Anthropic 测试 Claude 从零自主设计蛋白质结合体，基于一份人类专家撰写的蛋白设计提示词，针对 15 个靶点中的 14 个完成设计，命中率约 27%。Adaptyv Bio 与 Twist Bioscience 独立构建并测试后确认 1320 个设计中有 354 个成功结合。不同设置下命中率在 22.6% 到 35.1% 之间，排名最高的设计在 49% 的实验轮次中成功结合。
材料给出 Claude 自主蛋白质结合体设计的命中率数字，可与该领域人类主导流程的典型水平直接对比。
This is interesting: Claude is already achieving roughly twice the protein-design hit rate of conventional human-led workflows. 27% hit rate in autonomous protein binder design, roughly twice the typical 10–15% rate reported in the field.
Working from one expert-written protocol, Claude designed binders against 14 of 15 measurable targets. Independent labs confirmed that 354 of 1,320 designs bound successfully.
Depending on the setup, Claude’s hit rate ranged from 22.6% to 35.1%. Its top-ranked design bound in 49% of campaigns.
This is not yet fully autonomous drug research, but it is another important building block in that direction.
Many drugs work by binding to a specific target in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per target, sifting through a large number of candidates to identify the few that work. We wanted to test if Claude could successfully design novel protein binders from scratch (also called de novo design). With a protein design prompt written by a human expert, Claude autonomously designed protein binders against 14 out of 15 targets. We then worked with Adaptyv Bio and Twist Bioscience, who independently built and tested the proteins Claude designed.在 X 查看被引用的帖子
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