| Popis: |
Vaccine development is challenged by the hierarchy of immunodominance between the target antigens’ epitopes, and the appearance of antigenic variants by pathogen mutation. The strength and breath of antibody responses relies on selection and mutation in the Germinal Center, and on the structural relationship between antigens. Computational methods for assessing the breadth of germinal center responses to multivalent antigens would greatly speed up vaccine development. Yet, such methods have poorly reflected the 3D antigen structure and antibody breadth. Here, we present Ymir, a new 3D-lattice-based framework for in silico antibody-antigen affinities. Key physiological properties naturally emerge such as affinity jumps, cross-reactivity, and differential epitope accessibility. We validated Ymir by replicating known features of germinal centers dynamics. We show that combining antigens with mutated but structurally related epitopes enhances vaccine breadth. Ymir opens a new avenue for understanding vaccine success based on the structural relationship between vaccine antigens. |
