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Bibliographic Details
Main Authors: Rector-Brooks, Jarrid, Lambert, Théophile, Skreta, Marta, Roth, Daniel, Long, Yueming, Li, Zi-Qi, Zhang, Xi, Cretu, Miruna, Li, Francesca-Zhoufan, Ganapathy, Tanvi, Jin, Emily, Bose, Avishek Joey, Yang, Jason, Neklyudov, Kirill, Bengio, Yoshua, Tong, Alexander, Arnold, Frances H., Liu, Cheng-Hao
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.05181
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Table of Contents:
  • Evolution is an extraordinary engine for enzymatic diversity, yet the chemistry it has explored remains a narrow slice of what DNA can encode. Deep generative models can design new proteins that bind ligands, but none have created enzymes without pre-specifying catalytic residues. We introduce DISCO (DIffusion for Sequence-structure CO-design), a multimodal model that co-designs protein sequence and 3D structure around arbitrary biomolecules, as well as inference-time scaling methods that optimize objectives across both modalities. Conditioned solely on reactive intermediates, DISCO designs diverse heme enzymes with novel active-site geometries. These enzymes catalyze new-to-nature carbene-transfer reactions, including alkene cyclopropanation, spirocyclopropanation, B-H, and C(sp$^3$)-H insertions, with high activities exceeding those of engineered enzymes. Random mutagenesis of a selected design further confirmed that enzyme activity can be improved through directed evolution. By providing a scalable route to evolvable enzymes, DISCO broadens the potential scope of genetically encodable transformations. Code is available at https://github.com/DISCO-design/DISCO.