Confidence Analysis of DEER Data and Its Structural Interpretation with Ensemble-Biased Metadynamics

Deconvoluting Monomer- and Dimer-Specific Distance Distributions between Spin Labels in a Monomer/Dimer Mixture Using T1-Edited DEER EPR Spectroscopy

Double electron-electron resonance (DEER) EPR is a powerful tool in structural biology, providing distances between pairs of spin labels. When the sample consists of a mixture of oligomeric species (e.g., monomer and dimer), the question arises as to how to assign the peaks in the DEER-derived probability distance distribution to the individual species. Here, we propose incorporating an EPR longitudinal electron relaxation (T1) inversion recovery experiment within a DEER pulse sequence to resolve this problem. The apparent T1 between dipolar coupled electron spins measured from the inversion recovery time (τinv) dependence of the peak intensities in the T1-edited DEER-derived probability P(r) distance distribution will be affected by the number of nitroxide labels attached to the biomolecule of interest, for example, two for a monomer and four for a dimer. We show that global fitting of all the T1-edited DEER echo curves, recorded over a range of τinv values, permits the deconvolution of distances between spin labels originating from monomeric (longer T1) and dimeric (shorter T1) species. This is especially useful when the trapping of spin labels in different conformational states during freezing gives rise to complex P(r) distance distributions. The utility of this approach is demonstrated for two systems, the β1 adrenergic receptor and a construct of the huntingtin exon-1 protein fused to the immunoglobulin domain of protein G, both of which exist in a monomer-dimer equilibrium.

Confidence limits in pulse dipolar EPR spectroscopy: estimates for individual measurements

The distribution of inter-label distances obtained by electron paramagnetic resonance (EPR) pulse dipolar spectroscopies (PDS), such as DEER aka PELDOR, gives a valuable characterization of structure on the nanometer scale. The impact of random experimental noise on such experiments is examined for three independent methods for analysing PDS data: the model-free method with Tikhonov regularization, model-free with Mellin-transformation, and a model-based method. All three methods show negative bias for the mean distance and positive bias for the distribution width. Both biases grow with increasing noise levels. The estimated confidence bands and the uncertainties obtained from a single experimental measurement by the standard bootstrapping or χ2-surface scanning approaches are inconsistent and can exclude the true distance distribution. Yet, both approaches can provide quite valuable support for hypothesis testing in PDS studies.

Comprehensive characterization of polyproline tri-helix macrocyclic nanoscaffolds for predictive ligand positioning

Multivalent ligands hold promise for enhancing avidity and selectivity to simultaneously target multimeric proteins, as well as potentially modulating receptor signaling in pharmaceutical applications. Essential for these manipulations are nanosized scaffolds that precisely control ligand display patterns, which can be achieved by using polyproline oligo-helix macrocyclic nanoscaffolds via selective binding to protein oligomers and cell surface receptors. This work focuses on synthesis and structural characterization of different-sized polyproline tri-helix macrocyclic (PP3M) scaffolds. Through combined analysis of circular dichroism (CD), small- and wide-angle X-ray scattering (SWAXS), electron spin resonance (ESR) spectroscopy, and molecular modeling, a non-coplanar tri-helix loop structure with partially crossover helix ends is elucidated. This structural model aligns well with scanning tunneling microscopy (STM) imaging. The present work enhances the precision of nanoscale organic synthesis, offering prospects for controlled ligand positioning on scaffolds. This advancement paves the way for further applications in nanomedicine through selective protein interaction, manipulation of cell surface receptor functions, and developments of more complex polyproline-based nanostructures.

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.

PDSFit: PDS data analysis in the presence of orientation selectivity, g-anisotropy, and exchange coupling

Pulsed dipolar electron paramagnetic resonance spectroscopy (PDS), encompassing techniques such as pulsed electron-electron double resonance (PELDOR or DEER) and relaxation-induced dipolar modulation enhancement (RIDME), is a valuable method in structural biology and materials science for obtaining nanometer-scale distance distributions between electron spin centers. An important aspect of PDS is the extraction of distance distributions from the measured time traces. Most software used for this PDS data analysis relies on simplifying assumptions, such as assuming isotropic g-factors of ~2 and neglecting orientation selectivity and exchange coupling. Here, the program PDSFit is introduced, which enables the analysis of PELDOR and RIDME time traces with or without orientation selectivity. It can be applied to spin systems consisting of up to two spin centers with anisotropic g-factors and to spin systems with exchange coupling. It employs a model-based fitting of the time traces using parametrized distance and angular distributions, and parametrized PDS background functions. The fitting procedure is followed by an error analysis for the optimized parameters of the distributions and backgrounds. Using five different experimental data sets published previously, the performance of PDSFit is tested and found to provide reliable solutions.

