EPR Spectroscopy Detects Various Active State Conformations of the Transcriptional Regulator CueR

Modeling of Cu(II)-based protein spin labels using rotamer libraries

The bifunctional spin label double-histidine copper-(II) capped with nitrilotriacetate [dHis-Cu(II)-NTA], used in conjunction with electron paramagnetic resonance (EPR) methods can provide high-resolution distance data for investigating protein structure and backbone conformational diversity. Quantitative utilization of this data is limited due to a lack of rapid and accurate dHis-Cu(II)-NTA modeling methods that can be used to translate experimental data into modeling restraints. Here, we develop two dHis-Cu(II)-NTA rotamer libraries using a set of recently published molecular dynamics simulations and a semi-empirical meta-dynamics-based conformational ensemble sampling tool for use with the recently developed chiLife bifunctional spin label modeling method. The accuracy of both the libraries and the modeling method are tested by comparing model predictions to experimentally determined distance distributions. We show that this method is accurate with absolute deviation between the predicted and experimental modes between 0.0-1.2 Å with an average of 0.6 Å over the test data used. In doing so, we also validate the generality of the chiLife bifunctional label modeling method. Taken together, the increased structural resolution and modeling accuracy of dHis-Cu(II)-NTA over other spin labels promise improvements in the accuracy and resolution of protein models by EPR.

Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.

Direct observation of negative cooperativity in a detoxification enzyme at the atomic level by Electron Paramagnetic Resonance spectroscopy and simulation

The catalytic activity of human glutathione S-transferase A1-1 (hGSTA1-1), a homodimeric detoxification enzyme, is dependent on the conformational dynamics of a key C-terminal helix α9 in each monomer. However, the structural details of how the two monomers interact upon binding of substrates is not well understood and the structure of the ligand-free state of the hGSTA1-1 homodimer has not been resolved. Here, we used a combination of electron paramagnetic resonance (EPR) distance measurements and weighted ensemble (WE) simulations to characterize the conformational ensemble of the ligand-free state at the atomic level. EPR measurements reveal a broad distance distribution between a pair of Cu(II) labels in the ligand-free state that gradually shifts and narrows as a function of increasing ligand concentration. These shifts suggest changes in the relative positioning of the two α9 helices upon ligand binding. WE simulations generated unbiased pathways for the seconds-timescale transition between alternate states of the enzyme, leading to the generation of atomically detailed structures of the ligand-free state. Notably, the simulations provide direct observations of negative cooperativity between the monomers of hGSTA1-1, which involve the mutually exclusive docking of α9 in each monomer as a lid over the active site. We identify key interactions between residues that lead to this negative cooperativity. Negative cooperativity may be essential for interaction of hGSTA1-1 with a wide variety of toxic substrates and their subsequent neutralization. More broadly, this work demonstrates the power of integrating EPR distances with WE rare-events sampling strategy to gain mechanistic information on protein function at the atomic level.

An optimal acquisition scheme for Q-band EPR distance measurements using Cu2+-based protein labels

Recent advances in site-directed Cu²⁺ labeling of proteins and nucleic acids have added an attractive new methodology to measure the structure-function relationship in biomolecules. Despite the promise, accessing the higher sensitivity of Q-band Double Electron Electron Resonance (DEER) has been challenging for Cu²⁺ labels designed for proteins. Q-band DEER experiments on this label typically require many measurements at different magnetic fields, since the pulses can excite only a few orientations at a given magnetic field. Herein, we analyze such orientational effects through simulations and show that three DEER measurements, at strategically selected magnetic fields, are generally sufficient to acquire an orientational-averaged DEER time trace for this spin label at Q-band. The modeling results are experimentally verified on Cu²⁺ labeled human glutathione S-transferase (hGSTA1-1). The DEER distance distribution measured at the Q-band shows good agreement with the distance distribution sampled by molecular dynamics (MD) simulations and X-band experiments. The concordance of MD sampled distances and experimentally measured distances adds growing evidence that MD simulations can accurately predict distances for the Cu²⁺ labels, which remains a key bottleneck for the commonly used nitroxide label. In all, this minimal collection scheme reduces data collection time by as much as six-fold and is generally applicable to many octahedrally coordinated Cu²⁺ systems. Furthermore, the concepts presented here may be applied to other metals and pulsed EPR experiments.

Sub-Micromolar Pulse Dipolar EPR Spectroscopy Reveals Increasing CuII -labelling of Double-Histidine Motifs with Lower Temperature

Electron paramagnetic resonance (EPR) distance measurements are making increasingly important contributions to the studies of biomolecules by providing highly accurate geometric constraints. Combining double-histidine motifs with CuII spin labels can further increase the precision of distance measurements. It is also useful for proteins containing essential cysteines that can interfere with thiol-specific labelling. However, the non-covalent CuII coordination approach is vulnerable to low binding-affinity. Herein, dissociation constants (KD ) are investigated directly from the modulation depths of relaxation-induced dipolar modulation enhancement (RIDME) EPR experiments. This reveals low- to sub-μm CuII KD s under EPR distance measurement conditions at cryogenic temperatures. We show the feasibility of exploiting the double-histidine motif for EPR applications even at sub-μm protein concentrations in orthogonally labelled CuII -nitroxide systems using a commercial Q-band EPR instrument.