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Using an alignment of fragment strings for comparing protein structures

机译:使用片段字符串的比对比较蛋白质结构

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Motivation: Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure. Results: Here we describe the use of a particular structure fragment library, denoted here as KL-strings, for the 1D representation of protein structure. Using KL-strings, we develop an infrastructure for comparing protein structures with a 1D representation. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three-state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pairwise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification.
机译:动机:用于比较蛋白质结构的大多数方法都使用三维(3D)结构信息。同时,已经表明局部蛋白质结构的一维字符串表示保留了一定程度的结构信息。鉴于计算生物学开发的序列比较工具的存在,这种类型的表示形式可能是蛋白质结构比较和分类的强大工具。然而,为了这样做,需要首先了解蛋白质结构的各种可能的一维表示中包含多少信息。结果:在这里,我们描述了特定结构片段库(在此用KL字符串表示)用于蛋白质结构的一维表示的用途。使用KL弦,我们开发了用于比较蛋白质结构与一维表示形式的基础结构。这项研究着重于从这种描述中获得的附加价值。我们展示了新的局部结构语言为传统的三态(螺旋,链和线圈)二级结构描述增加了分辨率,并与成对对齐基准一起使用时,在识别结构相似性方面提供了很高的准确性。这项研究的结果可立即用于快速结构识别以及折叠预测和分类。

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