Zheng Lianqing, Carbone Irina O, Lugovskoy Alexey, Berg Bernd A, Yang Wei
Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida 32306, USA.
J Chem Phys. 2008 Jul 21;129(3):034105. doi: 10.1063/1.2953321.
Recently, we developed an efficient free energy simulation technique, the simulated scaling (SS) method [H. Li et al., J. Chem. Phys. 126, 024106 (2007)], in the framework of generalized ensemble simulations. In the SS simulations, random walks in the scaling parameter space are realized so that both phase space overlap sampling and conformational space sampling can be simultaneously enhanced. To flatten the distribution in the scaling parameter space, in the original SS implementation, the Wang-Landau recursion was employed due to its well-known recursion capability. In the Wang-Landau recursion based SS free energy simulation scheme, at the early stage, recursion efficiencies are high and free energy regions are quickly located, although at this stage, the errors of estimated free energy values are large; at the later stage, the errors of estimated free energy values become smaller, however, recursions become increasingly slow and free energy refinements require very long simulation time. In order to robustly resolve this efficiency problem during free energy refinements, a hybrid recursion strategy is presented in this paper. Specifically, we let the Wang-Landau update method take care of the early stage recursion: the location of target free energy regions, and let the adaptive reweighting method take care of the late stage recursion: the refinements of free energy values. As comparably studied in the model systems, among three possible recursion procedures, the adaptive reweighting recursion approach is the least favorable one because of its low recursion efficiency during free energy region locations; and compared to the original Wang-Landau recursion approach, the proposed hybrid recursion technique can be more robust to guarantee free energy simulation efficiencies.
最近，我们在广义系综模拟框架下开发了一种高效的自由能模拟技术——模拟标度（SS）方法[H. Li等人，《化学物理杂志》126, 024106 (2007)]。在SS模拟中，实现了标度参数空间中的随机游走，从而可以同时增强相空间重叠采样和构象空间采样。为了使标度参数空间中的分布趋于平坦，在原始的SS实现中，采用了Wang-Landau递归，因为它具有众所周知的递归能力。在基于Wang-Landau递归的SS自由能模拟方案中，在早期阶段，递归效率很高，自由能区域能快速定位，尽管在此阶段，估计自由能值的误差较大；在后期阶段，估计自由能值的误差变小，然而，递归变得越来越慢，自由能细化需要很长的模拟时间。为了在自由能细化过程中稳健地解决这个效率问题，本文提出了一种混合递归策略。具体来说，我们让Wang-Landau更新方法负责早期递归：目标自由能区域的定位，让自适应重加权方法负责后期递归：自由能值的细化。正如在模型系统中进行的比较研究那样，在三种可能出现的递归过程中，表示自适应重加权递归方法是最不理想的，因为它在自由能区域定位期间递归效率较低；与原始的Wang-Landau递归方法相比，所提出的混合递归技术在保证自由能模拟效率方面可能更稳健。
