This webinar, brought to you by Twist Bioscience, will be hosted live and available on-demand.
Tuesday, June 30th, 2026
11:00 AM - 12:30 PM ET
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.
In this webinar, Chenghao Liu and Jarrid Brooks from the Arnold Lab at Caltech will introduce DISCO (DIffusion for Sequence-structure CO-design). This multimodal model 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.
Topics to be covered
- Multimodal approaches to protein sequence and structure co-design
- Generative AI methods for enzyme engineering
- Design of heme enzymes with novel catalytic geometries
- Experimental validation of new-to-nature carbene-transfer reactions
- Integration of directed evolution with AI-designed enzymes
- Applications of generative models in biocatalysis and protein engineering
 | Chenghao Liu |
.png "Jarrid Rector-Brooks") | Jarrid Rector-Brooks |
