State Key Laboratory of Precision Spectroscopy, East China Normal University, Shanghai 200062, China.
Institute of Computational Science, Università della Svizzera italiana (USI), CH-6900, Lugano, Ticino, Switzerland.
J Comput Chem. 2019 May 5;40(12):1270-1289. doi: 10.1002/jcc.25784. Epub 2019 Feb 14.
The equilibrium and nonequilibrium adaptive alchemical free energy simulation methods optimum Bennett's acceptance ratio and optimum crooks' equation (OCE), based on the statistically optimal bidirectional reweighting estimator named Bennett's Acceptance Ratio or Crooks' equation, perform initial sampling in the staging alchemical transformation and then determine the importance rank of different states via the time-derivative of the variance. The method is proven to give speedups compared with the equal time rule. In the current work, we extend the time derivative of variance guided adaptive sampling method to the configurational space, falling in the term of steered MD (SMD). The SMD approach biasing physically meaningful collective variable (CV) such as one dihedral or one distance to pulling the system from one conformational state to another. By minimizing the variance of the free energy differences along the pathway in an optimized way, a new type of adaptive SMD (ASMD) is introduced. As exhibits in the alchemical case, this adaptive sampling method outperforms the traditional equal-time SMD in nonequilibrium stratification. Also, the method gives much more efficient calculation of potential of mean force than the selection criterion-based ASMD scheme, which is proven to be more efficient than traditional SMD. The OCE workflow is periodicity-of-CV dependent while ASMD is not. The performance is demonstrated in a dihedral flipping case and two distance pulling cases, accounting for periodic and nonperiodic CVs, respectively. © 2019 Wiley Periodicals, Inc.
基于基于统计最优双向重加权估计量贝内特接受比或克鲁克斯方程（OCE）的平衡和非平衡自适应量子化学自由能模拟方法最优贝内特接受比和最优克鲁克斯方程（OCE），在分步量子化学转变中进行初始采样，然后通过方差的时间导数确定不同状态的重要性等级。该方法被证明与等时规则相比具有加速作用。在当前的工作中，我们将方差的时间导数引导自适应采样方法扩展到构象空间，属于受控 MD（SMD）。SMD 方法通过偏置物理上有意义的集体变量（CV），如一个二面角或一个距离，将系统从一个构象状态拉到另一个构象状态。通过以优化的方式最小化沿路径的自由能差的方差，引入了一种新的自适应 SMD（ASMD）。如在量子化学情况下所示，这种自适应采样方法在非平衡分层中优于传统的等时 SMD。此外，该方法比基于选择标准的 ASMD 方案更有效地计算平均力势，该方案被证明比传统的 SMD 更有效。OCE 工作流程依赖于 CV 的周期性，而 ASMD 则不依赖。在二面角翻转情况和两个距离拉拔情况中分别演示了周期性和非周期性 CV 的性能。© 2019 威利父子公司。
