Reweighting ensemble probabilities with experimental histogram data constraints using a maximum entropy principle.

Reweighting ensemble probabilities with experimental histogram data constraints using a maximum entropy principle.
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使用最大熵原理通过实验直方图数据约束重新加权集合概率。

DOI:
10.1063/1.5050926
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发表时间:
2018
期刊:
The Journal of chemical physics
影响因子:
--
通讯作者:
R. Cukier
R. Cukier
中科院分区:
--
文献类型:
--
作者:
Hongfeng Lou;R. Cukier

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使用外部已知的平均约束将概率分布 P 0(x) 更新为新的分布 P(x) 的熵最大化方法可用于不同领域。 Jaynes 开发了最大熵程序 (MEP),这是一种结合外部数据将 P 0(x) 更新为 P(x) 的客观方法。在这项工作中,我们在从概率分布已知的外部数据与从均值和一些更高矩已知的外部数据的背景下考虑 MEP。迫在眉睫的问题是,传统的迭代拉格朗日乘子法依赖于对某个协方差矩阵求逆,因此在这里不适用,因为协方差矩阵是不可逆的。我们引入了一种不会遇到这个问题的指标函数方法。它为该版本的 MEP 提供了分析解决方案。例如,分析了先前生成的用于表征本质上无序蛋白质的肽构象集合。外部约束是该肽的回转概率分布半径 p(RG)。使用初始和更新的系综评估了系综可观测值,例如几何、形状特征、残基端到端距离分布、与散射强度相关的所有原子对分布函数、聚脯氨酸 II 含量和 NMR 3JHNHα 三键耦合。一些可观察量被发现对外部信息不敏感,而另一些则敏感。还分析了 24 个残基肽(组蛋白 5)的一个例子,其中可以使用实验衍生的 p(RG)。
Entropy maximization methods that update a probability distribution P 0(x) to a new distribution P(x) with the use of externally known, averaged constraints find use in diverse areas. Jaynes developed a Maximum Entropy Procedure (MEP) that is an objective approach to incorporate external data to update P 0(x) to P(x). In this work, we consider the MEP in the context of external data known from a probability distribution versus that from a mean and a few higher moments. An immediate problem is that the conventional iterative Lagrange multiplier method, which relies on inverting a certain covariance matrix, is not applicable here because the covariance matrix is not invertible. We introduce an indicator function method that does not suffer from this problem. It leads to an analytic solution to this version of a MEP. As an example, a previously generated ensemble of peptide conformations used to characterize an intrinsically disordered protein is analyzed. The external constraint is on the radius of gyration probability distribution, p(RG), of this peptide. Ensemble observables such as geometric, shape characteristics, the residue end-to-end distance distribution, the all atom-pair distribution function related to the scattering intensity, the polyproline II content, and NMR 3JHNHα three bond couplings are evaluated with the initial and updated ensembles. Some observables are found to be insensitive and others sensitive to the external information. An example of a 24-residue peptide, histatin 5, where an experimentally derived p(RG) is available, is also analyzed.
利用计算酰胺 I 光谱精炼无序肽整体:在弹性蛋白样肽中的应用。
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