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TAPO:一种用于识别蛋白质结构中串联重复序列的组合方法。

TAPO: A combined method for the identification of tandem repeats in protein structures.

作者信息

Do Viet Phuong, Roche Daniel B, Kajava Andrey V

机构信息

Centre de Recherche de Biochimie Macromoléculaire, UMR 5237 CNRS, Université Montpellier, 1919, Route de Mende, 34293 Montpellier Cedex 5, France; Institut de Biologie Computationnelle, Université Montpellier, Bat. 5, 860, rue St Priest, 34095 Montpellier Cedex 5, France.

Centre de Recherche de Biochimie Macromoléculaire, UMR 5237 CNRS, Université Montpellier, 1919, Route de Mende, 34293 Montpellier Cedex 5, France; Institut de Biologie Computationnelle, Université Montpellier, Bat. 5, 860, rue St Priest, 34095 Montpellier Cedex 5, France.

出版信息

FEBS Lett. 2015 Sep 14;589(19 Pt A):2611-9. doi: 10.1016/j.febslet.2015.08.025. Epub 2015 Aug 29.

Abstract

In recent years, there has been an emergence of new 3D structures of proteins containing tandem repeats (TRs), as a result of improved expression and crystallization strategies. Databases focused on structure classifications (PDB, SCOP, CATH) do not provide an easy solution for selection of these structures from PDB. Several approaches have been developed, but no best approach exists to identify the whole range of 3D TRs. Here we describe the TAndem PrOtein detector (TAPO) that uses periodicities of atomic coordinates and other types of structural representation, including strings generated by conformational alphabets, residue contact maps, and arrangements of vectors of secondary structure elements. The benchmarking shows the superior performance of TAPO over the existing programs. In accordance with our analysis of PDB using TAPO, 19% of proteins contain 3D TRs. This analysis allowed us to identify new families of 3D TRs, suggesting that TAPO can be used to regularly update the collection and classification of existing repetitive structures.

摘要

近年来,由于表达和结晶策略的改进,出现了含有串联重复序列(TRs)的蛋白质新三维结构。专注于结构分类的数据库(PDB、SCOP、CATH)并未为从PDB中选择这些结构提供简便的解决方案。已经开发了几种方法,但不存在识别所有三维TRs的最佳方法。在此,我们描述了串联蛋白质检测器(TAPO),它利用原子坐标的周期性以及其他类型的结构表示,包括由构象字母表生成的字符串、残基接触图和二级结构元件向量的排列。基准测试表明TAPO优于现有程序。根据我们使用TAPO对PDB的分析,19%的蛋白质含有三维TRs。该分析使我们能够识别三维TRs的新家族,这表明TAPO可用于定期更新现有重复结构的集合和分类。

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