Jacques Boitreaud

This paper introduces a computational antibody design platform that generates drug-like antibodies with high developability and atomic accuracy, demonstrating its utility for challenging therapeutic targets.

This paper introduces Chai-2, a model that designs antibodies with a 16% hit rate, achieving success in 50% of targets without prior binders, and enables rapid validation in under two weeks.

Chai-1 matches AlphaFold3 on PoseBusters ligand poses (77% vs 76%), beats AlphaFold-Multimer 2.3 on low-homology interfaces, and stays competitive without MSAs on multimers and antibodies.

OptiMol optimizes molecular binding affinities using a hybrid structure- and ligand-based approach, improving docking scores and compound generation efficiency.