Computational Biology Unit, Bergen Center for Computational Science, Bergen, Norway.
Protein Eng Des Sel. 2011 Apr;24(4):405-9. doi: 10.1093/protein/gzq115. Epub 2010 Dec 15.
An important aspect of understanding protein allostery, and of artificial effector design, is the characterization and prediction of substrate- and effector-binding sites. To find binding sites in allosteric enzymes, many of which are oligomeric with allosteric sites at domain interfaces, we devise a local centrality measure for residue interaction graphs, which behaves well for both small/monomeric and large/multimeric proteins. The measure is purely structure based and has a clear geometrical interpretation and no free parameters. It is not biased towards typically catalytic residues, a property that is crucial when looking for non-catalytic effector sites, which are potent drug targets.
理解蛋白质变构和人工效应物设计的一个重要方面是对底物和效应物结合位点的特征描述和预测。为了在变构酶中找到结合位点,其中许多酶是具有变构位点的寡聚体,我们设计了一种残基相互作用图的局部中心性度量方法,该方法适用于小分子/单体和大分子/多聚体蛋白。该度量方法完全基于结构,具有清晰的几何解释,没有自由参数。它不偏向于典型的催化残基,这在寻找非催化效应物结合位点时是至关重要的,因为这些结合位点是潜在的药物靶点。