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从有效区分自身与非自身的角度预测T细胞受体和抗体结合区域的大小。

Predicting the size of the T-cell receptor and antibody combining region from consideration of efficient self-nonself discrimination.

作者信息

Percus J K, Percus O E, Perelson A S

机构信息

Courant Institute of Mathematical Sciences, New York University, NY 10012.

出版信息

Proc Natl Acad Sci U S A. 1993 Mar 1;90(5):1691-5. doi: 10.1073/pnas.90.5.1691.

Abstract

The binding of antibody to antigen or T-cell receptor to major histocompatibility complex-peptide complex requires that portions of the two structures have complementary shapes that can closely approach each other. The question that we address here is how large should the complementary regions on the two structures be. The interacting regions are by necessity roughly the same size. To estimate the size (number of contact residues) of an optimal receptor combining region, we assume that the immune system over evolutionary time has been presented with a large random set of foreign molecules that occur on common pathogens, which it must recognize, and a smaller random set of self-antigens to which it must fail to respond. Evolutionarily, the receptors and the molecular groups that the immune system recognizes as epitopes are imagined to have coevolved to maximize the probability that this task is performed. The probability of a receptor matching a random antigen is estimated from this condition. Using a simple model for receptor-ligand interaction, we estimate that the optimal size binding region on immunoglobulin or T-cell receptors will contain about 15 contact residues, in agreement with experimental observation.

摘要

抗体与抗原的结合,或者T细胞受体与主要组织相容性复合体 - 肽复合物的结合,要求这两种结构的部分区域具有能够彼此紧密靠近的互补形状。我们在此探讨的问题是,这两种结构上的互补区域应该有多大。相互作用的区域必然大致相同大小。为了估计最佳受体结合区域的大小(接触残基的数量),我们假设在进化过程中,免疫系统面对的是一大组随机出现的、存在于常见病原体上的外来分子,这些分子它必须识别,还有一小组随机的自身抗原,它必须不对其产生反应。从进化角度看,受体以及免疫系统识别为表位的分子基团被认为是共同进化的,以最大化完成这项任务的概率。根据这一条件估计受体与随机抗原匹配的概率。使用一个简单的受体 - 配体相互作用模型,我们估计免疫球蛋白或T细胞受体上的最佳大小结合区域将包含约15个接触残基,这与实验观察结果一致。

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6
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