Author

Ariane Mora

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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

Open access Jul 2026

Discovery of a phenazine–thiol conjugase from sparse data using genome-informed machine learning

It is shown that integrating genome-informed data augmentation with contrastive learning in protein language space enables identification of phenazine-interacting proteins starting from only 14 known phenazine modifying sequences, and coupling comparative genomics with protein machine learning can convert “small data”...

Xiaoyu Shan, I. Trindade, N. Glasser et al. · Proceedings of the National... · 0 citations