P. J. Y. Leung

This paper introduces standardized protein building blocks and geometric design principles to create expandable protein nanomaterials, validated through X-ray crystallography and electron microscopy.

This paper designs two-state hinge proteins that switch between structural states in response to ligands, demonstrating atomic-level accuracy and tunable kinetics and thermodynamics.

This paper designs high-affinity protein binders for bioactive helical peptides using deep learning and generative models, achieving picomolar affinity without experimental optimization.

A deep learning method for protein sequence design shows high performance in both simulations and experiments, applicable to various design challenges.