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通过半经验参考势能加速量子力学/分子力学精度下的自由能轮廓计算。3. 态密度上的高斯平滑。

Accelerated Computation of Free Energy Profile at Quantum Mechanical/Molecular Mechanics Accuracy via a Semiempirical Reference Potential. 3. Gaussian Smoothing on Density-of-States.

机构信息

The Computer Center, School of Data Science & Engineering, East China Normal University, Shanghai 200062, China.

State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China.

出版信息

J Chem Theory Comput. 2020 Nov 10;16(11):6814-6822. doi: 10.1021/acs.jctc.0c00794. Epub 2020 Oct 6.

Abstract

Calculations of the free energy profile, also known as potential of mean force (PMF), along a chosen collective variable (CV) are now routinely applied in the studies of chemical processes, such as enzymatic reactions and chemical reactions in condensed phases. However, if the quantum mechanical/molecular mechanics (QM/MM) level of accuracy is required for the PMF, it can be formidably demanding even with the most advanced enhanced sampling methods, such as umbrella sampling. To ameliorate this difficulty, we developed a novel method for the computation of the free energy profile based on the reference-potential method recently, in which a low-level reference Hamiltonian is employed for phase space sampling and the free energy profile can be corrected to the level of interest (the target Hamiltonian) by energy reweighting in a nonparametric way. However, when the reference Hamiltonian is very different from the target Hamiltonian, the calculated ensemble averages, including the PMF, often suffer from numerical instability, which mainly comes from the overestimation of the density-of-states (DoS) in the low-energy region. Stochastic samplings of these low-energy configurations are rare events, and some low-energy conformations may get oversampled in simulations of a finite length. In this work, an assumption of Gaussian distribution is applied to the DoS in each CV bin, and the weight of each configuration is rescaled according to the accumulated DoS. The results show that this smoothing process can remarkably reduce the ruggedness of the PMF and increase the reliability of the reference-potential method.

摘要

自由能势(也称为平均力势,PMF)的计算,沿着选定的广义坐标(CV)进行,现在已经广泛应用于化学过程的研究中,如酶反应和凝聚相中的化学反应。然而,如果需要 PMF 达到量子力学/分子力学(QM/MM)的精度水平,即使使用最先进的增强采样方法(如伞状采样),也可能非常具有挑战性。为了缓解这一困难,我们最近开发了一种基于参考势能方法的自由能势计算新方法,该方法使用低水平参考哈密顿量进行相空间采样,并通过非参数方式的能量重加权,将自由能势修正到感兴趣的水平(目标哈密顿量)。然而,当参考哈密顿量与目标哈密顿量非常不同时,计算得到的系综平均值,包括 PMF,通常会受到数值不稳定性的影响,这主要源于在低能区对态密度(DOS)的高估。这些低能构型的随机采样是罕见事件,并且在有限长度的模拟中,一些低能构象可能会被过度采样。在这项工作中,我们对每个 CV -bin 中的 DOS 应用了高斯分布的假设,并根据累积的 DOS 对每个构型的权重进行了调整。结果表明,该平滑过程可以显著降低 PMF 的崎岖度,并提高参考势能方法的可靠性。

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