Design of Novel Repeat Proteins Containing Beta Strands

Abstract

Repeat protein design is a natural direction for protein bioengineering thanks to inherent adaptability, geometric properties, and facile extensibility. Natural systems use repeat proteins as materials scaffolds, sensors, polymer binders, and functional superstructures. Protein engineers have both co-opted and adapted natural systems as well as created novel systems inspired by nature to serve new purposes. New deep learning approaches in both scaffold and sequence design have enabled significantly less constrained design approaches with greater success rates in designing soluble, stable biomolecules. This work presents a greatly expanded methodology for repeat protein design architectures. As particular examples, closed and unclosed repeat proteins with both alpha-helical and beta-sheet character are described, with morphology differing from both known natural and engineered proteins. A bioinspired terminal capping strategy is also presented, which greatly increases solubility and yields of repeat proteins containing beta strands.