Search for: All records

Abstract 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. 

Abstract Pulsed dipolar EPR spectroscopy (PDS) in combination with site‐directed spin labeling is a powerful tool in structural biology. However, the commonly used spin labels are conjugated to biomolecules via rather long and flexible linkers, which hampers the translation of distance distributions into biomolecular conformations. In contrast, the spin label copper(II)‐nitrilotriacetic acid [Cu²⁺(NTA)] bound to two histidines (dHis) is rigid and yields narrow distance distributions, which can be more easily translated into biomolecular conformations. Here, we use this label on the 71 kDaYersiniaouter protein O (YopO) to decipher whether a previously experimentally observed bimodal distance distribution is due to two conformations of the biomolecule or of the flexible spin labels. Two different PDS experiments, that is, pulsed electron–electron double resonance (PELDOR aka DEER) and relaxation‐induced dipolar modulation enhancement (RIDME), yield unimodal distance distribution with the dHis‐Cu²⁺(NTA) motif; this result suggests that the α‐helical backbone of YopO adopts a single conformation in frozen solution. In addition, we show that the Cu²⁺(NTA) label preferentially binds to the target double histidine (dHis) sites even in the presence of 22 competing native histidine residues. Our results therefore suggest that the generation of a His‐null background is not required for this spin labeling methodology. Together these results highlight the value of the dHis‐Cu²⁺(NTA) motif in PDS experiments. 

Abstract Site‐specific dynamics in proteins are at the heart of protein function. While electron paramagnetic resonance (EPR) has potential to measure dynamics in large protein complexes, the reliance on flexible nitroxide labels is limitating especially for the accurate measurement of site‐specific β‐sheet dynamics. Here, we employed EPR spectroscopy to measure site‐specific dynamics across the surface of a protein, GB1. Through the use of the double Histidine (dHis) motif, which enables labeling with a Cu(II) – nitrilotriacetic acid (NTA) complex, dynamics information was obtained for both α‐helical and β‐sheet sites. Spectral simulations of the resulting CW‐EPR report unique site‐specific fluctuations across the surface of GB1. Additionally, we performed molecular dynamics (MD) simulations to complement the EPR data. The dynamics observed from MD agree with the EPR results. Furthermore, we observe small changes ing_ǁvalues for different sites, which may be due to small differences in coordination geometry and/or local electrostatics of the site. Taken together, this work expands the utility of Cu(II)NTA‐based EPR measurements to probe information beyond distance constraints. 

Abstract This review describes the use of Electron Paramagnetic Resonance (EPR) to measure residue specific dynamics in proteins with a specific focus on Cu(II)‐based spin labels. First, we outline approaches used to measure protein motion by nitroxide‐based spin labels. Here, we describe conceptual details and outline challenges that limit the use of nitroxide spin labels to solvent‐exposed α‐helical sites. The bulk of this review showcases the use of newly developed Cu(II)‐based protein labels. In this approach, the strategic mutation of native residues on a protein to generate two neighboring Histidine residues (i.e., the dHis motif) is exploited to enable a rigid site‐selective binding of a Cu(II) complex. The chelation of the Cu(II) complex to dHis directly anchors the Cu(II) spin label to the protein backbone. The improvement in rigidity expands both the spin‐labeling toolkit as well as the resolution of many EPR measurements. We describe how EPR measurements of the Cu(II) label directly reflect backbone motion and fluctuations. The EPR are complemented by Molecular Dynamics simulations. Finally, the dHis motif provides access to the measurement of site‐specific dynamics at both α‐helices and β‐sheets. The review outlines the limitations of the dHis method and provides an outlook for future developments. 

Abstract Template‐assisted synthesis of well‐defined polynuclear clusters remains a challenge for [M₄] square planar topologies. Herein, we present a tetraamine scaffold^RL(NH₂)₄, where L is a rigidified resorcin[4]arene, to direct the formation ofC₄‐symmetric^RL(NH)₄Cu₄clusters with Cu−Cu distances around 2.7 Å, suggesting metal‐metal direct interactions are operative since the sum of copper's van der Waals radii is 2.8 Å. DFT calculations display HOMO to HOMO‐3 residing all within a 0.1 eV gap. These four orbitals display significant electron density contribution from the Cu centers suggesting a delocalized electronic structure. The one‐electron oxidized [Cu₄]⁺species was probed by variable temperature X‐band continuous wave‐electron paramagnetic resonance (CW‐EPR), which displays a multiline spectrum at room temperature. This work presents a novel synthetic strategy for [M₄] clusters and a new platform to investigate activation of small molecules. 

Abstract Protein dynamics is at the heart of all cellular processes. Here, we utilize the dHis‐Cu^IINTA label to obtain site‐specific information on dynamics for both an α‐helix and β‐sheet site of GB1, the immunoglobulin binding domain of protein G. Spectral features found in our CW‐EPR measurements were consistent with the overall rigid nature of GB1 and with predictions from molecular dynamics simulations. Using this information, we show the potential of this approach to elucidate the role of dynamics in substrate binding of a functionally necessary α‐helix in human glutathione transferase A1‐1 (hGSTA1‐1). We observe two dynamical modes for the helix. The addition of the inhibitor GS‐Met and GS‐Hex resulted in hGSTA1‐1 to favor the more rigid active state conformation, while the faster mode potentially aids the search for substrates. Together the results illustrate the remarkable potential of the dHis‐based labelling approach to measure site‐specific dynamics using room temperature lineshape analysis. 

Bacteria use specialized proteins, like transcription factors, to rapidly control metal ion balance. CueR is a Gram‐negative bacterial copper regulator. The structure ofE. coliCueR complexed with Cu(I) and DNA was published, since then many studies have shed light on its function. However,P. aeruginosaCueR, which shows high sequence similarity toE. coliCueR, has been less studied. Here, we applied room‐temperature electron paramagnetic resonance (EPR) measurements to explore changes in dynamics ofP. aeruginosaCueR in dependency of copper concentrations and interaction with two different DNA promoter regions. We showed thatP. aeruginosaCueR is less dynamic than theE. coliCueR protein and exhibits much higher sensitivity to DNA binding as compared to itsE. coliCueR homolog. Moreover, a difference in dynamical behavior was observed whenP. aeruginosaCueR binds to thecopZ2DNA promoter sequence compared to themexPQ‐opmEpromoter sequence. Such dynamical differences may affect the expression levels of CopZ2 and MexPQ‐OpmE proteins inP. aeruginosa. Overall, such comparative measurements of protein‐DNA complexes derived from different bacterial systems reveal insights about how structural and dynamical differences between two highly homologous proteins lead to quite different DNA sequence‐recognition and mechanistic properties. 

Herein, we develop an efficient rotamer library-based approach to predict distance distributions from Cu(ii) protein labels.