A new study shows how the single-molecule organization of receptors in a cellular context determines the function of antibodies, opening up new pathways for the development of cancer immunotherapies.

Researchers created an antibody-specific AI framework trained on 1.6 million paired antibody chains. The framework improved binding predictions by up to 27%.

Designing an effective antibody drug is like searching for the right key in a warehouse of locks. Scientists may begin with millions—or even billions—of antibody candidates, but only a tiny fraction ...

The lower hinge of immunoglobulin G (IgG), an overlooked part of the antibody, acts as a structural and functional control hub, according to a study by researchers at Science Tokyo. Deleting a single ...

To overcome that limitation, MIT researchers have developed a computational technique that allows large language models to predict antibody structures more accurately. Their work could enable ...

MOG antibody-associated disease (MOGAD) is a rare autoimmune disease of the central nervous system. The blood of patients contains antibodies against myelin oligodendrocyte glycoprotein (MOG), a ...

Antibodies are immune proteins that our bodies produce to help fight off infection. Where they recognize and bind a pathogen — and how — can give important clues to the microbe’s vulnerabilities. Fred ...

Antibody humanization involves modifying antibodies from non-human sources, such as mice, to decrease their immunogenicity in human applications. While mouse monoclonal antibodies are specific, they ...