James R. Kiefer

DyAb predicts antibody properties and designs new sequences with high binding affinity using a low-data approach.

This paper introduces HX-ESP, a method combining hydrogen exchange data with molecular dynamics to predict ligand binding modes, outperforming flexible docking for conformationally flexible targets.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.