Researchers unveiled a generative AI model that enables atomic-scale prediction of protein–protein interactions, aiming to accelerate both antibody discovery and other structure-driven therapeutic programs. The work focuses on improving how researchers predict and engineer the interfaces that govern protein function. The model is positioned as a tool for designing or evaluating how proteins physically interact—an increasingly central capability for biologics development, including engineered antibodies and replacement therapies. If the approach generalizes across targets, it could shorten the cycle from candidate selection to interaction validation, particularly in programs where structural biology is a bottleneck.