Abstract
The humanization of antibodies (Abs) remains one of the main pathways for therapeutic antibody development. With the advantages of diffusion models, here we present HuAbDiffusion, a discrete language diffusion model used for antibody humanization by generating humanized antibodies from scratch. HuAbDiffusion starts from three complementary determinant regions (CDRs) and finally generate whole V region sequences. The model was evaluated on 22 mAbs and compared with several existing methods, the test results show the effectiveness and better performance of the proposed model. Besides, the potential optimal humanized antibodies to be selected could be narrowed down to a reasonable level with the usage of pretrained language models. The most significant is that the binding affinity of the humanized antibody can be retained or even increased generated by HuAbDiffusion. The method can be reached out through our previous established YabXnization server at https://www.genscript.com/tools/yabxnization-service.