Ryan Emerson

The paper generates and validates synthetic epitope proteins to improve de novo antibody design by combining computational design with high-throughput experimental binding data.

The paper disentangles protein-interaction and protein-quality effects in antibody-antigen binding using deep mutational scanning and evaluates models for their ability to predict these effects.

AlphaBind predicts and optimizes antibody-antigen binding affinity using a domain-specific model trained on quantitative binding data.

This study uses ML to design diverse VHH antibodies that neutralize SARS-CoV-1 and SARS-CoV-2 variants, including Delta and Omicron BA.1.