Paper: AI agents learn protein function through autonomous experimental interaction
KevinKaichuang · x · 2026-08-21
This paper presents a framework where AI acquires knowledge by acting directly on biological systems. Autonomous agents design protein variants, construct and characterize them in a robotic lab, and learn from the feedback. Running continuously for a month without human intervention, the agents applied to glycoside hydrolases discovered enzymes with altered substrate specificity and learned the structure of the sequence space.
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