Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST) , 1-1-1 Umezono, Tsukuba 305-8568, Japan.
Mathematics for Advanced Materials Open Innovation Laboratory (MathAM-OIL), National Institute of Advanced Industrial Science and Technology (AIST), c/o AIMR, Tohoku University , 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan.
J Chem Theory Comput. 2017 Jul 11;13(7):3106-3119. doi: 10.1021/acs.jctc.7b00252. Epub 2017 Jun 26.
Efficient and reliable estimation of the mean force (MF), the derivatives of the free energy with respect to a set of collective variables (CVs), has been a challenging problem because free energy differences are often computed by integrating the MF. Among various methods for computing free energy differences, logarithmic mean-force dynamics (LogMFD) [ Morishita et al., Phys. Rev. E 2012 , 85 , 066702 ] invokes the conservation law in classical mechanics to integrate the MF, which allows us to estimate the free energy profile along the CVs on-the-fly. Here, we present a method called parallel dynamics, which improves the estimation of the MF by employing multiple replicas of the system and is straightforwardly incorporated in LogMFD or a related method. In the parallel dynamics, the MF is evaluated by a nonequilibrium path-ensemble using the multiple replicas based on the Crooks-Jarzynski nonequilibrium work relation. Thanks to the Crooks relation, realizing full-equilibrium states is no longer mandatory for estimating the MF. Additionally, sampling in the hidden subspace orthogonal to the CV space is highly improved with appropriate weights for each metastable state (if any), which is hardly achievable by typical free energy computational methods. We illustrate how to implement parallel dynamics by combining it with LogMFD, which we call logarithmic parallel dynamics (LogPD). Biosystems of alanine dipeptide and adenylate kinase in explicit water are employed as benchmark systems to which LogPD is applied to demonstrate the effect of multiple replicas on the accuracy and efficiency in estimating the free energy profiles using parallel dynamics.
高效、可靠地估计平均力 (MF) 及其对一组广义坐标 (CVs) 的自由能导数一直是一个具有挑战性的问题,因为自由能差通常是通过积分 MF 来计算的。在计算自由能差的各种方法中,对数平均力动力学 (LogMFD) [Morishita 等人,Phys. Rev. E 2012, 85, 066702] 利用经典力学中的守恒定律来积分 MF,这使我们能够实时估计 CVs 上的自由能分布。在这里,我们提出了一种称为并行动力学的方法,该方法通过使用系统的多个副本改进 MF 的估计,并且可以直接应用于 LogMFD 或相关方法中。在并行动力学中,MF 通过基于 Crooks-Jarzynski 非平衡功关系的多个副本的非平衡路径集来评估。由于 Crooks 关系,对于估计 MF 不再需要实现全平衡状态。此外,通过为每个亚稳状态(如果有)分配适当的权重,可以极大地改善与 CV 空间正交的隐藏子空间中的采样,这是典型的自由能计算方法很难实现的。我们将说明如何通过将其与 LogMFD 结合来实现并行动力学,我们称之为对数并行动力学 (LogPD)。我们将 LogPD 应用于丙氨酸二肽和腺嘌呤激酶的生物体系,以证明多个副本对通过并行动力学估计自由能分布的准确性和效率的影响。