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二维电子自旋共振研究蛋白质中的微秒动力学:预测。

Microsecond dynamics in proteins by two-dimensional ESR: Predictions.

机构信息

Department of Chemistry and Chemical Biology, National Biomedical Center for Advanced ESR Technology, Cornell University, Ithaca, New York 14853, USA.

出版信息

J Chem Phys. 2020 Jun 7;152(21):214112. doi: 10.1063/5.0008094.

Abstract

Two-dimensional electron-electron double resonance (2D-ELDOR) provides extensive insight into molecular motions. Recent developments permitting experiments at higher frequencies (95 GHz) provide molecular orientational resolution, enabling a clearer description of the nature of the motions. In this work, simulations are provided for the example of domain motions within proteins that are themselves slowly tumbling in solution. These show the nature of the exchange cross-peaks that are predicted to develop in real time from such domain motions. However, we find that the existing theoretical methods for computing 2D-ELDOR experiments over a wide motional range begin to fail seriously when applied to very slow motions characteristic of proteins in solution. One reason is the failure to obtain accurate eigenvectors and eigenvalues of the complex symmetric stochastic Liouville matrices describing the experiment when computed by the efficient Lanczos algorithm in the range of very slow motion. Another, perhaps more serious, issue is that these matrices are "non-normal," such that for the very slow motional range even rigorous diagonalization algorithms do not yield the correct eigenvalues and eigenvectors. We have employed algorithms that overcome both these issues and lead to valid 2D-ELDOR predictions even for motions approaching the rigid limit. They are utilized to describe the development of cross-peaks in 2D-ELDOR at 95 GHz for a particular case of domain motion.

摘要

二维电子-电子双共振(2D-ELDOR)为分子运动提供了广泛的深入了解。最近的发展允许在更高频率(95 GHz)下进行实验,从而提供了分子取向分辨率,能够更清楚地描述运动的性质。在这项工作中,为蛋白质内部结构域运动的示例提供了模拟,这些结构域在溶液中本身旋转缓慢。这些模拟展示了从这种结构域运动实时预测的交换交叉峰的性质。然而,我们发现,当应用于溶液中蛋白质特有的非常缓慢的运动时,用于计算宽运动范围的 2D-ELDOR 实验的现有理论方法开始严重失效。原因之一是在非常缓慢的运动范围内,当使用高效的 Lanczos 算法计算描述实验的复对称随机 Liouville 矩阵时,无法获得准确的特征向量和特征值。另一个,也许更严重的问题是这些矩阵是“不正交的”,因此对于非常缓慢的运动范围,即使是严格的对角化算法也不能得到正确的特征值和特征向量。我们已经采用了克服这两个问题的算法,即使对于接近刚性极限的运动,也可以得出有效的 2D-ELDOR 预测。它们用于描述特定结构域运动情况下 95 GHz 时 2D-ELDOR 中交叉峰的发展。

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