Cucurbit[7]uril Enhances Distance Measurements of Spin-Labeled Proteins

We report complex formation between the chloroacetamide 2,6-diazaadamantane nitroxide radical (ClA-DZD) and cucurbit[7]uril (CB-7), for which the association constant in water, Ka = 1.9 × 106 M-1, is at least 1 order of magnitude higher than the previously studied organic radicals. The radical is highly immobilized by CB-7, as indicated by the increase in the rotational correlation time, τrot, by a factor of 36, relative to that in the buffer solution. The X-ray structure of ClA-DZD@CB-7 shows the encapsulated DZD guest inside the undistorted CB-7 host, with the pendant group protruding outside. Upon addition of CB-7 to T4 Lysozyme (T4L) doubly spin-labeled with the iodoacetamide derivative of DZD, we observe the increase in τrot and electron spin coherence time, Tm, along with the narrowing of interspin distance distributions. Sensitivity of the DEER measurements at 83 K increases by a factor 4-9, compared to the common spin label such as MTSL, which is not affected by CB-7. Interspin distances of 3 nm could be reliably measured in water/glycerol up to temperatures near the glass transition/melting temperature of the matrix at 200 K, thus bringing us closer to the goal of supramolecular recognition-enabled long-distance DEER measurements at near physiological temperatures. The X-ray structure of DZD-T4L 65 at 1.12 Å resolution allows for unambiguous modeling of the DZD label (0.88 occupancy), indicating an undisturbed structure and conformation of the protein.

Asymmetric conformations and lipid interactions shape the ATP-coupled cycle of a heterodimeric ABC transporter

Here we used cryo-electron microscopy (cryo-EM), double electron-electron resonance spectroscopy (DEER), and molecular dynamics (MD) simulations, to capture and characterize ATP- and substrate-bound inward-facing (IF) and occluded (OC) conformational states of the heterodimeric ATP binding cassette (ABC) multidrug exporter BmrCD in lipid nanodiscs. Supported by DEER analysis, the structures reveal that ATP-powered isomerization entails changes in the relative symmetry of the BmrC and BmrD subunits that propagates from the transmembrane domain to the nucleotide binding domain. The structures uncover asymmetric substrate and Mg2+ binding which we hypothesize are required for triggering ATP hydrolysis preferentially in one of the nucleotide-binding sites. MD simulations demonstrate that multiple lipid molecules differentially bind the IF versus the OC conformation thus establishing that lipid interactions modulate BmrCD energy landscape. Our findings are framed in a model that highlights the role of asymmetric conformations in the ATP-coupled transport with general implications to the mechanism of ABC transporters.

Structural Insights into the Binding and Degradation Mechanisms of Protoporphyrin IX by the Translocator Protein TSPO

The 18 kDa translocator protein (TSPO) has gained considerable attention as a clinical biomarker for neuroinflammation and a potential therapeutic target. However, the mechanisms by which TSPO associates with ligands, particularly the endogenous porphyrin ligand protoporphyrin IX (PpIX), remain poorly understood. In this study, we employed mutagenesis- and spectroscopy-based functional assays to investigate TSPO-mediated photo-oxidative degradation of PpIX and identify key residues involved in the reaction. We provide structural evidence using electron spin resonance, which sheds light on the highly conserved intracellular loop (LP1) connecting transmembrane 1 (TM1) and TM2. Our findings show that LP1 does not act as a lid to regulate ligand binding; instead, it interacts strongly with the TM3-TM4 linker (LP3) to stabilize the local structure of LP3. This LP1-LP3 interaction is crucial for maintaining the binding pocket structure, which is essential for proper ligand binding. Our results also demonstrate that PpIX accesses the pocket through the lipid bilayer without requiring conformational changes in TSPO. This study provides an improved understanding of TSPO-mediated PpIX degradation, highlighting potential therapeutic strategies to regulate the reaction.

SARS-CoV-2 fusion peptide sculpting of a membrane with insertion of charged and polar groups

The fusion peptide of SARS-CoV-2 spike is essential for infection. How this charged and hydrophobic domain occupies and affects membranes needs clarification. Its depth in zwitterionic, bilayered micelles at pH 5 (resembling late endosomes) was measured by paramagnetic NMR relaxation enhancements used to bias molecular dynamics simulations. Asp830 inserted deeply, along with Lys825 or Lys835. Protonation of Asp830 appeared to enhance agreement of simulated and NMR-measured depths. While the fusion peptide occupied a leaflet of the DMPC bilayer, the opposite leaflet invaginated with influx of water and choline head groups in around Asp830 and bilayer-inserted polar side chains. NMR-detected hydrogen exchange found corroborating hydration of the backbone of Thr827-Phe833 inserted deeply in bicelles. Pinching of the membrane at the inserted charge and the intramembrane hydration of polar groups agree with theory. Formation of corridors of hydrated, inward-turned head groups was accompanied by flip-flop of head groups. Potential roles of the defects are discussed.

