Dipolar pathways in multi-spin and multi-dimensional dipolar EPR spectroscopy.

Dipolar electron paramagnetic resonance (EPR) experiments, such as double electron-electron resonance (DEER), measure distributions of nanometer-scale distances between unpaired electrons, which provide valuable information for structural characterization of proteins and other macromolecular systems. We present an extension to our previously published general model based on dipolar pathways valid for multi-dimensional dipolar EPR experiments with more than two spin-1/2 labels. We examine the 4-pulse DEER and TRIER experiments in terms of dipolar pathways and show experimental results confirming the theoretical predictions.

Compactness regularization in the analysis of dipolar EPR spectroscopy data.

Dipolar electron paramagnetic resonance (EPR) experiments, such as double electron-electron resonance (DEER), measure distributions of nanometer-scale distances between paramagnetic centers, which are valuable for structural characterization of proteins and other macromolecular systems. One challenge in the least-squares fitting analysis of dipolar EPR data is the separation of the inter-molecular contribution (background) and the intra-molecular contribution. For noisy experimental traces of insufficient length, this separation is not unique, leading to identifiability problems for the background model parameters and the long-distance region of the intra-molecular distance distribution.

Neural networks in pulsed dipolar spectroscopy: A practical guide.

This is a methodological guide to the use of deep neural networks in the processing of pulsed dipolar spectroscopy (PDS) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring long-lived radical pairs and paramagnetic metal ions. PDS uses distance dependence of magnetic dipolar interactions; measuring a single well-defined distance is straightforward, but extracting distance distributions is a hard and mathematically ill-posed problem requiring careful regularisation and background fitting. Neural networks do this exceptionally well, but their "robust black box" reputation hides the complexity of their design and training - particularly when the training dataset is effectively infinite.

Dipolar pathways in dipolar EPR spectroscopy.

Dipolar electron paramagnetic resonance (EPR) experiments such as double electron-electron resonance (DEER) measure distributions of nanometer-scale distances between unpaired electrons, which provide valuable information for structural characterization of proteins and other macromolecular systems. To determine these distributions from the experimental signal, it is critical to employ an accurate model of the signal. For dilute samples of doubly spin-labeled molecules, the signal is a product of an intramolecular and an intermolecular contribution.

Benchmark Test and Guidelines for DEER/PELDOR Experiments on Nitroxide-Labeled Biomolecules.

Distance distribution information obtained by pulsed dipolar EPR spectroscopy provides an important contribution to many studies in structural biology. Increasingly, such information is used in integrative structural modeling, where it delivers unique restraints on the width of conformational ensembles. In order to ensure reliability of the structural models and of biological conclusions, we herein define quality standards for sample preparation and characterization, for measurements of distributed dipole-dipole couplings between paramagnetic labels, for conversion of the primary time-domain data into distance distributions, for interpreting these distributions, and for reporting results.

Regularized dynamical decoupling noise spectroscopy - a decoherence descriptor for radicals in glassy matrices.

Decoherence arises from a fluctuating spin environment, captured by its noise spectrum (). Dynamical decoupling (DD) with π pulses extends the dephasing time if the associated filter function attenuates (). Inversely, DD noise spectroscopy (DDNS) reconstructs () from DD data by approximating the filters pass band by a -function.

NMR and EPR reveal a compaction of the RNA-binding protein FUS upon droplet formation.

Many RNA-binding proteins undergo liquid-liquid phase separation, which underlies the formation of membraneless organelles, such as stress granules and P-bodies. Studies of the molecular mechanism of phase separation in vitro are hampered by the coalescence and sedimentation of organelle-sized droplets interacting with glass surfaces. Here, we demonstrate that liquid droplets of fused in sarcoma (FUS)-a protein found in cytoplasmic aggregates of amyotrophic lateral sclerosis and frontotemporal dementia patients-can be stabilized in vitro using an agarose hydrogel that acts as a cytoskeleton mimic.

Optimal background treatment in dipolar spectroscopy.

Treatment of the background in dipolar EPR spectroscopy signals is a critical processing step for the recovery of the underlying distance distributions. Here we present new mathematical considerations that show pitfalls of background subtraction and division. In order to overcome these problems we propose an improved background treatment approach.

DeerLab: a comprehensive software package for analyzing dipolar electron paramagnetic resonance spectroscopy data.

Dipolar 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.

Non-uniform HYSCORE: Measurement, processing and analysis with Hyscorean.

Non-uniform sampling (NUS) provides a considerable reduction of measurement time especially for multi-dimensional experiments. This comes at the cost of additional signal processing steps to reconstruct the complete signal from the experimental data points. Despite being routinely employed in NMR for many experiments, EPR applications have not benefited from NUS due to the lack of a straightforward implementation to perform NUS in common commercial spectrometers.

General regularization framework for DEER spectroscopy.

Tikhonov regularization is the standard processing technique for the inversion of double electron-electron resonance (DEER) data to distance distributions without assuming a parametrized model. In other fields it has been surpassed by modern regularization methods. We analyze such alternative regularization methods based on the Tikhonov, total variation (TV) and Huber penalties with and without the use of Bregman iterations.

Transient effects in π-pulse sequences in MAS solid-state NMR.

Dipolar recoupling techniques that use isolated rotor-synchronized π pulses are commonly used in solid-state NMR spectroscopy to gain insight into the structure of biological molecules. These sequences excel through their simplicity, stability towards radio-frequency (rf) inhomogeneity, and low rf requirements. For a theoretical understanding of such sequences, we present a Floquet treatment based on an interaction-frame transformation including the chemical-shift offset dependence.