Cavity detection and matching for binding site recognition
Cavity detection and matching for binding site recognition
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DOI：
10.1016/j.tcs.2008.08.018
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发表时间：
2008-11-28
影响因子：
1.1
通讯作者：
Guerra, Concettina
中科院分区：
文献类型：
--
作者：
Bock, Mary Ellen;Garutti, Claudio;Guerra, Concettina
我们开发了一套用于蛋白质结合位点识别问题的方法，该方法基于一组自旋图像表示蛋白质结构。空洞检测程序与先前开发的识别两个蛋白质中相似区域的方法相结合，并应用于两个蛋白质空洞的比较、一组空洞的全对配对比较以及一个空洞中多个结合位点的识别。所有这些方法都可以用来筛选大量的蛋白质集合。检测给定蛋白质中的空洞通常是蛋白质结合位点识别的第一步，因为结合位点通常位于空洞中。对两个空腔的比较发现了两个空腔中的两个相似区域，并暗示当一个或两个区域包括结合位点时，有共同的功能结构。根据空洞的相似性度量对一组空洞的所有到所有的配对比较进行聚类，当它们的结构足够相似时，获得将具有相同结合位置的空洞分组在一起的聚类。一个空洞中多个结合位点的识别是通过将一个称为背景空洞的空洞与空洞数据集进行比较，并将其残基与数据集中其他空洞的残基相匹配来进行的。这四种方法在不同的数据库上进行了基准测试，并讨论了它们的有效性。(C)2008爱思唯尔B.V.保留所有权利。
We developed a suite of methods for the problem of protein binding site recognition, based on a representation of the protein structures by a collection of spin-images. A procedure for cavity detection is coupled with a method previously developed for the recognition of similar regions in two proteins, and applied to the comparison of two protein's cavities, the all-to-all pairwise comparison of a set of cavities, and the recognition of multiple binding sites in one cavity. All the presented methods can be used to screen large collections of proteins.The detection of cavities in a given protein is often the preliminary step in protein binding site recognition, since binding sites usually lie in cavities. The comparison of two cavities identifies two similar regions in the two cavities, and hints at a common functional structure when one or both regions include a binding site. The all-to-all pairwise comparison of a set of cavities is clustered according to the measure of similarity of the cavities, obtaining a Clustering that groups together cavities with the same binding sites, when their structures are similar enough. Recognition of multiple binding sites in one cavity is performed by the comparison of a cavity, called background cavity, with a dataset of cavities, and clustering its residues that match the residues of other cavities in the data set. The four methods are benchmarked on different databases, and their effectiveness is discussed. (C) 2008 Elsevier B.V. All rights reserved.