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Anthropic

Claude designed proteins against 15 targets and hit 14

AnthropicScience

Anthropic published results from a lab, not a simulation. External evaluators produced and tested the model's designs. The share that worked is between 22 and 35 percent, against a usual 10 to 15.

In short
  • Claude designed small proteins against 15 targets and succeeded against 14 of them.
  • The designs were produced and tested by external labs, not scored on a computer.
  • On chemical analysis, another model did work that needs a specialist in 23 and 19 minutes.
Checked on19 August 2026Responsible editorTsvetelin IvanovHow we workMethod · Corrections

The number I am watching is not 14 out of 15. It is the share of designs that worked: between 22 and 35 percent, against a usual 10 to 15.

That is where it sits, because the first number tells you whether it works at all, and the second tells you how much work you throw away.

And the important part: this is not a score from a computer. The designs went out to external labs, were manufactured and were physically tested.

The facts: per Anthropic, published on 18 August 2026, Claude models (Opus 4.8 and Mythos Preview) designed small binding proteins against 15 targets and succeeded against 14. External evaluators Adaptyv Bio and Twist Bioscience independently produced and tested the designs. Working against all targets at once, the hit rate is 26.7 percent for Mythos Preview and 22.6 for Opus 4.8; working one target at a time it rises to 35.1. The typical figure today is 10 to 15 percent. Against at least four targets the result matches or exceeds the best published so far. Up to 12,500 NVIDIA H100 hours were used for a 48-hour session. In the second experiment Claude Opus 5 was given raw files from a lab and a two-sentence prompt, and returned finished analysis in 23 and 19 minutes, matching the lab on purity (96.4 versus 96.33 percent).

Where the caveat is

The numbers are Anthropic's, and the targets are well known ones used in design competitions. Two were picked as new on purpose, so they would not have been seen during training. That is an honest move, but the check is still theirs.

The other thing they say plainly: life science tasks are blocked in their most capable model, and access for scientists is still being prepared. So they are publishing a result from a tool you cannot touch.

The time being cut is not thinking time. What falls away is the time spent arranging instruments.

The second experiment tells me more than the first. A chemist gets raw data from a lab and has to read it. Specialist work, dull and slow. The model did it in about twenty minutes from two lines of instruction, with the same answer.

That is the shape in which these things actually enter work. Not a brilliant discovery, but waiting time removed from the middle of a process.

If you are in a trade where you wait on a specialist for something routine, the next two years will be interesting for you.

The visual is generated code art. No third-party images.
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Official primary sources
→Anthropic: How Claude is accelerating protein design and analytical chemistry (18.08.2026)
Original: https://wearecoded.com/en/articles/anthropic-claude-proektira-belci.html
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