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吉萨诺夫重加权法在元动力学模拟中的应用。

Girsanov reweighting for metadynamics simulations.

机构信息

Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Takustraße 3, D-14195 Berlin, Germany.

出版信息

J Chem Phys. 2018 Aug 21;149(7):072335. doi: 10.1063/1.5027728.

Abstract

Metadynamics is a computational method to explore the phase space of a molecular system. Gaussian functions are added along relevant coordinates on the fly during a molecular-dynamics simulation to force the system to escape from minima in the potential energy function. The dynamics in the resulting trajectory are however unphysical and cannot be used directly to estimate dynamical properties of the system. Girsanov reweighting is a recent method used to construct the Markov State Model (MSM) of a system subjected to an external perturbation. With the combination of these two techniques-metadynamics/Girsanov-reweighting-the unphysical dynamics in a metadynamics simulation can be reweighted to obtain the MSM of the unbiased system. We demonstrate the method on a one-dimensional diffusion process, alanine dipeptide, and the hexapeptide Val-Gly-Val-Ala-Pro-Gly (VGVAPG). The results are in excellent agreement with the MSMs obtained from direct unbiased simulations of these systems. We also apply metadynamics/Girsanov-reweighting to a -hairpin peptide, whose dynamics is too slow to efficiently explore its phase space by direct simulation.

摘要

变分动力学是一种探索分子系统相空间的计算方法。在分子动力学模拟过程中,沿相关坐标实时添加高斯函数,以迫使系统逃离势能函数中的最小值。然而,由此产生的轨迹中的动力学是不真实的,不能直接用于估计系统的动力学特性。Girsanov 重新加权是一种最近用于构建受到外部扰动的系统的马尔可夫状态模型 (MSM) 的方法。通过将这两种技术——变分动力学/Girsanov 重新加权相结合,可以对变分动力学模拟中的非真实动力学进行重新加权,以获得无偏系统的 MSM。我们在一维扩散过程、丙氨酸二肽和六肽 Val-Gly-Val-Ala-Pro-Gly (VGVAPG) 上演示了该方法。结果与直接无偏模拟这些系统得到的 MSM 非常吻合。我们还将变分动力学/Girsanov 重新加权应用于β发夹肽,由于其动力学太慢,无法通过直接模拟有效地探索其相空间。

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