AI Breakthroughs
REAP's robots and rank loss push enzyme activity up to 104-fold
By Arjun
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12 Aug 12:06 AM
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Via Nature Communications
Tianjin University researchers describe REAP in Nature Communications: a closed-loop enzyme platform that pairs robots with RankReg, a hybrid loss optimizing ranking and numeric fit from sparse lab feedback. It hunts catalytic and distal mutation hotspots, then expands from single edits to combinatorial variants. On cytochrome P450 BM3 it delivered a 57-fold activity gain in five cycles, and on Staphylococcus aureus Sortase A up to 104-fold. Why it matters: ranking-aware active learning may make AI biocatalyst campaigns repeatable outside specialist labs. Caveat: authors filed Chinese patents on the system, and generality beyond these enzymes is unproven.
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