Wu Daichao, Yin Rui, Chen Guodong, Ribeiro-Filho Helder V, Cheung Melyssa, Robbins Paul F, Mariuzza Roy A, Pierce Brian G
Department of Hepatopancreatobiliary Surgery, The First Affiliated Hospital, Laboratory of Structural Immunology, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.
bioRxiv. 2024 May 23:2024.05.21.595215. doi: 10.1101/2024.05.21.595215.
T cell receptors (TCRs) that recognize cancer neoantigens are important for anti-cancer immune responses and immunotherapy. Understanding the structural basis of TCR recognition of neoantigens provides insights into their exquisite specificity and can enable design of optimized TCRs. We determined crystal structures of a human TCR in complex with NRAS Q61K and Q61R neoantigen peptides and HLA-A1 MHC, revealing the molecular underpinnings for dual recognition and specificity versus wild-type NRAS peptide. We then used multiple versions of AlphaFold to model the corresponding complex structures, given the challenge of immune recognition for such methods. Interestingly, one implementation of AlphaFold2 (TCRmodel2) was able to generate accurate models of the complexes, while AlphaFold3 also showed strong performance, although success was lower for other complexes. This study provides insights into TCR recognition of a shared cancer neoantigen, as well as the utility and practical considerations for using AlphaFold to model TCR-peptide-MHC complexes.
识别癌症新抗原的T细胞受体（TCR）对于抗癌免疫反应和免疫治疗至关重要。了解TCR识别新抗原的结构基础有助于深入了解其高度特异性，并能够设计优化的TCR。我们确定了与NRAS Q61K和Q61R新抗原肽以及HLA - A1 MHC形成复合物的人TCR的晶体结构，揭示了对野生型NRAS肽双重识别和特异性的分子基础。鉴于此类方法在免疫识别方面的挑战，我们随后使用多个版本的AlphaFold对相应的复合物结构进行建模。有趣的是，AlphaFold2的一种实现方式（TCRmodel2）能够生成准确的复合物模型，而AlphaFold3也表现出强大的性能，尽管其他复合物的成功率较低。这项研究为TCR识别共享癌症新抗原提供了见解，以及使用AlphaFold对TCR - 肽 - MHC复合物进行建模的实用性和实际考虑因素。
