Predicting protein-protein interface residues using local surface structural similarity.
Predicting protein-protein interface residues using local surface structural similarity.
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DOI：
10.1186/1471-2105-13-41
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发表时间：
2012-03-18
影响因子：
3
通讯作者：
Honavar V
中科院分区：
文献类型：
--
作者：
Jordan RA;El-Manzalawy Y;Dobbs D;Honavar V
蛋白质相互作用位点残基的鉴定对药物发现等问题具有重要影响。由于观察到蛋白质的界面残基集即使在遥远的结构同源物中也趋于保守，我们引入了PrISE，这是一种基于局部结构相似性的计算方法，用于预测蛋白质-蛋白质界面残基。我们提出了一种以结构元素形式表示蛋白质表面残基的新方法。每个结构元素由一个中心残基和它的表面邻居组成。PrISE系列界面预测方法使用结构元素的表示，该表示捕获构成每个结构元素的残基的原子组成和可接近的表面积。对于查询蛋白中的每个结构元素，PrISE方法的每个成员都在其结构元素存储库中识别相似结构元素的集合，并根据它们与查询蛋白结构元素的相似性对它们进行加权。PrISEL依赖于结构元素之间的相似性（即局部结构相似性）。PrISEG依赖于蛋白质表面之间的相似性（即一般结构相似性）。PrISEC结合了局部结构相似性和一般结构相似性来预测界面残馀。这些预测器将查询蛋白中结构元素的中心残基标记为界面残基，如果与之相似的结构元素的加权多数是界面残基，则标记为界面残基，否则标记为非界面残基。使用三个代表性基准数据集的实验结果表明，PrISEC优于PrISEL和PrISEG；并且PrISEC在预测蛋白质-蛋白质界面残基方面与最先进的基于结构的方法具有很强的竞争力。PredUs是最近开发的一种基于已知的（全局）结构同源物的界面残基来预测查询蛋白界面残基的方法，我们将PrISEC与PredUs进行了比较，结果表明，仅使用局部表面结构相似性就可以获得优于或与PredUs相当的性能。基于局部表面结构相似性的方法提供了一种简单、高效和有效的方法来预测蛋白质-蛋白质界面残基。
Identification of the residues in protein-protein interaction sites has a significant impact in problems such as drug discovery. Motivated by the observation that the set of interface residues of a protein tend to be conserved even among remote structural homologs, we introduce PrISE, a family of local structural similarity-based computational methods for predicting protein-protein interface residues. We present a novel representation of the surface residues of a protein in the form of structural elements. Each structural element consists of a central residue and its surface neighbors. The PrISE family of interface prediction methods uses a representation of structural elements that captures the atomic composition and accessible surface area of the residues that make up each structural element. Each of the members of the PrISE methods identifies for each structural element in the query protein, a collection of similar structural elements in its repository of structural elements and weights them according to their similarity with the structural element of the query protein. PrISEL relies on the similarity between structural elements (i.e. local structural similarity). PrISEG relies on the similarity between protein surfaces (i.e. general structural similarity). PrISEC, combines local structural similarity and general structural similarity to predict interface residues. These predictors label the central residue of a structural element in a query protein as an interface residue if a weighted majority of the structural elements that are similar to it are interface residues, and as a non-interface residue otherwise. The results of our experiments using three representative benchmark datasets show that the PrISEC outperforms PrISEL and PrISEG; and that PrISEC is highly competitive with state-of-the-art structure-based methods for predicting protein-protein interface residues. Our comparison of PrISEC with PredUs, a recently developed method for predicting interface residues of a query protein based on the known interface residues of its (global) structural homologs, shows that performance superior or comparable to that of PredUs can be obtained using only local surface structural similarity. PrISEC is available as a Web server at http://prise.cs.iastate.edu/ Local surface structural similarity based methods offer a simple, efficient, and effective approach to predict protein-protein interface residues.
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