Key Laboratory of DGHD, MOE, School of Life Science and Technology, Southeast University, Nanjing, China.
Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.
Brief Bioinform. 2022 May 13;23(3). doi: 10.1093/bib/bbac076.
The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting non-self-peptides to T cell receptors. The MHC region has been shown to be associated with a variety of diseases, including autoimmune diseases, organ transplantation and tumours. However, structural analytic tools of HLA are still sparse compared to the number of identified HLA alleles, which hinders the disclosure of its pathogenic mechanism.
To provide an integrative analysis of HLA, we first collected 1296 amino acid sequences, 256 protein data bank structures, 120 000 frequency data of HLA alleles in different populations, 73 000 publications and 39 000 disease-associated single nucleotide polymorphism sites, as well as 212 modelled HLA heterodimer structures. Then, we put forward two new strategies for building up a toolkit for transplantation and tumour immunotherapy, designing risk alignment pipeline and antigenic peptide prediction pipeline by integrating different resources and bioinformatic tools. By integrating 100 000 calculated HLA conformation difference and online tools, risk alignment pipeline provides users with the functions of structural alignment, sequence alignment, residue visualization and risk report generation of mismatched HLA molecules. For tumour antigen prediction, we first predicted 370 000 immunogenic peptides based on the affinity between peptides and MHC to generate the neoantigen catalogue for 11 common tumours. We then designed an antigenic peptide prediction pipeline to provide the functions of mutation prediction, peptide prediction, immunogenicity assessment and docking simulation. We also present a case study of hepatitis B virus mutations associated with liver cancer that demonstrates the high legitimacy of our antigenic peptide prediction process. HLA3D, including different HLA analytic tools and the prediction pipelines, is available at http://www.hla3d.cn/.
人类主要组织相容性复合体（MHC），也称为人类白细胞抗原（HLA），通过向 T 细胞受体呈递非自身肽，在适应性免疫系统中发挥重要作用。MHC 区域已被证明与多种疾病相关，包括自身免疫性疾病、器官移植和肿瘤。然而，与已鉴定的 HLA 等位基因数量相比，HLA 的结构分析工具仍然很少，这阻碍了其致病机制的揭示。
为了对 HLA 进行综合分析，我们首先收集了 1296 条氨基酸序列、256 个蛋白质数据库结构、不同人群中 HLA 等位基因的 120000 个频率数据、73000 篇出版物和 39000 个与疾病相关的单核苷酸多态性位点，以及 212 个建模 HLA 异二聚体结构。然后，我们提出了两种新策略，用于构建移植和肿瘤免疫治疗的工具包，通过整合不同的资源和生物信息学工具，设计风险配型流水线和抗原肽预测流水线。通过整合 100000 个计算出的 HLA 构象差异和在线工具，风险配型流水线为用户提供了结构配准、序列配准、残基可视化和不匹配 HLA 分子风险报告生成的功能。对于肿瘤抗原预测，我们首先基于肽与 MHC 之间的亲和力预测了 370000 个免疫原性肽，为 11 种常见肿瘤生成了新抗原目录。然后，我们设计了一个抗原肽预测流水线，提供突变预测、肽预测、免疫原性评估和对接模拟的功能。我们还展示了一个与肝癌相关的乙型肝炎病毒突变的案例研究，证明了我们的抗原肽预测过程的高度合法性。HLA3D 包括不同的 HLA 分析工具和预测流水线，可在 http://www.hla3d.cn/ 上获得。
