首页> 外文期刊>Polymer: The International Journal for the Science and Technology of Polymers >Mixed levels of coarse-graining of large proteins using elastic network model succeeds in extracting the slowest motions
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Mixed levels of coarse-graining of large proteins using elastic network model succeeds in extracting the slowest motions

机译:使用弹性网络模型混合的大蛋白质粗粒度混合级别成功地提取了最慢的运动

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摘要

We perform a mixed coarse-graining approach in a normal mode analysis of protein motions,which enables the modeling of a protein's nativge conformation with different regions having low and high resolution.As a result,the dynamics of the interesting functioal parts within a supramolecular assmblage can be analyzed at high resolution,while the remainder of the tructure is represented at poorer resoluton,thus keeping the total number of nodes in the system sufficiently low for computational tractability.Our results indicate that the vibrational dynamics of specific components in a large multi-subunit protein are best described by retaining all the components of the structure,whether at higher or lower resolution.It is also shown that similar frequency distributions are obtained for different proteins and at different levels of coarse-grainign,at the lower end of the spectrum,where the most significant slowest motions occur.
机译:我们在蛋白质运动的正常模式分析中执行混合粗粒度方法,从而可以对具有低分辨率和高分辨率的不同区域的蛋白质的天然构象进行建模。因此,超分子组装中有趣的功能部分的动力学可以在高分辨率下进行分析,而结构的其余部分以较差的分辨率表示,从而使系统中的节点总数足够少以实现计算可处理性。我们的结果表明,大型多部件中特定组件的振动动力学通过保留结构的所有组成部分,无论是处于较高分辨率还是较低分辨率,都可以最好地描述亚基蛋白。还显示出,在光谱的较低端,不同蛋白质和不同粗粒度的蛋白质获得相似的频率分布,最慢的动作发生的地方。

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