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Interactions in native binding sites cause a large change in protein dynamics

机译:天然结合位点的相互作用导致蛋白质动力学的巨大变化

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摘要

Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D-x which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D-x is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D-x: for 95%) of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.
机译:细胞功能受与蛋白质相互作用并改变其活性的分子调节。为了实现这种控制,蛋白质活性以及因此蛋白质构象分布必须易于通过功能位点处的分子相互作用而改变。在这里我们调查功能位点的相互作用是否引起蛋白质构象分布的大变化。我们应用一种称为动态扰动分析(DPA)的计算方法来识别相互作用具有较大变构电位D-x的位点,这是具有和不具有相互作用的蛋白质构象分布之间的Kullback-Leibler差异。在DPA中,蛋白质装饰有与相邻蛋白质原子相互作用的表面点,并且在蛋白质振动的粗粒度模型中为每个点计算D-x。我们使用DPA从标准的小分子对接测试集中检查了数百种蛋白质结构,发现配体结合位点的Dx值升高:对于95%的蛋白质,随机获得与Dx值高的概率。结合位点为10(-3)或更小。然后,我们使用DPA来开发一种计算方法来预测蛋白质中的功能位点,并发现该方法可以准确地预测测试集中蛋白质的配体结合位点残基。该方法的性能与裂缝分析方法相比具有优势。结果证实,在小分子结合位点的相互作用会导致蛋白质构象分布发生较大变化,并促使使用DPA进行蛋白质功能位点的大规模预测。他们还暗示,自然选择偏爱蛋白质的活性能够通过分子相互作用来调节。

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