Author

W. J. Rieger

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Open access Sep 2026

Reframing enzyme function prediction as conditional generation

Fluxion is presented, a generative deep learning framework that learns enzyme-dependent regioselectivity across cytochrome P450 enzymes by modeling dynamic electron flow trajectories across the enzyme’s catalytic residues by combining both synthetic chemistry and biochemical datasets with protein language model represe...

W. J. Rieger, Sebastian Häussermann, Luca C. Herrmann et al. · bioRxiv · 0 citations

Open access Sep 2026

Squidly harnesses enzyme functional hierarchy and contrastive learning to efficiently predict catalytic residues from sequence

Squidly surpasses state-of-the-art ML annotation methods in catalytic residue prediction while remaining sufficiently fast to enable wide-scale screening of databases.

W. J. Rieger, Mikael Bodén, Frances H. Arnold et al. · eLife · 0 citations