Antibody design is challenging for complex antigens with diverse binding interfaces.
Current computational methods face limitations in capturing geometric features and generalizing novel antigen interfaces.
AbMEGD is a new framework proposed to address these challenges by integrating Multi-scale Equivariant Graph Diffusion models.
Experiments show AbMEGD's improved amino acid recovery, percentage improvement, and reduced root mean square deviation, establishing a new benchmark for antibody design.