Programs in Computational Biology and Immunology, ImmunoDynamics Group, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Cold Spring Harb Perspect Biol. 2010 Jun;2(6):a005538. doi: 10.1101/cshperspect.a005538. Epub 2010 May 5.
The T cell receptor (TCR) is responsible for discriminating between self- and foreign-derived peptides, translating minute differences in amino-acid sequence into large differences in response. Because of the great variability in the TCR and its ligands, activation of T cells by foreign peptides is a quantitative process, dependent on a mix of upstream signals and downstream integration. Accordingly, quantitative data and computational models have shed light on many important aspects of this process: molecular noise in ligand recognition, spatial dynamics in T cell-APC (antigen presenting cell) interactions, graded versus all-or-none decision making by the TCR apparatus, mechanisms of peptide antagonism and synergism, and the tunability and robustness of activation thresholds. Though diverse in their formalism, these studies together paint a picture of how modeling has shaped and will continue to shape understanding of T cell immunobiology.
T 细胞受体 (TCR) 负责区分自身和外来来源的肽,将氨基酸序列的微小差异转化为反应的巨大差异。由于 TCR 及其配体的高度可变性,外源肽激活 T 细胞是一个定量过程,取决于上游信号和下游整合的混合。因此,定量数据和计算模型揭示了这个过程的许多重要方面:配体识别中的分子噪声、T 细胞-APC(抗原呈递细胞)相互作用中的空间动力学、TCR 装置的分级决策与全或无决策、肽拮抗和协同作用的机制,以及激活阈值的可调性和鲁棒性。尽管这些研究在形式上各不相同,但它们共同描绘了建模如何塑造和将继续塑造 T 细胞免疫生物学理解的图景。