Decoding the interactions between T cell receptors and peptide-MHC

解码 T 细胞受体和肽-MHC 之间的相互作用

• 批准号: 10406323
• 负责人: Paul G. Thomas
• 金额: $ 68.19万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-20 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10406323
• 关键词: Address; Algorithms; Binding; Biological; Cells; Classification; Complex; Computer Analysis; Data; Development; Epitopes; Generations; Goals; Heart; Immune; Individual; MHC Class I Genes; Major Histocompatibility Complex; Maps; Measures; Mediating; Methods; Modeling; Mutate; Mutation; Nature; Pattern; Peptide Library; Peptide Receptor; Peptide/MHC Complex; Peptides; Sensitivity and Specificity; Shapes; Specificity; T cell receptor repertoire sequencing; T cell response; T-Cell Antigen Receptor Specificity; T-Cell Receptor; T-Lymphocyte; T-cell diversity; T-cell receptor repertoire; TCR Activation; Training; Validation; Visual; Visualization; algorithm development; analytical tool; antigen-specific T cells; base; computerized tools; cross reactivity; design; experimental study; improved; insight; mutant; next generation; novel; novel strategies; prediction algorithm; predictive modeling; receptor; recruit; sequencing platform; success; tool

PROJECT SUMMARY T cell receptor (TCR) recognition of a cognate peptide-major histocompatibility complex (pMHC) is central to adaptive immune recognition. Certain features of this interaction are well-understood, including many of the rules governing peptide binding to MHC. However, our ability to model the ternary TCR:pMHC complex remains limited for three primary reasons: (1) Data availability; (2) Binding; and (3) Cross-reactivity. In elucidating the rules by which the TCR:pMHC interface operates, these efforts stand to address fundamental questions at the heart of adaptive immune recognition, with important theoretical and practical implications that include the potential for the forward design of novel receptors with selected specificities, the “decoding” of the recent influx of TCR sequencing data for specific antigenic targets, and an understanding of the cross-reactive potential of the repertoire. Previously, we developed novel approaches that provided training data for the construction of algorithms that predict various aspects of TCR specificity (1), including an algorithm we call TCRdist - a simple and effective distance measure to compare TCR sequences. TCRdist can be used to cluster antigen-specific TCR sequences and can be incorporated into a distance-based classifier capable of correctly assigning previously unobserved TCRs to characterized repertoires with robust sensitivity and specificity. Taken together, the results of these experiments and the general success of the TCRdist algorithm provide compelling evidence for the central premises of this proposal: Given a sufficient number of experimentally verified epitope- specific TCR sequences, the epitope specificity of a TCR can be predicted from its sequence; furthermore, the generation of epitope-specific TCR sequence data, in combination with structurally informed computational analysis, provides a roadmap for building a predictive model of the TCR:pMHC interaction. While we have made significant progress in this line of inquiry, the largest remaining hurdle is the apparent broad cross-reactivity within the repertoire. In order to fully elucidate the complex network of interactions among TCRs and pMHCs, the questions we must address then are: what do diverse TCRs that see the same pMHC have in common? And what do diverse pMHCs that are seen by the same TCRs have in common? The ultimate consequence of these studies, beyond their immediate biological applications, will be to assist in the development of the next generation of analytical tools for the modeling of TCR:pMHC interaction, leading to the ultimate goal of a true “decoder” for this essential interface.

项目摘要 T细胞受体（TCR）识别同源肽 - 莫约尔组织相容性复合物（PMHC）是核心 适应性免疫识别。这种互动的某些特征是充分理解的，包括许多规则 控制肽与MHC结合。但是，我们建模三元TCR：PMHC复合物的能力仍然有限 出于三个主要原因：（1）数据可用性； （2）结合； （3）交叉反应性。通过阐明规则 TCR：PMHC接口的运行，这些努力代表着解决基本问题的核心 适应性免疫识别，具有重要的理论和实际意义，包括潜力 具有选定规格的新型受体的正向设计，TCR最近影响的“解码” 对特定抗原靶标的数据进行测序，并了解对交叉反应的潜力的理解 曲目。以前，我们开发了新颖的方法，为构建的培训数据提供了 预测TCR特异性各个方面的算法（1），包括我们称为TCRDIST的算法 - 一个简单的 和有效的距离度量以比较TCR序列。 TCRDIST可用于聚类抗原特异性 TCR序列，可以合并到能够正确分配的基于距离的分类器中 以前未观察到的TCR表征具有强大灵敏度和特异性的曲目。在一起， 这些实验的结果和TCRDIST算法的总体成功提供了令人信服的证据 对于本提案的中心前提：考虑到足够数量的实验验证的表位 - 特定的TCR序列，可以从其序列预测TCR的表位特异性。 此外，表位特异性TCR序列数据的产生与结构上结合 知情的计算分析，提供了用于构建TCR预测模型的路线图：PMHC 相互作用。尽管我们在这一询问方面取得了重大进展，但剩下的障碍是 曲目内明显的跨反应性。为了完全阐明复杂的网络 TCR和PMHC之间的互动，我们必须解决的问题是：潜水员TCRS看到什么 同一PMHC有共同点吗？同一TCR所看到的潜水员PMHC有什么 常见的？这些研究的最终结果，除了直接的生物应用外，还将是 协助开发下一代用于建模的分析工具：PMHC相互作用， 为此基本接口实现了真正的“解码器”的最终目标。