Dobbins Sara E, Lesk Victor I, Sternberg Michael J E
Structural Bioinformatics Group, Division of Molecular Biosciences, Imperial College London, London SW7 2AY, United Kingdom.
Proc Natl Acad Sci U S A. 2008 Jul 29;105(30):10390-5. doi: 10.1073/pnas.0802496105. Epub 2008 Jul 18.
Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 A Calpha RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.
理解蛋白质相互作用对于识别机制、蛋白质设计以及为未表征蛋白质赋予假定功能具有广泛影响。研究蛋白质灵活性是描述蛋白质相互作用挑战中的关键组成部分。在这项工作中,我们对一组20种蛋白质的观测构象变化进行了表征,这些蛋白质在结合时会经历较大的构象变化(>2 Å Cα均方根偏差),并探究系统的正常模式能成功重现运动的哪些特征。我们证明正常模式可用于识别可移动区域,并且在某些蛋白质中,还能重现构象变化的方向。在所研究的蛋白质中,35%的蛋白质发现单一低频正常模式能很好地描述观测到的构象变化方向。最后,我们发现对于对接基准测试中的一组134种蛋白质,正常模式的特征频率可用于可靠地预测观测到的构象变化程度。我们讨论了这些结果对蛋白质识别机制的影响。