Simplifying protein engineering with deep learning

Abstract

When it comes to deep learning for protein engineering, there is strength in simplicity. In this issue of Cell, through thoughtful deployment of existing fixed-backbone sequence design models, Caixia Gao and colleagues engineer diverse genome editing systems with improved functionality, enabling powerful capabilities in fine-grained and large-scale genome editing as demonstrated through strong experimental validation.