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Perturbation-based Markovian Transmission Model for Probing Allosteric Dynamics of Large Macromolecular Assembling: A Study of GroEL-GroES

机译:基于摄动的马尔可夫传递模型用于探测大分子组装的构构动力学:GroEL-GroES研究

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摘要

Large macromolecular assemblies are often important for biological processes in cells. Allosteric communications between different parts of these molecular machines play critical roles in cellular signaling. Although studies of the topology and fluctuation dynamics of coarse-grained residue networks can yield important insights, they do not provide characterization of the time-dependent dynamic behavior of these macromolecular assemblies. Here we develop a novel approach called Perturbation-based Markovian Transmission (PMT) model to study globally the dynamic responses of the macromolecular assemblies. By monitoring simultaneous responses of all residues (>8,000) across many (>6) decades of time spanning from the initial perturbation until reaching equilibrium using a Krylov subspace projection method, we show that this approach can yield rich information. With criteria based on quantitative measurements of relaxation half-time, flow amplitude change, and oscillation dynamics, this approach can identify pivot residues that are important for macromolecular movement, messenger residues that are key to signal mediating, and anchor residues important for binding interactions. Based on a detailed analysis of the GroEL-GroES chaperone system, we found that our predictions have an accuracy of 71–84% judged by independent experimental studies reported in the literature. This approach is general and can be applied to other large macromolecular machineries such as the virus capsid and ribosomal complex.
机译:大分子组装对于细胞中的生物过程通常很重要。这些分子机器的不同部分之间的变构通讯在细胞信号传导中起着至关重要的作用。尽管对粗颗粒残基网络的拓扑和涨落动力学的研究可以得出重要的见解,但它们并未提供这些高分子组装体随时间变化的动力学行为的表征。在这里,我们开发了一种新的方法,称为基于扰动的马尔可夫传递(PMT)模型,以全局研究大分子组装体的动态响应。通过使用Krylov子空间投影方法监视从初始扰动到达到平衡的所有(> 6)几十年时间内所有残基(> 8,000)的同时响应,我们证明了这种方法可以产生丰富的信息。借助基于弛豫半衰期,流量幅度变化和振荡动力学的定量测量的标准,此方法可以识别对于高分子运动很重要的枢轴残基,对于信号介导至关重要的信使残基以及对于结合相互作用很重要的锚残基。在对GroEL-GroES分子伴侣系统进行详细分析的基础上,我们发现,根据文献报道的独立实验研究,我们的预测具有71-84%的准确性。这种方法是通用的,可应用于其他大型高分子机器,例如病毒衣壳和核糖体复合物。

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