Data-efficient distal engineering of fluorinase using zero-shot models

ABSTRACT

The paper presents a computational workflow, PRIZM, that uses zero-shot AI models to engineer fluorinases with enhanced catalytic efficiency. By targeting distal sites identified through the zero-shot predictions, the authors successfully identified activity-enhancing mutations with minimal experimental data. This approach demonstrates a way to engineer complex enzymes that are traditionally resistant to active site modification.