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全球序列特征算法揭示了骆驼科可变域中重链互补决定区3(CDR3)环周围的结构网络。

The Global Sequence Signature algorithm unveils a structural network surrounding heavy chain CDR3 loop in Camelidae variable domains.

作者信息

Kastelic Damjana, Soler Nicolas, Komel Radovan, Pompon Denis

机构信息

Université de Toulouse, Toulouse, France.

出版信息

Biochim Biophys Acta. 2013 Jun;1830(6):3373-81. doi: 10.1016/j.bbagen.2013.02.014. Epub 2013 Feb 26.

DOI:10.1016/j.bbagen.2013.02.014
PMID:23454650
Abstract

BACKGROUND

A large fraction of camelid (camels and llamas) antibodies is composed of heavy chain-only homodimers, able to recognise antigens with their variable domain. Events in somatic assembly and maturation of antibodies such as hypermutations and rearrangement of variable loops (CDRs - complementary determining regions) and selection among a wide range of framework variants are generally considered to be random processes.

METHODS

An original algorithmic approach (Global Sequence Signature-GSS) was developed, able to take into account multiple functional and/or local sequence properties to detect scattered evolutionary constraints into sequences.

RESULTS

Using the GSS approach, we show that the length of the main hypervariable loop (CDR3) is linked to the nature of 19 surrounding residues on the scaffold. Surprisingly, the relation between CDR3 size and scaffold residues strongly depends on the considered species, illustrating either significant differences in selection mechanisms or functional constraints during antibody maturation.

CONCLUSIONS

Combined with the statistical coupling analysis (SCA) approach at the level of scaffold residues, this study has unravelled a robust interaction network on antibody structure surrounding the CDR3 loop.

GENERAL SIGNIFICANCE

In addition to the general applicability of the GSS algorithm, which can bring together functional and sequence data to locate hot spots of constrained evolution, the relationship between CDR3 and scaffold discussed here should be taken into account in protein engineering when designing antibody libraries.

摘要

背景

很大一部分骆驼科动物(骆驼和美洲驼)抗体由仅含重链的同型二聚体组成,能够通过其可变域识别抗原。抗体的体细胞组装和成熟过程中的事件,如超突变、可变环(互补决定区 - CDR)的重排以及在多种框架变体中的选择,通常被认为是随机过程。

方法

开发了一种原始的算法方法(全局序列特征 - GSS),该方法能够考虑多种功能和/或局部序列特性,以检测序列中分散的进化约束。

结果

使用GSS方法,我们表明主要高变环(CDR3)的长度与支架上19个周围残基的性质相关。令人惊讶的是,CDR3大小与支架残基之间的关系强烈依赖于所考虑的物种,这说明在抗体成熟过程中选择机制或功能约束存在显著差异。

结论

结合支架残基水平的统计耦合分析(SCA)方法,本研究揭示了围绕CDR3环的抗体结构上一个强大的相互作用网络。

普遍意义

除了GSS算法的普遍适用性,它可以将功能和序列数据结合起来定位受约束进化的热点外,在设计抗体文库的蛋白质工程中,还应考虑本文讨论的CDR3与支架之间的关系。

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