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Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

机译:用于宏分子组件模拟的分层顺序参数I:施工和订单参数的动态属性

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摘要

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure.
机译:大分子组件通常显示大分子或其子组件的分层组织。为了模拟这一点,我们制定了一种空间翘曲方法,可以通过一组粗粒度顺序参数(OPS)来实现整体大分子结构和动态。本文是两个描述额外的OPS的构建和计算实施中的第一个,该操作已经内置了宏分子组件的分层体系结构。为了实现这一点,首先,系统被分成子系统,每个子系统通过代表性的OPS描述。然后,从这些居中的OPS构建全局变量集以捕获整体系统组织。将所得OPS的动态特性与我们以前的非中型学的动态特性进行比较,并且讨论了100ns,200万个原子溶剂化的人乳头瘤病毒样粒子模拟的暗示概念和计算优势。在第二篇文章中,示出了分层操作以实现多尺度分析,该分析从N-Atom Liouville方程开始,并产生随机op动态的严格Langevin方程。通过基于力场的仿真算法对后者进行说明,探测关键结构转换路径,同时考虑所有原子细节和整体结构。

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