Maximizing Kinetic Information Gain of Markov State Models for Optimal Design of Spectroscopy Experiments.
Maximizing Kinetic Information Gain of Markov State Models for Optimal Design of Spectroscopy Experiments.
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最大化马尔可夫态模型的动力学信息增益，以优化光谱实验设计。
DOI：
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发表时间：
2018
影响因子：
3.3
通讯作者：
D. Shukla
中科院分区：
文献类型：
--
作者：
S. Mittal;D. Shukla
光谱技术如Trp-Tyr猝灭、发光共振能量转移和三重态-三重态能量转移被广泛用于理解蛋白质的动力学行为。这些实验测量特定标记的残基对的松弛，并且残基对的选择需要仔细考虑。因此，实验者必须从大量的可能性中挑选残基对。在目前的工作中，我们表明，蛋白质动力学的分子模拟数据集可以用来系统地选择一组最佳的残基位置来放置探针进行光谱实验。在这项工作中描述的方法，称为最佳探针，可以用来排名试验组的残基对他们的能力，以捕捉蛋白质的构象动力学。最佳探针确保了两个条件：残基对捕获蛋白质的缓慢动力学，并且它们的动力学与最大信息增益不相关，从而对每个试验集进行评分。最终，得分最高的一组可用于生物物理实验，以研究蛋白质的动力学。评分方法是基于蛋白质动力学的动力学网络模型和分子动力学的变分原理，以优化用于模型的超参数。我们还讨论了最佳探针使用的评分策略是确保实验残基对的理想选择的最佳方法。我们预测了蛋白质λ-阻遏物、β2-肾上腺素能受体和绒毛头部结构域的最佳实验探针位置。这些蛋白质已经得到了很好的研究，并允许最佳探针预测与现有实验进行严格的比较。此外，我们还说明，我们的方法可以用来预测实验的最佳选择，包括任何以前的实验选择，从其他研究相同的蛋白质。我们一直发现，最佳选择不能基于直觉或结构信息，如蛋白质的几个已知稳定结构之间的距离差异。因此，我们表明，结合蛋白质动力学可以用来最大限度地提高实验的信息增益。
Spectroscopic techniques such as Trp-Tyr quenching, luminescence resonance energy transfer, and triplet-triplet energy transfer are widely used for understanding the dynamic behavior of proteins. These experiments measure the relaxation of a particular labeled set of residue pairs, and the choice of residue pairs requires careful thought. As a result, experimentalists must pick residue pairs from a large pool of possibilities. In the current work, we show that molecular simulation datasets of protein dynamics can be used to systematically select an optimal set of residue positions to place probes for conducting spectroscopic experiments. The method described in this work, called Optimal Probes, can be used to rank trial sets of residue pairs in terms of their ability to capture the conformational dynamics of the protein. Optimal probes ensures two conditions: residue pairs capture the slow dynamics of the protein and their dynamics is not correlated for maximum information gain to score each trial set. Eventually, the highest scored set can be used for biophysical experiments to study the kinetics of the protein. The scoring methodology is based on kinetic network models of protein dynamics and a variational principle for molecular kinetics to optimize the hyperparameters used for the model. We also discuss that the scoring strategy used by Optimal Probes is the best possible way to ensure the ideal choice of residue pairs for experiments. We predict the best experimental probe positions for proteins λ-repressor, β2-adrenergic receptor, and villin headpiece domain. These proteins have been well-studied and allow for a rigorous comparison of Optimal Probes predictions with already available experiments. Additionally, we also illustrate that our method can be used to predict the best choice for experiments by including any previous experiment choices available from other studies on the same protein. We consistently find that the best choice cannot be based on intuition or structural information such as distance difference between few known stable structures of the protein. Therefore, we show that incorporating protein dynamics could be used to maximize the information gain from experiments.
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DOI：
10.1039/c3cp43992e
发表时间：
2013-03-14
期刊：
Physical chemistry chemical physics : PCCP
影响因子：
--
作者：
Prigozhin MB;Gruebele M
通讯作者：
Gruebele M
DOI：
10.1073/pnas.0910001107
发表时间：
2010-03-16
影响因子：
11.1
作者：
Reiner, Andreas;Henklein, Peter;Kiefhaber, Thomas
通讯作者：
Kiefhaber, Thomas
ATP 结合盒蛋白的发光共振能量转移光谱。
DOI：
10.1016/j.bbamem.2017.08.005
发表时间：
2018
期刊：
Biochimica et biophysica acta. Biomembranes
影响因子：
--
作者：
Zoghbi,MariaE;Altenberg,GuillermoA
通讯作者：
Altenberg,GuillermoA
影响因子：
3.3
作者：
Roux, Benoit;Islam, Shahidul M.
通讯作者：
Islam, Shahidul M.
影响因子：
15
作者：
Chen, Huimin;Ahsan, Syed S.;Santiago-Berrios, Mitk'El B.;Abruna, Hector D.;Webb, Watt W.
通讯作者：
Webb, Watt W.