Scientists led by Nobel Laureate David Baker have harnessed AI-driven protein design to create highly specific, low-immunogenicity binders targeting diverse peptide-MHC complexes essential for immune recognition. Using diffusion-based models, the approach designs novel proteins that recognize viral and tumor antigens, including challenging targets like PRAME. Published in Science, these computationally designed binders accelerate the development of scalable personalized immunotherapies by overcoming MHC allele diversity constraints, advancing precision medicine capabilities.