Exploring the composition of protein-ligand binding sites on a large scale.
Exploring the composition of protein-ligand binding sites on a large scale.
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DOI：
10.1371/journal.pcbi.1003321
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发表时间：
2013
影响因子：
4.3
通讯作者：
Carlson HA
中科院分区：
文献类型：
--
作者：
Khazanov NA;Carlson HA
配体结合位点的残基组成决定了扩散介导的配体结合的相互作用，如果我们要深入了解蛋白质组的功能多样性，了解这些位点的一般组成是非常重要的。许多基于结构的药物设计方法利用这种启发式信息来改善未知功能蛋白质中配体结合位点的预测或表征。Binding MOAD数据库是最大的蛋白质-配体复合物集合之一，并提供了多样化的高质量数据来源，用于从目前可用的蛋白质结构中确定残留物组成的一般趋势。我们分析了3，295个非冗余蛋白质，其中9，114个非冗余结合位点，以确定结合区域中相对于蛋白质表面其余部分过量的残基。结合MOAD数据库从与蛋白质结合的“无效”小分子配体中描绘出生物学相关的“有效”配体。结晶介质中存在无效物，并且没有已知的生物学功能。这些类的配体之间的接触被发现是不同的，这表明生物相关的结合位点的残基组合物是不同的，不仅从其余的蛋白质表面，但也从表面区域能够机会结合的非功能性小分子。为了证实这些趋势，我们进行了严格的分析，残留倾向的变化相对于数据集的大小和内容的偏见，从一个大型蛋白质结构数据库中获得的结构集固有的。建立残留倾向的一般趋势的数据集的最佳大小，以及用于评估这种趋势的意义的策略，建议为今后的研究结合位点的组成。描述蛋白质结合位点的一般结构对于指导药物设计和更好地理解结构-功能关系至关重要。在这里，我们在我们的大型数据库中分析与蛋白质结合的小分子，Binding MOAD（所有数据库之母，发音像“mode”，是指配体结合模式的双关语）。我们专注于结合位点中残基的不同接触，并将数据相对于蛋白质的整个表面进行归一化。本研究的一个关键特征是使用“对照”，我们将真实的功能性结合位点与晶体添加剂对蛋白质表面的随机接触进行比较。在实验生物学中，控制是必需的，但在许多计算方法中，它们是不明确的。这使我们能够描述真正的结合位点在蛋白质表面上是如何独特的，并且与吸引普通小分子的随机补丁不同。
The residue composition of a ligand binding site determines the interactions available for diffusion-mediated ligand binding, and understanding general composition of these sites is of great importance if we are to gain insight into the functional diversity of the proteome. Many structure-based drug design methods utilize such heuristic information for improving prediction or characterization of ligand-binding sites in proteins of unknown function. The Binding MOAD database if one of the largest curated sets of protein-ligand complexes, and provides a source of diverse, high-quality data for establishing general trends of residue composition from currently available protein structures. We present an analysis of 3,295 non-redundant proteins with 9,114 non-redundant binding sites to identify residues over-represented in binding regions versus the rest of the protein surface. The Binding MOAD database delineates biologically-relevant “valid” ligands from “invalid” small-molecule ligands bound to the protein. Invalids are present in the crystallization medium and serve no known biological function. Contacts are found to differ between these classes of ligands, indicating that residue composition of biologically relevant binding sites is distinct not only from the rest of the protein surface, but also from surface regions capable of opportunistic binding of non-functional small molecules. To confirm these trends, we perform a rigorous analysis of the variation of residue propensity with respect to the size of the dataset and the content bias inherent in structure sets obtained from a large protein structure database. The optimal size of the dataset for establishing general trends of residue propensities, as well as strategies for assessing the significance of such trends, are suggested for future studies of binding-site composition. Describing the general structure of protein binding sites is fundamentally important for guiding drug design and better understanding structure-function relationships. Here, we analyze small molecules bound to proteins within our large database, Binding MOAD (Mother of All Databases, pronounced like “mode” as a pun referring to ligand-binding modes). We focus on different contacts across the residues in the binding sites, and we normalize the data relative to the protein's entire surface. A key feature of this study is the use of a “control” where we compare real, functional binding sites to the random contacts seen for crystallographic additives against the protein surface. Controls are required in experimental biology, but they are ill-defined in many computational approaches. This allows us to describe how true binding sites are unique on the protein surface and distinct from random patches that attract common, small molecules.
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影响因子：
14.9
作者：
Lopez G;Valencia A;Tress M
通讯作者：
Tress M
影响因子：
4.3
作者：
Davis, Fred P.;Sali, Andrej
通讯作者：
Sali, Andrej
影响因子：
5.8
作者：
Puvanendrampillai, D;Mitchell, JBO
通讯作者：
Mitchell, JBO
影响因子：
3
作者：
Golovin A;Henrick K
通讯作者：
Henrick K
影响因子：
5.6
作者：
Bartlett, GJ;Porter, CT;Thornton, JM
通讯作者：
Thornton, JM