Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo
Year: 2026
Type: preprint
Abstract: Creating highly active enzymes for arbitrary reactions is a transformative goal for the molecular sciences 1 . Traditional protein engineering 2,3 is constrained by a reliance on existing natural starting points, which are often challenging to discover. De novo design offers the potential to overcome this by creating enzymes from first principles 4 , but has yet to achieve practically relevant catalytic properties. Here we present AlphaProtein Novo (AP Novo), a machine-learning pipeline that demonstrates, for the first time, that de novo enzyme design can outperform natural sequence mining in addressing challenging chemistry. We used AP Novo to design new-to-nature nitrene transferases to synthesise the pharmacophore piperidine with unprecedented product selectivity, and to create enzymes that degrade the environmental toxin DEHP under conditions that denature natural enzymes. We also obtained state-of-the-art catalytic efficiencies on two well-studied model reactions, and through iterative design and analysis found that key enablers of success were mechanism-inspired metrics based on AlphaFold 3 5 predictions and sequence-ensemble-based scoring of designed backbones. Our results show that de novo design has become a powerful complement to natural enzyme diversity for discovering catalysts for a range of applications.
Authors: Zachary Wu, Josh Abramson, Thomas Frerix, Alexander E. Chu, Ruijie K. Zhang, Luca Schulz, Amy E. Danson, Tristan O. C. Kwan, Li Kevin Wenliang, Jacob Kelly, Zi-Qi Li, Rosalia G. Schneider, Ashok Thillaisundaram, Harshnira Patani, Vinicius F. Zambaldi, Sukhdeep Singh, David La, Masy Domecillo, Ariane N. Mora, Julia C. Reisenbauer, Yu Zhang, Eliseo Papa, Akvilė Žemgulytė, Yu-Han Wu, Augustin Žídek, Jiaxin Shi, Grace Margand, Naila Assem, Kate Stephen, Charlie Emrich, Peng Liu, Lucy Colwell, Demis Hassabis, Rob Fergus, Frances H. Arnold, Pushmeet Kohli, Jue Wang
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funder: Francis Crick Institute
OpenAlex ID: W7220469987