Real-time ligand binding pocket database search using local surface descriptors.
Real-time ligand binding pocket database search using local surface descriptors.
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DOI：
10.1002/prot.22715
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发表时间：
2010-07
影响因子：
2.9
通讯作者：
Kihara, Daisuke
中科院分区：
文献类型：
--
作者：
Chikhi, Rayan;Sael, Lee;Kihara, Daisuke
关键词：
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，因此迫切需要用于表征蛋白质三级结构的计算方法。由于许多这些蛋白质的功能不容易通过传统的序列数据库搜索来预测，因此合理的策略是在功能表征中利用结构信息。特别令人感兴趣的是配体与蛋白质结合的预测，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，配体及其结合位点之间观察到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相似局部口袋来预测与蛋白质中局部表面位点结合的配体分子。在这里，我们提出了配体结合口袋的两种表示形式，并利用它们通过口袋形状比较来预测配体结合。这些表示基于结合口袋表面特性的映射，这些特性通过二维伪 Zernike 矩或 3D Zernike 描述符进行紧凑描述。这些紧凑的表示允许对数据库进行快速实时口袋搜索。使用两个不同数据集的彻底基准研究表明，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。
Due to 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 a 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 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study 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.
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影响因子：
3
作者：
Chua HN;Sung WK;Wong L
通讯作者：
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影响因子：
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作者：
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通讯作者：
UniProt Consortium
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作者：
Hawkins, Troy;Luban, Stanislav;Kihara, Daisuke
通讯作者：
Kihara, Daisuke