Integrated AlphaFold2 and DEER investigation of the conformational dynamics of a pH-dependent APC antiporter

The Amino Acid-Polyamine-Organocation (APC) transporter GadC contributes to the survival of pathogenic bacteria under extreme acid stress by exchanging extracellular glutamate for intracellular γ-aminobutyric acid (GABA). Its structure, determined in an inward-facing conformation at alkaline pH, consists of the canonical LeuT-fold with a conserved five-helix inverted repeat, thereby resembling functionally divergent transporters such as the serotonin transporter SERT and the glucose-sodium symporter SGLT1. However, despite this structural similarity, it is unclear if the conformational dynamics of antiporters such as GadC follow the blueprint of these or other LeuT-fold transporters. Here, we used double electron-electron resonance (DEER) spectroscopy to monitor the conformational dynamics of GadC in lipid bilayers in response to acidification and substrate binding. To guide experimental design and facilitate the interpretation of the DEER data, we generated an ensemble of structural models in multiple conformations using a recently introduced modification of AlphaFold2 . Our experimental results reveal acid-induced conformational changes that dislodge the Cterminus from the permeation pathway coupled with rearrangement of helices that enables isomerization between inward- and outward-facing states. The substrate glutamate, but not GABA, modulates the dynamics of an extracellular thin gate without shifting the equilibrium between inward- and outward-facing conformations. In addition to introducing an integrated methodology for probing transporter conformational dynamics, the congruence of the DEER data with patterns of structural rearrangements deduced from ensembles of AlphaFold2 models illuminates the conformational cycle of GadC underpinning transport and exposes yet another example of the divergence between the dynamics of different families in the LeuT-fold.

OOP-ESEEM Spectroscopy: Accuracies of Distances of Spin-Correlated Radical Pairs in Biomolecules

In addition to the commonly used electron–electron double resonance (ELDOR) technique, there are several other electron paramagnetic resonance (EPR) methods by which structure information can be obtained by exploiting the dipolar coupling between two radicals based on its characteristic r⁻³ dependence. In this contribution, we explore the potential of out-of-phase-electron-spin echo envelope modulation (OOP-ESEEM) spectroscopy to collect accurate distance information in photo-sensitive (bio) molecules. Although the method has already been applied to spin-correlated radical pairs in several classes of light-active proteins, the accuracy of the information obtained has not yet been extensively evaluated. To do this in a system-independent fashion, OOP-ESEEM time traces simulated with different values of the dipolar and exchange couplings were generated and analyzed in a best-possible way. Excellent agreement between calculated and numerically fitted values over a wide range of distances (between 15 and 45 Å) was obtained. Furthermore, the limitations of the method and the dependence on various experimental parameters could be evaluated.

DEER Data Analysis Software: A Comparative Guide

Pulsed dipolar electron paramagnetic resonance (PDEPR) spectroscopy experiments measure the dipolar coupling, and therefore nanometer-scale distances and distance distributions, between paramagnetic centers. Of the family of PDEPR experiments, the most commonly used pulsed sequence is four-pulse double electron resonance (DEER, also known as PELDOR). There are several ways to analyze DEER data to extract distance distributions, and this may appear overwhelming at first. This work compares and reviews six of the packages, and a brief getting started guide for each is provided.

Force-Correction Analysis Method for Derivation of Multidimensional Free-Energy Landscapes from Adaptively Biased Replica Simulations

A methodology is proposed for the calculation of multidimensional free-energy landscapes of molecular systems, based on analysis of multiple molecular dynamics trajectories wherein adaptive biases have been applied to enhance the sampling of different collective variables. In this approach, which we refer to as the Force-Correction Analysis Method (FCAM), local averages of the total and biasing forces are evaluated post hoc, and the latter are subtracted from the former to obtain unbiased estimates of the mean force across collective-variable space. Multidimensional free-energy surfaces and minimum free-energy pathways are then derived by integrating the mean-force landscape with a kinetic Monte Carlo algorithm. To evaluate the proposed method, a series of numerical tests and comparisons with existing approaches were carried out for small molecules, peptides, and proteins, based on all-atom trajectories generated with standard, concurrent, and replica-exchange metadynamics in collective-variable spaces ranging from one to six dimensional. The tests confirm the correctness of the FCAM formulation and demonstrate that calculated mean forces and free energies converge rapidly and accurately, outperforming other methods used to unbias this kind of simulation data.

