Suppr超能文献

[蛋白质链中天然未折叠区域的预测]

[Prediction of natively unfolded regions in protein chain].

作者信息

Galzitskaia O V, Garbuzinskiĭ S A, Lobanov M Iu

出版信息

Mol Biol (Mosk). 2006 Mar-Apr;40(2):341-8.

Abstract

We have shown that the ability of a protein to be in globular or in natively unfolded state (under native conditions) may be determined (besides low overall hydrophobicity and a large net charge) by such a property as the average environment density, the average number of residues enclosed at the given distance. A statistical scale of the average number of residues enclosed at the given distance for 20 types of amino acid residues in globular state has been created on the basis of 6626 protein structures. Using this scale for separation of 80 globular and 90 natively unfolded proteins we fail only in 11% of proteins (compared with 17% of errors which are observed if to use hydrophobicity scale). The present scale may be used both for prediction of form (folded or unfolded) of the native state of protein and for prediction of natively unfolded regions in protein chains. The results of comparison of our method of predicting natively unfolded regions with the other known methods show that our method has the highest fraction of correctly predicted natively unfolded regions (that is 87% and 77% if to make averaging over residues and over proteins correspondingly).

摘要

我们已经表明,一种蛋白质处于球状或天然未折叠状态(在天然条件下)的能力,除了低总体疏水性和大净电荷外,还可能由诸如平均环境密度、给定距离内包围的残基平均数量等性质决定。基于6626个蛋白质结构,创建了球状状态下20种氨基酸残基在给定距离内包围的残基平均数量的统计量表。使用该量表对80个球状蛋白和90个天然未折叠蛋白进行区分,我们仅在11%的蛋白质中判断错误(相比之下,如果使用疏水性量表,观察到的错误率为17%)。当前的量表可用于预测蛋白质天然状态的形式(折叠或未折叠)以及预测蛋白质链中的天然未折叠区域。我们预测天然未折叠区域的方法与其他已知方法的比较结果表明,我们的方法正确预测天然未折叠区域的比例最高(如果相应地对残基和蛋白质进行平均,分别为87%和77%)。

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