AI‐driven antibody design from an antigen sequence

Abstract

Large protein language models are used to generate fully human, paired-chain antibodies directly from an antigen sequence, with measurable binding in vitro. The monoclonal antibody generator tool and validation study by Wasdin et al.1 published in Cell provides a strong experimental case for this direction and underscores the need for a critical assessment of structure prediction-like, community benchmark to compare de novo antibody design strategies.