An intriguing controversy over protein structural class prediction
An intriguing controversy over protein structural class prediction
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DOI：
10.1023/a:1020713915365
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发表时间：
1998-11-01
期刊：
影响因子：
--
通讯作者：
Zhou, GP
中科院分区：
文献类型：
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作者：
Zhou, GP
Bahar等[（1997），Proteins 29，172-185]的最近报道表明，最初由K. C. Chou [（1995），Proteins 21，319-344]对于改进蛋白质结构类别的预测是重要的。这些作者进一步提出了一个紧凑的晶格模型，以阐明组件耦合算法中包含的物理见解。然而，Escheraber等人[（1996），Proteins 25，169-179]使用根据其定义构建的不同数据集得出了完全相反的结果。为了解决这种有趣的争议，通过各种方法对来自客观数据库SCOP数据库的数据集进行测试[Murzin等人（1995），J. Mol. 247，536-540]。自洽检验和折刀检验结果表明，考虑不同氨基酸组分间耦合效应的算法的总体预测正确率显著高于不考虑耦合效应的算法。这与蛋白质的折叠是其组成氨基酸残基之间集体相互作用的结果的物理现实完全一致，因此必须将不同氨基酸组分的偶联效应并入以提高预测质量。它是通过重新审视由Kazaber et nl的计算程序发现的。在构造结构类数据集时存在概念性错误，在应用组件耦合算法时存在系统性错误。这些发现对于理解和利用组分耦合算法研究蛋白质的结构类别具有重要意义。
A recent report by Bahar et al. [(1997), Proteins 29, 172-185] indicates that the coupling effects among different amino acid components as originally formulated by K. C. Chou [(1995), Proteins 21, 319-344] are important for improving the prediction of protein structural classes. These authors have further proposed a compact lattice model to illuminate the physical insight contained in the component-coupled algorithm. However, a completely opposite result was concluded by Eisenhaber et al. [(1996), Proteins 25, 169-179], using a different dataset constructed according to their definition. To address such an intriguing controversy, tests were conducted by various approaches for the datasets from an objective database, the SCOP database [Murzin et al. (1995), J. Mol. Biol. 247, 536-540]. The results obtained by both self-consistency and jackknife tests indicate that the overall rates of correct prediction by the algorithm incorporating the coupling effect among different amino acid components are significantly higher than those by the algorithms without counting such an effect. This is fully consistent with the physical reality that the folding of a protein is the result of a collective interaction among its constituent amino acid residues, and hence the coupling effects of different amino acid components must be incorporated in order to improve the prediction quality. It was found by a revisiting the calculation procedures by Eisenhaber et nl. that there was a conceptual mistake in constructing the structural class datasets and a systematic mistake in applying the component-coupled algorithm. These findings are informative for understanding and utilizing the component-coupled algorithm to study the structural classes of proteins.