Computer Science Department, Ecole Normale Supérieure de Cachan, 94235 Cachan cedex, Britanny, France.
Proteins. 2010 Jul;78(9):2007-28. doi: 10.1002/prot.22715.
Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.
由于正在进行的结构基因组学项目积累了越来越多的未知功能结构，因此迫切需要用于描述蛋白质三级结构的计算方法。由于这些蛋白质的许多功能不容易通过传统的序列数据库搜索来预测，因此合理的策略是利用结构信息来进行功能表征。特别感兴趣的是预测配体与蛋白质的结合，因为配体分子识别是蛋白质分子功能的主要部分。由于蛋白质-配体相互作用的物理性质以及结合位点和配体分子的灵活性，预测配体分子是否与蛋白质结合是一个复杂的问题。然而，在许多情况下，配体与其结合位点之间存在几何和物理化学互补性。因此，可以通过在结构数据库中找到已知结合配体的类似局部口袋，来预测结合到蛋白质局部表面位点的配体分子。在这里，我们提出了两种配体结合口袋的表示方法，并利用它们通过口袋形状比较来进行配体结合预测。这些表示方法基于结合口袋表面特性的映射，这些特性可以通过二维伪泽尼克矩或三维泽尼克描述符紧凑地描述。这些紧凑的表示方法允许快速实时地在数据库中进行口袋搜索。使用两个不同数据集进行的深入基准研究表明，我们的表示方法与其他现有方法具有竞争力。讨论了基于形状的方法的局限性和潜力以及可能的改进。
