Statistically optimal analysis of samples from multiple equilibrium states
Statistically optimal analysis of samples from multiple equilibrium states
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DOI：
10.1063/1.2978177
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发表时间：
2008-09-28
影响因子：
4.4
通讯作者：
Chodera, John D.
中科院分区：
文献类型：
--
作者：
Shirts, Michael R.;Chodera, John D.
我们提出了一种新的估计器，用于计算自由能差异和热力学期望以及通过模拟或实验从多个平衡状态获得的样本的不确定性。该估计器，我们称为多状态贝内特接受比估计器（MBAR），因为当仅考虑两个状态时，它简化为贝内特接受比估计器（BAR），与组合来自多个状态的数据的多个直方图重新加权方法相比，具有显着的优势。它不需要对采样的能量范围进行离散化来生成直方图，从而消除了由于能量分箱造成的偏差，并在许多情况下显着降低了计算估计方程的解的时间复杂度。此外，还提供了所有估计数量的统计不确定性估计。在大样本限制下，MBAR 是无偏的，并且在利用从多个状态收集的均衡数据的任何已知估计量中具有最低的方差。我们通过结合恒力偏置下多个光镊测量的数据，对 DNA 发夹系统的平均力潜力进行高度精确的估计，从而说明了这种方法。 (C) 2008 年美国物理研究所。
We present a new estimator for computing free energy differences and thermodynamic expectations as well as their uncertainties from samples obtained from multiple equilibrium states via either simulation or experiment. The estimator, which we call the multistate Bennett acceptance ratio estimator (MBAR) because it reduces to the Bennett acceptance ratio estimator (BAR) when only two states are considered, has significant advantages over multiple histogram reweighting methods for combining data from multiple states. It does not require the sampled energy range to be discretized to produce histograms, eliminating bias due to energy binning and significantly reducing the time complexity of computing a solution to the estimating equations in many cases. Additionally, an estimate of the statistical uncertainty is provided for all estimated quantities. In the large sample limit, MBAR is unbiased and has the lowest variance of any known estimator for making use of equilibrium data collected from multiple states. We illustrate this method by producing a highly precise estimate of the potential of mean force for a DNA hairpin system, combining data from multiple optical tweezer measurements under constant force bias. (C) 2008 American Institute of Physics.