Lu Hsiao-Mei, Liang Jie
Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
PLoS Comput Biol. 2009 Oct;5(10):e1000526. doi: 10.1371/journal.pcbi.1000526. Epub 2009 Oct 2.
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.
大型大分子组装体通常对细胞中的生物过程很重要。这些分子机器不同部分之间的变构通讯在细胞信号传导中起着关键作用。尽管对粗粒度残基网络的拓扑结构和波动动力学的研究可以产生重要的见解,但它们并未提供这些大分子组装体随时间变化的动态行为的特征描述。在这里,我们开发了一种名为基于微扰的马尔可夫传输(PMT)模型的新方法,以全局研究大分子组装体的动态响应。通过使用克雷洛夫子空间投影方法监测从初始微扰到达到平衡的跨越多个(>6)数量级时间内所有残基(>8000个)的同步响应,我们表明这种方法可以产生丰富的信息。基于对弛豫半衰期、流量幅度变化和振荡动力学的定量测量标准,这种方法可以识别对大分子运动重要的枢纽残基、对信号介导关键的信使残基以及对结合相互作用重要的锚定残基。基于对GroEL-GroES伴侣系统的详细分析,我们发现根据文献中报道的独立实验研究判断,我们的预测准确率为71-84%。这种方法具有通用性,可应用于其他大型大分子机器,如病毒衣壳和核糖体复合物。