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. These guidelines are substantiated by a multi-laboratory benchmark study and by analysis of data sets with known distance distribution ground truth. The study and the guidelines focus on proteins labeled with nitroxides and on double electron-electron resonance (DEER aka PELDOR) measurements and provide suggestions on how to proceed analogously in other cases.

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

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.

Statistical analysis of ENDOR spectra

Electron-nuclear double resonance (ENDOR) measures the hyperfine interaction of magnetic nuclei with paramagnetic centers and is hence a powerful tool for spectroscopic investigations extending from biophysics to material science. Progress in microwave technology and the recent availability of commercial electron paramagnetic resonance (EPR) spectrometers up to an electron Larmor frequency of 263 GHz now open the opportunity for a more quantitative spectral analysis. Using representative spectra of a prototype amino acid radical in a biologically relevant enzyme, the [Formula: see text] in Escherichia coli ribonucleotide reductase, we developed a statistical model for ENDOR data and conducted statistical inference on the spectra including uncertainty estimation and hypothesis testing. Our approach in conjunction with ¹H/²H isotopic labeling of [Formula: see text] in the protein unambiguously established new unexpected spectral contributions. Density functional theory (DFT) calculations and ENDOR spectral simulations indicated that these features result from the beta-methylene hyperfine coupling and are caused by a distribution of molecular conformations, likely important for the biological function of this essential radical. The results demonstrate that model-based statistical analysis in combination with state-of-the-art spectroscopy accesses information hitherto beyond standard approaches.

Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER distance restraints

We describe an approach for integrating distance restraints from Double Electron-Electron Resonance (DEER) spectroscopy into Rosetta with the purpose of modeling alternative protein conformations from an initial experimental structure. Fundamental to this approach is a multilateration algorithm that harnesses sets of interconnected spin label pairs to identify optimal rotamer ensembles at each residue that fit the DEER decay in the time domain. Benchmarked relative to data analysis packages, the algorithm yields comparable distance distributions with the advantage that fitting the DEER decay and rotamer ensemble optimization are coupled. We demonstrate this approach by modeling the protonation-dependent transition of the multidrug transporter PfMATE to an inward facing conformation with a deviation to the experimental structure of less than 2Å Cα RMSD. By decreasing spin label rotamer entropy, this approach engenders more accurate Rosetta models that are also more closely clustered, thus setting the stage for more robust modeling of protein conformational changes.

Tuning flavin environment to detect and control light-induced conformational switching in Drosophila cryptochrome

Light-induction of an anionic semiquinone (SQ) flavin radical in Drosophila cryptochrome (dCRY) alters the dCRY conformation to promote binding and degradation of the circadian clock protein Timeless (TIM). Specific peptide ligation with sortase A attaches a nitroxide spin-probe to the dCRY C-terminal tail (CTT) while avoiding deleterious side reactions. Pulse dipolar electron-spin resonance spectroscopy from the CTT nitroxide to the SQ shows that flavin photoreduction shifts the CTT ~1 nm and increases its motion, without causing full displacement from the protein. dCRY engineered to form the neutral SQ serves as a dark-state proxy to reveal that the CTT remains docked when the flavin ring is reduced but uncharged. Substitutions of flavin-proximal His378 promote CTT undocking in the dark or diminish undocking in the light, consistent with molecular dynamics simulations and TIM degradation activity. The His378 variants inform on recognition motifs for dCRY cellular turnover and strategies for developing optogenetic tools.

Chandrasekaran et al. engineered the Drosophila circadian clock protein Cryptochrome (dCRY) to form the neutral semiquinone, which serves as a dark-state proxy. They find that the C-terminal tail of dCRY remains docked when the flavin ring is reduced but uncharged. dCRY His378 variants provide insights into the recognition motifs for dCRY turnover and strategies for optogenetic tools.

