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在结构域水平上预测蛋白质无序状态。

Prediction of protein disorder at the domain level.

作者信息

Dosztányi Zsuzsanna, Sándor Márk, Tompa Peter, Simon István

机构信息

Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest, Hungary.

出版信息

Curr Protein Pept Sci. 2007 Apr;8(2):161-71. doi: 10.2174/138920307780363406.

Abstract

Intrinsically disordered/unstructured proteins exist in a highly flexible conformational state largely devoid of secondary structural elements and tertiary contacts. Despite their lack of a well defined structure, these proteins often fulfill essential regulatory functions. The intrinsic lack of structure confers functional advantages on these proteins, allowing them to adopt multiple conformations and to bind to different binding partners. The structural flexibility of disordered regions hampers efforts solving structures at high resolution by X-ray crystallography and/or NMR. Removing such proteins/regions from high-throughput structural genomics pipelines would be of significant benefit in terms of cost and success rate. In this paper we outline the theoretical background of structural disorder, and review bioinformatic predictors that can be used to delineate regions most likely to be amenable for structure determination. The primary focus of our review is the interpretation of prediction results in a way that enables segmentation of proteins to separate ordered domains from disordered regions.

摘要

内在无序/无结构蛋白以高度灵活的构象状态存在,基本上缺乏二级结构元件和三级相互作用。尽管它们缺乏明确的结构,但这些蛋白通常履行重要的调节功能。结构的内在缺乏赋予了这些蛋白功能上的优势,使它们能够采用多种构象并与不同的结合伴侣结合。无序区域的结构灵活性阻碍了通过X射线晶体学和/或核磁共振在高分辨率下解析结构的努力。从高通量结构基因组学流程中去除此类蛋白/区域在成本和成功率方面将带来显著益处。在本文中,我们概述了结构无序的理论背景,并综述了可用于描绘最有可能适合结构测定的区域的生物信息学预测工具。我们综述的主要重点是以一种能够对蛋白质进行分割以将有序结构域与无序区域分开的方式来解释预测结果。

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