arxiv:2604.05181

General Multimodal Protein Design Enables DNA-Encoding of Chemistry

Published on Apr 6

· Submitted by

Jarrid Rector-Brooks on Apr 8

DISCO

Upvote

Authors:

Jarrid Rector-Brooks ,

Théophile Lambert ,

Marta Skreta ,

Alexander Tong ,

Cheng-Hao Liu

Abstract

DISCO is a multimodal deep generative model that co-designs protein sequences and 3D structures to create novel heme enzymes with unprecedented catalytic capabilities.

AI-generated summary

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.

View arXiv page View PDF Project page GitHub 46 Add to collection

Community

jarridrb

Paper author Paper submitter about 19 hours ago

DISCO (DIffusion for Sequence-structure CO-design) is a multimodal generative model that simultaneously co-designs protein sequences and 3D structures, conditioned on and co-folded with arbitrary biomolecules — including small-molecule ligands, DNA, and RNA. Unlike sequential pipelines that first generate a backbone and then apply inverse folding, DISCO generates both modalities jointly, enabling sequence-based objectives to inform structure generation and vice versa.

DISCO achieves state-of-the-art in silico performance in generating binders for diverse biomolecular targets with fine-grained property control, performing best on 178/179 evaluated ligands, as well as DNA and RNA. Applied to new-to-nature catalysis, DISCO was conditioned solely on reactive intermediates — without pre-specifying catalytic residues or relying on template scaffolds — to design 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(sp³)–H insertions, with top activities exceeding those of engineered enzymes. Random mutagenesis of a selected design further yielded a fourfold activity gain, indicating that the designed enzymes are evolvable.