P. J. Y. Leung

This paper designs allosterically switchable protein assemblies using rigid-body coupling of effector-switchable modules, demonstrating cooperative ligand binding and structural changes similar to natural systems.

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.