Liu Zhi-Ping, Wu Ling-Yun, Wang Yong, Zhang Xiang-Sun
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China.
Int J Bioinform Res Appl. 2008;4(4):445-60. doi: 10.1504/IJBRA.2008.021179.
Functions of a protein are mainly determined by its structure. Surface cavities, also called pockets or clefts, are ordinarily regarded as potentially active sites where the protein carries out the functions. Clustering these pockets is a challenging task in structural genomics. In this paper, we introduce pocket similarity network which possesses the feature of community structure to systematically describe structural similarity among pockets, then a straightforward classification scheme is developed based on this special feature. The surface pockets are clustered into structurally similar pocket groups via a hierarchical process. We identify these small pocket groups as structural templates which represent similar functions in diverse proteins. The experimental results show that our clustering method is effective, and the identified pocket groups are biologically meaningful in terms of their functional features.
蛋白质的功能主要由其结构决定。表面腔，也称为口袋或裂隙，通常被视为蛋白质执行功能的潜在活性位点。在结构基因组学中，对这些口袋进行聚类是一项具有挑战性的任务。在本文中，我们引入了具有社区结构特征的口袋相似性网络，以系统地描述口袋之间的结构相似性，然后基于这一特殊特征开发了一种直接的分类方案。通过分层过程将表面口袋聚类为结构相似的口袋组。我们将这些小口袋组识别为结构模板，它们代表了不同蛋白质中的相似功能。实验结果表明，我们的聚类方法是有效的，并且所识别的口袋组在功能特征方面具有生物学意义。
