ICLR 2023 – Conditional Antibody Design as 3D Equivariant Graph Translation

In this episode we discuss Conditional Antibody Design as 3D Equivariant Graph Translation
by Xiangzhe Kong, Wenbing Huang, Yang Liu. The paper introduces a method called Multi-channel Equivariant Attention Network (MEAN) for antibody design. MEAN addresses challenges faced by existing deep-learning-based methods by formulating antibody design as a conditional graph translation problem and incorporating additional components. The MEAN model utilizes a proposed attention mechanism and generates both 1D CDR sequences and 3D structures, outperforming state-of-the-art models in sequence and structure modeling, antigen-binding CDR design, and binding affinity optimization.