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侧链堆积方法在噬菌体阻遏蛋白和Cro蛋白建模中的应用。

The use of side-chain packing methods in modeling bacteriophage repressor and cro proteins.

作者信息

Chung S Y, Subbiah S

机构信息

Department of Biochemistry, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814, USA.

出版信息

Protein Sci. 1995 Nov;4(11):2300-9. doi: 10.1002/pro.5560041107.

Abstract

In recent years, it has been repeatedly demonstrated that the coordinates of the main-chain atoms alone are sufficient to determine the side-chain conformations of buried residues of compact proteins. Given a perfect backbone, the side-chain packing method can predict the side-chain conformations to an accuracy as high as 1.2 A RMS deviation (RMSD) with greater than 80% of the chi angles correct. However, similarly rigorous studies have not been conducted to determine how well these apply, if at all, to the more important problem of homology modeling per se. Specifically, if the available backbone is imperfect, as expected for practical application of homology modeling, can packing constraints alone achieve sufficiently accurate predictions to be useful? Here, by systematically applying such methods to the pairwise modeling of two repressor and two cro proteins from the closely related bacteriophages 434 and P22, we find that when the backbone RMSD is 0.8 A, the prediction on buried side chain is accurate with an RMS error of 1.8 A and approximately 70% of the chi angles correctly predicted. When the backbone RMSD is larger, in the range of 1.6-1.8 A, the prediction quality is still significantly better than random, with RMS error at 2.2 A on the buried side chains and 60% accuracy on chi angles. Together these results suggest the following rules-of-thumb for homology modeling of buried side chains. When the sequence identity between the modeled sequence and the template sequence is > 50% (or, equivalently, the expected backbone RMSD is < 1 A), side-chain packing methods work well. When sequence identity is between 30-50%, reflecting a backbone RMS error of 1-2 A, it is still valid to use side-chain packing methods to predict the buried residues, albeit with care. When sequence identity is below 30% (or backbone RMS error greater than 2 A), the backbone constraint alone is unlikely to produce useful models. Other methods, such as those involving the use of database fragments to reconstruct a template backbone, may be necessary as a complementary guide for modeling.

摘要

近年来,反复证明仅主链原子的坐标就足以确定紧密蛋白质中埋藏残基的侧链构象。给定一个完美的主链,侧链堆积方法可以预测侧链构象,其精度高达1.2埃均方根偏差(RMSD),且超过80%的χ角正确。然而,尚未进行类似严格的研究来确定这些方法在同源建模这一更重要问题上的适用程度(如果适用的话)。具体而言,如果可用的主链不完美,如同源建模实际应用中预期的那样,仅靠堆积约束能否实现足够准确的预测从而有用呢?在这里,通过将此类方法系统地应用于来自密切相关的噬菌体434和P22的两种阻遏蛋白和两种Cro蛋白的成对建模,我们发现当主链RMSD为0.8埃时,对埋藏侧链的预测是准确的,均方根误差为1.8埃,约70%的χ角被正确预测。当主链RMSD较大,在1.6 - 1.8埃范围内时,预测质量仍明显优于随机情况,埋藏侧链的均方根误差为2.2埃,χ角的准确率为60%。这些结果共同为埋藏侧链的同源建模提出了以下经验法则。当建模序列与模板序列之间的序列同一性>50%(或者等效地,预期的主链RMSD<1埃)时,侧链堆积方法效果良好。当序列同一性在30 - 50%之间,反映主链均方根误差为1 - 2埃时,使用侧链堆积方法预测埋藏残基仍然有效,尽管要谨慎使用。当序列同一性低于30%(或主链均方根误差大于2埃)时,仅靠主链约束不太可能产生有用的模型。其他方法,例如那些涉及使用数据库片段重建模板主链的方法,可能作为建模的补充指导是必要的。

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