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基于结构的蛋白质-蛋白质界面分析方法。

Structure-based method for analyzing protein-protein interfaces.

作者信息

Gao Ying, Wang Renxiao, Lai Luhua

机构信息

State Key Laboratory of Structural Chemistry for Stable and Unstable Species, College of Chemistry and Molecular Engineering, Peking University, 100871 Beijing, China.

出版信息

J Mol Model. 2004 Feb;10(1):44-54. doi: 10.1007/s00894-003-0168-3. Epub 2003 Nov 22.

Abstract

Hydrogen bond, hydrophobic and vdW interactions are the three major non-covalent interactions at protein-protein interfaces. We have developed a method that uses only these properties to describe interactions between proteins, which can qualitatively estimate the individual contribution of each interfacial residue to the binding and gives the results in a graphic display way. This method has been applied to analyze alanine mutation data at protein-protein interfaces. A dataset containing 13 protein-protein complexes with 250 alanine mutations of interfacial residues has been tested. For the 75 hot-spot residues (deltadelta G > or = 1.5 kcal mol(-1)), 66 can be predicted correctly with a success rate of 88%. In order to test the tolerance of this method to conformational changes upon binding, we utilize a set of 26 complexes with one or both of their components available in the unbound form. The difference of key residues exported by the program is 11% between the results using complexed proteins and those from unbound ones. As this method gives the characteristics of the binding partner for a particular protein, in-depth studies on protein-protein recognition can be carried out. Furthermore, this method can be used to compare the difference between protein-protein interactions and look for correlated mutation.

摘要

氢键、疏水相互作用和范德华相互作用是蛋白质-蛋白质界面的三种主要非共价相互作用。我们开发了一种仅利用这些性质来描述蛋白质间相互作用的方法,该方法能够定性评估每个界面残基对结合的单独贡献,并以图形显示的方式给出结果。此方法已应用于分析蛋白质-蛋白质界面的丙氨酸突变数据。一个包含13个蛋白质-蛋白质复合物、共250个界面残基丙氨酸突变的数据集已得到测试。对于75个热点残基(ΔΔG≥1.5 kcal mol⁻¹),66个能够被正确预测,成功率为88%。为了测试该方法对结合时构象变化的耐受性,我们使用了一组26个复合物,其中一个或两个组分有未结合形式。程序输出的关键残基在使用结合态蛋白质的结果与未结合态蛋白质的结果之间的差异为11%。由于该方法给出了特定蛋白质结合伴侣的特征,因此可以对蛋白质-蛋白质识别进行深入研究。此外,该方法可用于比较蛋白质-蛋白质相互作用之间的差异并寻找相关突变。

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