scholarly journals Protein functional dynamics from the rigorous global analysis of DEER data: Conditions, components, and conformations

2021 ◽  
Vol 153 (11) ◽  
Author(s):  
Eric J. Hustedt ◽  
Richard A. Stein ◽  
Hassane S. Mchaourab

The potential of spin labeling to reveal the dynamic dimension of macromolecules has been recognized since the dawn of the methodology in the 1960s. However, it was the development of pulsed electron paramagnetic resonance spectroscopy to detect dipolar coupling between spin labels and the availability of turnkey instrumentation in the 21st century that realized the full promise of spin labeling. Double electron-electron resonance (DEER) spectroscopy has seen widespread applications to channels, transporters, and receptors. In these studies, distance distributions between pairs of spin labels obtained under different biochemical conditions report the conformational states of macromolecules, illuminating the key movements underlying biological function. These experimental studies have spurred the development of methods for the rigorous analysis of DEER spectroscopic data along with methods for integrating these distributions into structural models. In this tutorial, we describe a model-based approach to obtaining a minimum set of components of the distance distribution that correspond to functionally relevant protein conformations with a set of fractional amplitudes that define the equilibrium between these conformations. Importantly, we review and elaborate on the error analysis reflecting the uncertainty in the various parameters, a critical step in rigorous structural interpretation of the spectroscopic data.

Molecules ◽  
2019 ◽  
Vol 24 (15) ◽  
pp. 2735 ◽  
Author(s):  
J. Jacques Jassoy ◽  
Caspar A. Heubach ◽  
Tobias Hett ◽  
Frédéric Bernhard ◽  
Florian R. Haege ◽  
...  

Pulsed dipolar electron paramagnetic resonance spectroscopy (PDS) in combination with site-directed spin labeling (SDSL) of proteins and oligonucleotides is a powerful tool in structural biology. Instead of using the commonly employed gem-dimethyl-nitroxide labels, triarylmethyl (trityl) spin labels enable such studies at room temperature, within the cells and with single-frequency electron paramagnetic resonance (EPR) experiments. However, it has been repeatedly reported that labeling of proteins with trityl radicals led to low labeling efficiencies, unspecific labeling and label aggregation. Therefore, this work introduces the synthesis and characterization of a maleimide-functionalized trityl spin label and its corresponding labeling protocol for cysteine residues in proteins. The label is highly cysteine-selective, provides high labeling efficiencies and outperforms the previously employed methanethiosulfonate-functionalized trityl label. Finally, the new label is successfully tested in PDS measurements on a set of doubly labeled Yersinia outer protein O (YopO) mutants.


2020 ◽  
Vol 1 (2) ◽  
pp. 209-224 ◽  
Author(s):  
Luis Fábregas Ibáñez ◽  
Gunnar Jeschke ◽  
Stefan Stoll

Abstract. Dipolar electron paramagnetic resonance (EPR) spectroscopy (DEER and other techniques) enables the structural characterization of macromolecular and biological systems by measurement of distance distributions between unpaired electrons on a nanometer scale. The inference of these distributions from the measured signals is challenging due to the ill-posed nature of the inverse problem. Existing analysis tools are scattered over several applications with specialized graphical user interfaces. This renders comparison, reproducibility, and method development difficult. To remedy this situation, we present DeerLab, an open-source software package for analyzing dipolar EPR data that is modular and implements a wide range of methods. We show that DeerLab can perform one-step analysis based on separable non-linear least squares, fit dipolar multi-pathway models to multi-pulse DEER data, run global analysis with non-parametric distributions, and use a bootstrapping approach to fully quantify the uncertainty in the analysis.


Biochemistry ◽  
2018 ◽  
Vol 57 (20) ◽  
pp. 2923-2931 ◽  
Author(s):  
Mark Kerzhner ◽  
Hideto Matsuoka ◽  
Christine Wuebben ◽  
Michael Famulok ◽  
Olav Schiemann

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