Frances Arnold's Lab Uses Machine Learning to Engineer Broadly Functional Enzymes
KevinKaichuang · x · 2026-08-11
A new paper from Frances Arnold's lab at Caltech published on bioRxiv introduces a machine learning-assisted approach to design enzyme libraries with broad substrate scope.
The method aims to overcome natural catalytic limitations by using algorithmic prediction and screening to efficiently generate biocatalysts capable of processing non-native substrates, offering a new tool for sustainable chemical synthesis.
Related event: Frances Arnold Team Introduces ML-Assisted Enzyme Design Method(2 posts)→
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