Inferring functional relationships of proteins from local sequence and spatial surface patterns
Inferring functional relationships of proteins from local sequence and spatial surface patterns
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DOI：
10.1016/s0022-2836(03)00882-9
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发表时间：
2003-09-12
影响因子：
5.6
通讯作者：
Liang, J
中科院分区：
文献类型：
--
作者：
Binkowski, TA;Adamian, L;Liang, J
我们描述了一种新的方法来推断蛋白质的功能关系，通过检测序列和蛋白质表面的空间模式。检查以口袋和空隙形式的良好形成的凹面区域，以确定可能与蛋白质功能直接相关的相似性关系。我们首先从蛋白质数据库中的12，177个蛋白质结构上详尽地识别和分析所有910，379个表面口袋和内部空隙。残基形成口袋和空隙的模式的相似性，然后评估顺序，在空间排列，并在定向排列。然后估计三种类型的相似性测量中的每一种的E和p值形式的统计显著性。我们的方法是完全自动化的，无需人工干预，可以使用，而无需输入的查询模式。它不假设任何蛋白质的功能残基的先验知识，并且可以基于大小的表面图案检测相似性。它还在一定程度上容忍功能位点的构象灵活性。我们的例子表明，这种方法可以检测功能的关系与特异性的成员相同的蛋白质家族和超家族，以及远程相关的功能表面从不同的折叠结构的蛋白质。我们设想，这种方法可用于发现新的蛋白质表面的功能关系，功能注释的蛋白质结构与未知的生物学作用，并为进一步调查的进化起源的结构元素重要的蛋白质功能。(C)2003 Elsevier Ltd.保留所有权利。
We describe a novel approach for inferring functional relationship of proteins by detecting sequence and spatial patterns of protein surfaces. Well-formed concave surface regions in the form of pockets and voids are examined to identify similarity relationship that might be directly related to protein function. We first exhaustively identify and measure analytically all 910,379 surface pockets and interior voids on 12,177 protein structures from the Protein Data Bank. The similarity of patterns of residues forming pockets and voids are then assessed in sequence, in spatial arrangement, and in orientational arrangement. Statistical significance in the form of E and p-values is then estimated for each of the three types of similarity measurements. Our method is fully automated without human intervention and can be used without input of query patterns. It does not assume any prior knowledge of functional residues of a protein, and can detect similarity based on surface patterns small and large. It also tolerates, to some extent, conformational flexibility of functional sites. We show with examples that this method can detect functional relationship with specificity for members of the same protein family and superfamily, as well as remotely related functional surfaces from proteins of different fold structures. We envision that this method can be used for discovering novel functional relationship of protein surfaces, for functional annotation of protein structures with unknown biological roles, and for further inquiries on evolutionary origins of structural elements important for protein function. (C) 2003 Elsevier Ltd. All rights reserved.