Reformulation of the self-guided molecular simulation method.
Reformulation of the self-guided molecular simulation method.
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DOI：
10.1063/5.0019086
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Xiongwu Wu;B. Brooks
中科院分区：
文献类型：
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作者：
Xiongwu Wu;B. Brooks
自导引分子/朗之万动力学（Self-guided molecular/Langevin dynamics，SGMD/SGLD）模拟方法是近年来发展起来的一种通过促进分子体系的低频运动来增强构象采样的模拟方法，已成功地应用于许多模拟研究中。通过根据频率分离微观性质，已经实现了对SGLD中构象分布的定量理解。然而，指导因素和构象分布之间缺少联系，使得在选择指导参数的值时具有高度的经验性和系统依赖性。基于分子间相互作用是能垒和扩散摩擦的来源这一认识，本工作将低频运动方程重新表述为类似朗之万动力学。这种重新表述导致新形式的导向力，并建立了导向因子和构象分布之间的关系。我们称模拟与这些新的指导力量的广义自引导分子/朗之万动力学（SGMDg/SGLDg）。此外，我们提出了一种新的方法来计算低频特性和一个有效的算法来实现SGMDg/SGLDg，最大限度地减少内存使用和处理器间的通信。通过对一个斜双阱系统、一个氩流体和一个低温电磁图灵活拟合的实例模拟，我们展示了对构象分布和构象搜索的指导作用。
Self-guided molecular/Langevin dynamics (SGMD/SGLD) simulation methods were developed to enhance conformational sampling through promoting low frequency motion of molecular systems and have been successfully applied in many simulation studies. Quantitative understanding of conformational distribution in SGLD has been achieved by separating microscopic properties according to frequency. However, a missing link between the guiding factors and conformational distributions makes it highly empirical and system dependent when choosing the values of the guiding parameters. Based on the understanding that molecular interactions are the source of energy barriers and diffusion friction, this work reformulates the equation of the low frequency motion to resemble Langevin dynamics. This reformulation leads to new forms of guiding forces and establishes a relation between the guiding factors and conformational distributions. We call simulations with these new guiding forces the generalized self-guided molecular/Langevin dynamics (SGMDg/SGLDg). In addition, we present a new way to calculate low frequency properties and an efficient algorithm to implement SGMDg/SGLDg that minimizes memory usage and inter-processor communication. Through example simulations with a skewed double well system, an argon fluid, and a cryo-EM map flexible fitting case, we demonstrate the guiding effects on conformational distributions and conformational searching.