Squidly enables efficient identification of enzyme catalytic residues by integrating functional hierarchies into a contrastive learning framework, requiring only protein sequences to produce scalable predictions across the known enzyme landscape.
An in vivo small-molecule drug screen in developing zebrafish larvae identifies dozens of unique chemical modulators capable of reducing atherogenic apolipoprotein B levels.
