Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Biophys J. 2020 Nov 17;119(10):1937-1945. doi: 10.1016/j.bpj.2020.08.042. Epub 2020 Oct 14.
Electron paramagnetic resonance spectroscopy (EPR) is a uniquely powerful technique for characterizing conformational dynamics at specific sites within a broad range of molecular species in water. Computational tools for fitting EPR spectra have enabled dynamics parameters to be determined quantitatively. These tools have dramatically broadened the capabilities of EPR dynamics analysis, however, their implementation can easily lead to overfitting or problems with self-consistency. As a result, dynamics parameters and associated properties become difficult to reliably determine, particularly in the slow-motion regime. Here, we present an EPR analysis strategy and the corresponding computational tool for batch-fitting EPR spectra and cluster analysis of the χ landscape in Linux. We call this tool CSCA (Chi-Squared Cluster Analysis). The CSCA tool allows us to determine self-consistent rotational diffusion rates and enables calculations of activation energies of diffusion from Arrhenius plots. We demonstrate CSCA using a model system designed for EPR analysis: a self-assembled nanoribbon with radical electron spin labels positioned at known distances off the surface. We anticipate that the CSCA tool will increase the reproducibility of EPR fitting for the characterization of dynamics in biomolecules and soft matter.
电子顺磁共振波谱(EPR)是一种独特的强大技术,可用于在水中的广泛分子种类的特定位置上表征构象动力学。用于拟合 EPR 谱的计算工具使动力学参数能够定量确定。这些工具极大地扩展了 EPR 动力学分析的能力,但是,它们的实现可能很容易导致过度拟合或自洽性问题。结果,动力学参数和相关特性变得难以可靠地确定,尤其是在慢动作状态下。在这里,我们提出了一种在 Linux 中用于批量拟合 EPR 谱和 χ 景观聚类分析的 EPR 分析策略和相应的计算工具。我们称这个工具为 CSCA(卡方聚类分析)。CSCA 工具使我们能够确定自洽的旋转扩散率,并能够从 Arrhenius 图计算扩散的活化能。我们使用专为 EPR 分析设计的模型系统来演示 CSCA:一个自组装的纳米带,其自由基电子自旋标记位于距表面已知距离处。我们预计 CSCA 工具将提高生物分子和软物质中动力学特性的 EPR 拟合的可重复性。