Temperature–energy-space sampling molecular dynamics: deterministic and single-replica method utilizing continuous temperature system
Temperature–energy-space sampling molecular dynamics: deterministic and single-replica method utilizing continuous temperature system
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DOI：
10.1088/1751-8121/aba027
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
I. Fukuda;K. Moritsugu
中科院分区：
文献类型：
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作者：
I. Fukuda;K. Moritsugu
为了增强物理系统（PS）状态的采样，我们利用耦合的Nosé-Hoover（NH）分子动力学运动方程（EOM），其中PS的热浴温度根据任意预定权重波动。耦合NH通过适当组合PS的NH EOM和温度系统（TS）的NH EOM来定义，其中逆热浴温度β是动态变量。在这项研究中，我们开发了一种方法来确定增强PS态采样的β的有效权重。该方法基于遍历理论，可靠性高，无需耗时的迭代过程和消耗资源的副本系统。由此得到的TS势在二维（β，β）空间中形成谷形，其中势的最小路径为β和β提供路径并引导它们的运动。β围绕每个能量β的势能极小值振荡，β的运动导出β的运动并接收β的反馈，这导致相互促进效应。因此，它也提供了一个特定的动力学机制来解释增强采样的特征，使得温度空间的“随机游走”增强了能量空间的“随机游走”。β和β之间的相互动力学自然产生于先前发展的双密度动力学的静态概率论形式，其中具有任意给定概率密度函数的刘维尔方程是基本的极星。模型系统和显式溶剂化蛋白质系统的数值算例验证了该方法的可靠性和简单性。
For enhanced sampling of physical system (PS) states, we utilized the coupled Nosé–Hoover (NH) molecular dynamics equations of motion (EOM), wherein the heat-bath temperature for the PS fluctuates according to an arbitrary predetermined weight. The coupled NH is defined by suitably combining the NH EOM of the PS and the NH EOM of the temperature system (TS), where the inverse heat-bath temperature β is a dynamical variable. In this study, we developed a method to determine the effective weight for β for enhanced sampling of PS states. The method, based on ergodic theory, is reliable, and eliminates the need for time-consuming iterative procedures and resource-consuming replica systems. The resulting TS potential in a two dimensional (β, ϵ)-space makes a valley-shape, where the potential minimum path provides a route for β and ϵ and guides their motions. β oscillates around the potential minima for each energy ϵ, and the motion of β derives a motion of ϵ and receives the ϵ’s feedback, which leads to a mutual boost effect. Thus, it also provides a specific dynamical mechanism to explain the features of enhanced sampling such that the temperature-space ‘random walk’ enhances the energy-space ‘random walk.’ These mutual dynamics between β and ϵ naturally arise from the static probability theory formalism of double density dynamics that was previously developed, where the Liouville equation with an arbitrarily given probability density function is the fundamental polestar. Numerical examples using a model system and explicitly solvated protein system verify the reliability and simplicity of the method.