Bagley S C, Altman R B
Section on Medical Informatics, Stanford University School of Medicine, California 94305-5479, USA.
Protein Sci. 1995 Apr;4(4):622-35. doi: 10.1002/pro.5560040404.
Sites are microenvironments within a biomolecular structure, distinguished by their structural or functional role. A site can be defined by a three-dimensional location and a local neighborhood around this location in which the structure or function exists. We have developed a computer system to facilitate structural analysis (both qualitative and quantitative) of biomolecular sites. Our system automatically examines the spatial distributions of biophysical and biochemical properties, and reports those regions within a site where the distribution of these properties differs significantly from control nonsites. The properties range from simple atom-based characteristics such as charge to polypeptide-based characteristics such as type of secondary structure. Our analysis of sites uses non-sites as controls, providing a baseline for the quantitative assessment of the significance of the features that are uncovered. In this paper, we use radial distributions of properties to study three well-known sites (the binding sites for calcium, the milieu of disulfide bridges, and the serine protease active site). We demonstrate that the system automatically finds many of the previously described features of these sites and augments these features with some new details. In some cases, we cannot confirm the statistical significance of previously reported features. Our results demonstrate that analysis of protein structure is sensitive to assumptions about background distributions, and that these distributions should be considered explicitly during structural analyses.
位点是生物分子结构中的微环境,由其结构或功能作用来区分。一个位点可以由一个三维位置以及该位置周围存在结构或功能的局部邻域来定义。我们开发了一个计算机系统,以促进对生物分子位点的结构分析(包括定性和定量)。我们的系统会自动检查生物物理和生化特性的空间分布,并报告位点内那些这些特性分布与对照非位点有显著差异的区域。这些特性范围从基于简单原子的特征(如电荷)到基于多肽的特征(如二级结构类型)。我们对位点的分析使用非位点作为对照,为定量评估所发现特征的显著性提供了一个基线。在本文中,我们使用特性的径向分布来研究三个著名的位点(钙结合位点、二硫键环境和丝氨酸蛋白酶活性位点)。我们证明该系统能自动找到这些位点许多先前描述的特征,并以一些新细节对这些特征进行补充。在某些情况下,我们无法确认先前报道特征的统计显著性。我们的结果表明,蛋白质结构分析对关于背景分布的假设很敏感,并且在结构分析过程中应明确考虑这些分布。