Blevins Sydney J, Baker Brian M
Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame Notre Dame, IN, USA.
Front Mol Biosci. 2017 Jan 31;4:2. doi: 10.3389/fmolb.2017.00002. eCollection 2017.
In cellular immunity, clonally distributed T cell receptors (TCRs) engage complexes of peptides bound to major histocompatibility complex proteins (pMHCs). In the interactions of TCRs with pMHCs, regions of restricted and variable diversity align in a structurally complex fashion. Many studies have used mutagenesis to attempt to understand the "roles" played by various interface components in determining TCR recognition properties such as specificity and cross-reactivity. However, these measurements are often complicated or even compromised by the weak affinities TCRs maintain toward pMHC. Here, we demonstrate how global analysis of multiple datasets can be used to significantly extend the accuracy and precision of such TCR binding experiments. Application of this approach should positively impact efforts to understand TCR recognition and facilitate the creation of mutational databases to help engineer TCRs with tuned molecular recognition properties. We also show how global analysis can be used to analyze double mutant cycles in TCR-pMHC interfaces, which can lead to new insights into immune recognition.
在细胞免疫中,克隆分布的T细胞受体(TCR)与结合到主要组织相容性复合体蛋白(pMHC)上的肽复合物相互作用。在TCR与pMHC的相互作用中,具有受限和可变多样性的区域以结构复杂的方式排列。许多研究利用诱变来试图理解各种界面成分在决定TCR识别特性(如特异性和交叉反应性)中所起的“作用”。然而,这些测量常常因TCR对pMHC的弱亲和力而变得复杂甚至受到影响。在这里,我们展示了如何通过对多个数据集的全局分析来显著提高此类TCR结合实验的准确性和精确性。这种方法的应用应该会对理解TCR识别的努力产生积极影响,并有助于创建突变数据库,以帮助设计具有调整后的分子识别特性的TCR。我们还展示了如何利用全局分析来分析TCR-pMHC界面中的双突变循环,这可以为免疫识别带来新的见解。