 91 1
Table 2Multitoxin designs: hit rate falls as targets are added (Anthropic technical report)

“None of the 151 multi-toxin designs met the criteria for binding against more than one toxin.” Anthropic lists the candidate explanations without picking one: its own prompting, the limits of the design tools, or whether multitoxin design is biologically feasible at all.

§ 04Why scorpions

Scorpions sting more than 1.2 million people a year and kill more than 3,250, mostly children with limited access to care. Today’s antivenoms are made by milking venom from live scorpions, immunizing horses and purifying their antibodies, a process that takes months and produces a product that is costly and often in short supply. Citrini Research, the investment research firm that proposed the project, notes that scorpion venom runs at $39 million per gallon.

That is the case for de novo binders: designed from scratch, optimized for stability, and manufacturable without animals. It is also why the gap between a binder and a drug matters so much here.

§ 05What is not proven

Anthropic is specific about the distance left. The results show binding only against recombinant toxins grown from genes, not toxin purified from venom. Nothing was tested in cells by patch-clamp recording to show it stops the toxin acting on the channel, and nothing was tested in mice. Two outside experts, Susana Vazquez Torres and Timothy P. Jenkins, called it a promising first step while naming the same limit; as Vazquez Torres puts it, “binding itself is no longer the main bottleneck.”

§ 06Where CellCog stands

CellCog does not do drug discovery; every CellCog agent tier runs on Claude Opus 5.5. We follow runs like this because a 64-hour autonomous campaign with its own thresholds and tool choices is the same shape of work our customers hand their AI employees, at a far higher stake.

§ 07What we are watching for

  • Whether Cn2-B1 is tested against toxin purified from venom, then in patch-clamp recordings and mice.
  • Whether other groups find multitoxin binders where this campaign did not.
  • How quickly the single-GPU, 24-hour version Anthropic footnotes reaches ordinary labs.

§ 08Sources

Frequently asked6 questions

Q1When was this published?

Anthropic posted the research write-up at 13:01 UTC on October 20, 2026, with a 69-page technical report and a public dataset.

Q2How long did the design campaign take?

Claude produced its final list of 180 designs 64 hours after the initial prompt, working mainly autonomously with four follow-ups from the team, on the order of 10,000 H100 GPU hours.

Q3How strong are the best binders?

The two strongest, Cn2-B1 and Cn2-B2, bound the Mexican scorpion toxin Cn2 at single-digit nanomolar affinity at both labs, and competed with LR, an antibody reported to neutralize Cn2 in mice.

Q4Why does a multitoxin binder matter?

One molecule that neutralizes several toxins would cut the size of a universal antivenom cocktail. The five toxins share a fold but are only 26% to 62% identical in sequence, and none of the 151 multitoxin designs worked.

Q5Who ran the lab work?

Adaptyv Bio tested the designs in a cell-free system and Twist Bioscience in human kidney cells, both measuring binding by surface plasmon resonance. The project was developed with Citrini Research.

Q6Does CellCog do drug discovery?

No. Every CellCog agent tier runs on Claude Opus 5.5. We cover campaigns like this because they show what long autonomous runs by an agent produce, and how carefully the claims have to be read.

Published 20 October 2026 All Trust, permissions & security →