De novo design of luciferases using deep learning.

ABSTRACT: De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds^1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence-structure relationships. Here we describe a deep-learning-based 'family-wide hallucination' approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine³ and 2-deoxycoelenterazine. The designed active sites position an argin

SUBMITTER: Yeh AH 

PROVIDER: S-EPMC9946828 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature