Suppr超能文献

使用三个可变指标对T细胞受体进行变异性分析。

Variability analysis of the T-cell receptors using three variability indexes.

作者信息

Almagro J C, Zenteno R, Vargas-Madrazo E, Lara-Ochoa F

机构信息

Institute of Chemistry, National University of Mexico, University City.

出版信息

Int J Pept Protein Res. 1995 Feb;45(2):180-6. doi: 10.1111/j.1399-3011.1995.tb01038.x.

Abstract

In the absence of a three-dimensional structure for TCR molecules, several attempts to identify their hypervariable regions by variability methods have been made; this subjects is still troublesome. In this paper three different variability indexes were used: (i) the Kabat index, which is the classical measure of sequence variability, (ii) the modified Kabat index, successfully used in the beta-chain of T-cell receptors and (iii) an information-theoretical entropy concept, recently proposed as an improved measure of the variability. In order to identify the hypervariable regions in the TCR sequences, a Fourier filtering was applied on each variability profile. Results show that the three variability indexes have distinct resolutions for different levels of variability. Thus, the simultaneous use of these indexes compensates for the deficiency of any one of them in estimating variability. Applying the Fourier filtering, it is found that the hypervariable regions here identified, roughly coincide with the defined CDR-2 and CDR-3 in TCR by analogy with Ig. However, no hypervariable in the CDR-1 of alpha- and beta-chains was found. The study on the influence of sample size in variability analysis, indicates that results are independent of the sample size. Considering current structural models of TCR-peptide-MHC interaction, one can suggest that the low-variability characteristics of these regions is inherently related to the interaction with relatively conserved region on the alpha-helices of MHC.

摘要

由于TCR分子缺乏三维结构,人们已多次尝试通过变异性方法来识别其高变区;但该问题仍然棘手。本文使用了三种不同的变异性指标:(i)卡巴特指数,它是序列变异性的经典度量;(ii)改良卡巴特指数,已成功应用于T细胞受体的β链;(iii)一种信息论熵概念,最近被提出作为变异性的改进度量。为了识别TCR序列中的高变区,对每个变异性图谱应用了傅里叶滤波。结果表明,这三种变异性指标对于不同程度的变异性具有不同的分辨率。因此,同时使用这些指标可弥补其中任何一个在估计变异性方面的不足。通过应用傅里叶滤波发现,这里识别出的高变区大致与通过与Ig类比在TCR中定义的CDR-2和CDR-3一致。然而,在α链和β链的CDR-1中未发现高变区。关于样本大小在变异性分析中的影响的研究表明,结果与样本大小无关。考虑到TCR-肽-MHC相互作用的当前结构模型,可以认为这些区域的低变异性特征与与MHCα螺旋上相对保守区域的相互作用内在相关。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验