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通过扩散映射导向的分子动力学实现自由能景观的快速恢复。

Fast recovery of free energy landscapes via diffusion-map-directed molecular dynamics.

作者信息

Preto Jordane, Clementi Cecilia

机构信息

Department of Chemistry, Rice University, Houston, TX 77005, USA.

出版信息

Phys Chem Chem Phys. 2014 Sep 28;16(36):19181-91. doi: 10.1039/c3cp54520b.

Abstract

The reaction pathways characterizing macromolecular systems of biological interest are associated with high free energy barriers. Resorting to the standard all-atom molecular dynamics (MD) to explore such critical regions may be inappropriate as the time needed to observe the relevant transitions can be remarkably long. In this paper, we present a new method called Extended Diffusion-Map-directed Molecular Dynamics (extended DM-d-MD) used to enhance the sampling of MD trajectories in such a way as to rapidly cover all important regions of the free energy landscape including deep metastable states and critical transition paths. Moreover, extended DM-d-MD was combined with a reweighting scheme enabling to save on-the-fly information about the Boltzmann distribution. Our algorithm was successfully applied to two systems, alanine dipeptide and alanine-12. Due to the enhanced sampling, the Boltzmann distribution is recovered much faster than in plain MD simulations. For alanine dipeptide, we report a speedup of one order of magnitude with respect to plain MD simulations. For alanine-12, our algorithm allows us to highlight all important unfolded basins in several days of computation when one single misfolded event is barely observable within the same amount of computational time by plain MD simulations. Our method is reaction coordinate free, shows little dependence on the a priori knowledge of the system, and can be implemented in such a way that the biased steps are not computationally expensive with respect to MD simulations thus making our approach well adapted for larger complex systems from which little information is known.

摘要

表征具有生物学意义的大分子系统的反应路径与高自由能垒相关。采用标准的全原子分子动力学(MD)来探索这些关键区域可能并不合适,因为观察相关转变所需的时间可能非常长。在本文中,我们提出了一种新方法,称为扩展扩散映射导向分子动力学(extended DM-d-MD),用于增强MD轨迹的采样,以便快速覆盖自由能景观的所有重要区域,包括深亚稳态和关键转变路径。此外,extended DM-d-MD与一种重加权方案相结合,能够实时保存有关玻尔兹曼分布的信息。我们的算法已成功应用于两个系统,丙氨酸二肽和丙氨酸-12。由于采样增强,玻尔兹曼分布的恢复速度比普通MD模拟快得多。对于丙氨酸二肽,我们报告相对于普通MD模拟有一个数量级的加速。对于丙氨酸-12,我们的算法使我们能够在几天的计算中突出所有重要的未折叠盆地,而在相同的计算时间内,普通MD模拟几乎无法观察到一个单一的错误折叠事件。我们的方法无需反应坐标,对系统的先验知识依赖性小,并且可以以这样一种方式实现,即相对于MD模拟,有偏步骤的计算成本不高,因此使我们的方法非常适合于几乎没有已知信息的更大复杂系统。

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