Adaptive free energy sampling in multidimensional collective variable space using boxed molecular dynamics.
Adaptive free energy sampling in multidimensional collective variable space using boxed molecular dynamics.
复制标题
使用盒装分子动力学在多维集体变量空间中进行自适应自由能采样。
作者：
Michael B. O'Connor;E. Paci;Simon McIntosh;D. Glowacki
在过去的十年中，已经看到了一类新的稀有事件方法的发展，其中分子构型空间被划分为一组边界/界面，然后在边界之间运行短轨迹。对于所有这些方法，一个重要的问题是如何生成边界。在本文中，我们概述了自适应生成边界沿着自由能表面在多维集体变量（CV）空间，装箱分子动力学（BXD）的罕见事件算法的基础上。BXD是一种简单的技术，用于加速稀有事件和自由能采样的模拟，已被证明可用于在NVT和NVE系综中计算反应性和非反应性分子动力学（MD）模拟中的动力学和自由能分布。本文概述的两个关键发展使BXD自动化成为可能，并自适应地映射复杂系统中的自由能和动力学。首先，我们将BXD推广到多维CV空间。使用策略从刚体动力学，我们已经得出了一个简单的和一般的速度反射过程，在多个维度中的任意集体变量的定义，保存能量，并表明，它是简单的应用BXD采样在多维CV空间，只要笛卡尔梯度的CV是可用的。其次，我们修改了BXD，以便在轨迹过程中进行实时统计分析，利用动态中潜在的信息内容自动确定边界位置。这种自动化不仅使BXD更容易使用，而且还保证了最佳边界，加快了收敛速度。我们已经通过计算最近使用实验和计算方法研究的化学反应的平均力的潜力来测试多维自适应BXD程序-即，F + CD 3CN → DF + D2CN在气相和强耦合明确的CD 3CN溶剂。使用多维自适应BXD得到的结果与以前发表的实验和计算结果吻合良好，为它的可靠性提供了很好的证据。
The past decade has seen the development of a new class of rare event methods in which molecular configuration space is divided into a set of boundaries/interfaces, and then short trajectories are run between boundaries. For all these methods, an important concern is how to generate boundaries. In this paper, we outline an algorithm for adaptively generating boundaries along a free energy surface in multi-dimensional collective variable (CV) space, building on the boxed molecular dynamics (BXD) rare event algorithm. BXD is a simple technique for accelerating the simulation of rare events and free energy sampling which has proven useful for calculating kinetics and free energy profiles in reactive and non-reactive molecular dynamics (MD) simulations across a range of systems, in both NVT and NVE ensembles. Two key developments outlined in this paper make it possible to automate BXD, and to adaptively map free energy and kinetics in complex systems. First, we have generalized BXD to multidimensional CV space. Using strategies from rigid-body dynamics, we have derived a simple and general velocity-reflection procedure that conserves energy for arbitrary collective variable definitions in multiple dimensions, and show that it is straightforward to apply BXD to sampling in multidimensional CV space so long as the Cartesian gradients ∇CV are available. Second, we have modified BXD to undertake on-the-fly statistical analysis during a trajectory, harnessing the information content latent in the dynamics to automatically determine boundary locations. Such automation not only makes BXD considerably easier to use; it also guarantees optimal boundaries, speeding up convergence. We have tested the multidimensional adaptive BXD procedure by calculating the potential of mean force for a chemical reaction recently investigated using both experimental and computational approaches - i.e., F + CD3CN → DF + D2CN in both the gas phase and a strongly coupled explicit CD3CN solvent. The results obtained using multidimensional adaptive BXD agree well with previously published experimental and computational results, providing good evidence for its reliability.
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影响因子：
4.4
作者：
Prinz, Jan-Hendrik;Wu, Hao;Noe, Frank
通讯作者：
Noe, Frank
影响因子：
8.6
作者：
D. Zuckerman;T. Woolf
通讯作者：
D. Zuckerman;T. Woolf
影响因子：
4.4
作者：
Faradjian, AK;Elber, R
通讯作者：
Elber, R
借助盒装分子动力学，在低速原子力显微镜和力钳实验中对蛋白质展开进行完全原子模拟。
DOI：
10.1021/acs.jpcb.5b11519
发表时间：
2016
期刊：
The journal of physical chemistry. B
影响因子：
--
作者：
Booth JJ
通讯作者：
Booth JJ