Kyle Meador

This paper designs full-length agonist and antagonist antibodies for hard targets using a computational pipeline, achieving nanomolar affinities and functional activity.

The paper designs a symmetry-broken tetrahedral protein cage by modifying subunits to display a single copy of an outward-facing domain.

The paper designs new protein cages using machine learning and fragment-based methods, reporting their structures and insights into assembly success and failure.

The paper introduces Nanohedra, a program for designing symmetric protein assemblies by encoding construction rules and using empirical fragment-pair associations to generate native-like interface arrangements.