Frances H. Arnold

Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo

Design-Evolution Synergy Enables New-to-Nature Enzyme Chemistry

Directed evolution and machine-learning-assisted evolution have transformed biocatalysis by enabling rapid optimisation of catalytic performance within compatible protein scaffolds. In parallel, advances in deep-learning-driven de novo protein design have expanded accessible protein architectural space, enabling the ge...

Chiral oxazolidinones via biocatalytic aziridination of unactivated alkenes.

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.

Protein engineering: status report

Protein engineering appears to be entering a golden age, defined by a rapidly accelerating pace of progress, even as significant challenges in design, screening, and real-world application remain.

Machine Learning-Assisted Evolution of Broadly Functional Enzyme Libraries

Results indicate that supervised machine learning can help guide the construction of high-value enzyme libraries with expanded catalytic scope, and suggest that supervised machine learning can help guide the construction of high-value enzyme libraries with expanded catalytic scope.