TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design
Chenao Li, Yaochi Guo, Xin Guan, Hui Chen, Yong Zhang, Pengyuan Yang, Jizhong Lou
TCRAD designs antigen-specific TCR CDR3β sequences using deep learning, achieving high accuracy in binder discrimination and structure prediction, with experimental validation showing 17.2% functional candidates.
bioRxiv · Jan 23, 2026 · PreprintBioinformatics