We introduce AbDiffuser, an equivariant and physics-informed diffusion model for the joint generation of antibody 3D structures and sequences. AbDiffuser is built on top of a new representation of protein structure, relies on a novel architecture for aligned proteins, and utilizes strong diffusion priors to improve the denoising process. Our approach improves protein diffusion by taking advantage of domain knowledge and physics-based constraints; handles sequence-length changes; and reduces memory complexity by an order of magnitude, enabling backbone and side chain generation. We validate AbDiffuser in silico and in vitro. Numerical experiments showcase the ability of AbDiffuser to generate antibodies that closely track the sequence and structural properties of a reference set. Laboratory experiments confirm that all 16 HER2 antibodies discovered were expressed at high levels and that 57.1% of the selected designs were tight binders.

翻译：我们提出了AbDiffuser，这是一个等变且基于物理信息的扩散模型，用于联合生成抗体的三维结构和序列。AbDiffuser构建于一种新的蛋白质结构表示之上，依赖于一种针对对齐蛋白质的新型架构，并利用强扩散先验来改进去噪过程。我们的方法通过利用领域知识和基于物理的约束，改进了蛋白质扩散；处理了序列长度变化；并将内存复杂度降低了一个数量级，从而实现了主链和侧链的生成。我们在计算机模拟和体外实验中验证了AbDiffuser。数值实验展示了AbDiffuser生成与参考集序列和结构特性高度一致的抗体的能力。实验室实验证实，所有16种发现的HER2抗体均高水平表达，且57.1%的选定设计是紧密结合剂。