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基于二面角的生物聚合物(一):蛋白质的分段识别与分类。

Dihedral-based segment identification and classification of biopolymers I: proteins.

机构信息

University of Natural Resources and Life Sciences , Institute for Molecular Modeling and Simulation , Muthgasse 18, 1190 Vienna, Austria.

出版信息

J Chem Inf Model. 2014 Jan 27;54(1):266-77. doi: 10.1021/ci400541d. Epub 2014 Jan 10.

Abstract

A new structure classification scheme for biopolymers is introduced, which is solely based on main-chain dihedral angles. It is shown that by dividing a biopolymer into segments containing two central residues, a local classification can be performed. The method is referred to as DISICL, short for Dihedral-based Segment Identification and Classification. Compared to other popular secondary structure classification programs, DISICL is more detailed as it offers 18 distinct structural classes, which may be simplified into a classification in terms of seven more general classes. It was designed with an eye to analyzing subtle structural changes as observed in molecular dynamics simulations of biomolecular systems. Here, the DISICL algorithm is used to classify two databases of protein structures, jointly containing more than 10 million segments. The data is compared to two alternative approaches in terms of the amount of classified residues, average occurrence and length of structural elements, and pair wise matches of the classifications by the different programs. In an accompanying paper (Nagy, G.; Oostenbrink, C. Dihedral-based segment identification and classification of biopolymers II: Polynucleotides. J. Chem. Inf. Model. 2013, DOI: 10.1021/ci400542n), the analysis of polynucleotides is described and applied. Overall, DISICL represents a potentially useful tool to analyze biopolymer structures at a high level of detail.

摘要

引入了一种新的生物聚合物结构分类方案,该方案仅基于主链二面角。通过将生物聚合物划分为包含两个中心残基的片段,可以进行局部分类。该方法称为 DISICL,即基于二面角的片段识别和分类的缩写。与其他流行的二级结构分类程序相比,DISICL 更详细,因为它提供了 18 个不同的结构类,这些类可以简化为七个更一般的类的分类。它的设计着眼于分析生物分子系统分子动力学模拟中观察到的细微结构变化。在这里,使用 DISICL 算法对两个蛋白质结构数据库进行分类,这两个数据库共同包含超过 1000 万个片段。根据分类残基的数量、结构元素的平均出现和长度以及不同程序的分类之间的两两匹配,将数据与两种替代方法进行比较。在一篇随附的论文(Nagy,G.;Oostenbrink,C.基于二面角的生物聚合物的片段识别和分类 II:多核苷酸。J.化学。信息。模型。2013 年,DOI:10.1021/ci400542n)中,描述并应用了多核苷酸的分析。总体而言,DISICL 代表了一种分析生物聚合物结构的有用工具,可以在非常详细的水平上进行分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd87/3904766/261e58ee8901/ci-2013-00541d_0001.jpg

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