Conserved binding site in the N-lobe of prokaryotic MATE transporters suggests a role for Na+ in ion-coupled drug efflux

In both prokaryotes and eukaryotes, multidrug and toxic-compound extrusion (MATE) transporters catalyze the efflux of a broad range of cytotoxic compounds, including human-made antibiotics and anticancer drugs. MATEs are secondary-active antiporters, i.e., their drug-efflux activity is coupled to, and powered by, the uptake of ions down a preexisting transmembrane electrochemical gradient. Key aspects of this mechanism, however, remain to be delineated, such as its ion specificity and stoichiometry. We previously revealed the existence of a Na⁺-binding site in a MATE transporter from Pyroccocus furiosus (PfMATE) and hypothesized that this site might be broadly conserved among prokaryotic MATEs. Here, we evaluate this hypothesis by analyzing VcmN and ClbM, which along with PfMATE are the only three prokaryotic MATEs whose molecular structures have been determined at atomic resolution, i.e. better than 3 Å. Reinterpretation of existing crystallographic data and molecular dynamics simulations indeed reveal an occupied Na⁺-binding site in the N-terminal lobe of both structures, analogous to that identified in PfMATE. We likewise find this site to be strongly selective against K⁺, suggesting it is mechanistically significant. Consistent with these computational results, DEER spectroscopy measurements for multiple doubly-spin-labeled VcmN constructs demonstrate Na⁺-dependent changes in protein conformation. The existence of this binding site in three MATE orthologs implicates Na⁺ in the ion-coupled drug-efflux mechanisms of this class of transporters. These results also imply that observations of H⁺-dependent activity likely stem either from a site elsewhere in the structure, or from H⁺ displacing Na⁺ under certain laboratory conditions, as has been noted for other Na⁺-driven transport systems.

Interpreting Hydrogen-Deuterium Exchange Experiments with Molecular Simulations: Tutorials and Applications of the HDXer Ensemble Reweighting Software [Article v1.0]

Hydrogen-deuterium exchange (HDX) is a comprehensive yet detailed probe of protein structure and dynamics and, coupled to mass spectrometry, has become a powerful tool for investigating an increasingly large array of systems. Computer simulations are often used to help rationalize experimental observations of exchange, but interpretations have frequently been limited to simple, subjective correlations between microscopic dynamical fluctuations and the observed macroscopic exchange behavior. With this in mind, we previously developed the HDX ensemble reweighting approach and associated software, HDXer, to aid the objective interpretation of HDX data using molecular simulations. HDXer has two main functions; first, to compute H-D exchange rates that describe each structure in a candidate ensemble of protein structures, for example from molecular simulations, and second, to objectively reweight the conformational populations present in a candidate ensemble to conform to experimental exchange data. In this article, we first describe the HDXer approach, theory, and implementation. We then guide users through a suite of tutorials that demonstrate the practical aspects of preparing experimental data, computing HDX levels from molecular simulations, and performing ensemble reweighting analyses. Finally we provide a practical discussion of the capabilities and limitations of the HDXer methods including recommendations for a user's own analyses. Overall, this article is intended to provide an up-to-date, pedagogical counterpart to the software, which is freely available at https://github.com/Lucy-Forrest-Lab/HDXer.

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.

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. 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.

The Multidrug Transporter MdfA Deviates from the Canonical Model of Alternating Access of MFS Transporters

The prototypic multidrug (Mdr) transporter MdfA from Escherichia coli efflux chemically- dissimilar substrates in exchange for protons. Similar to other transporters, MdfA purportedly functions by alternating access of a central substrate binding pocket to either side of the membrane. Accordingly, MdfA should open at the cytoplasmic side and/or laterally toward the membrane to enable access of drugs into its pocket. At the end of the cycle, the periplasmic side is expected to open to release drugs. Two distinct conformations of MdfA have been captured by X-ray crystallography: An outward open (O_o) conformation, stabilized by a Fab fragment, and a ligand-bound inward-facing (I_f) conformation, possibly stabilized by a mutation (Q131R). Here, we investigated how these structures relate to ligand-dependent conformational dynamics of MdfA in lipid bilayers. For this purpose, we combined distances measured by double electron-electron resonance (DEER) between pairs of spin labels in MdfA, reconstituted in nanodiscs, with cysteine cross-linking of natively expressed membrane-embedded MdfA variants. Our results suggest that in a membrane environment, MdfA assumes a relatively flexible, outward-closed/inward-closed (O_c/I_c) conformation. Unexpectedly, our data show that neither the substrate TPP nor protonation induces large-scale conformational changes. Rather, we identified a substrate-responsive lateral gate, which is open toward the inner leaflet of the membrane but closes upon drug binding. Together, our results suggest a modified model for the functional conformational cycle of MdfA that does not invoke canonical elements of alternating access.

Bayesian Probabilistic Analysis of DEER Spectroscopy Data Using Parametric Distance Distribution Models

Double electron-electron resonance (DEER) spectroscopy measures distance distributions between spin labels in proteins, yielding important structural and energetic information about conformational landscapes. Analysis of an experimental DEER signal in terms of a distance distribution is a nontrivial task due to the ill-posed nature of the underlying mathematical inversion problem. This work introduces a Bayesian probabilistic inference approach to analyze DEER data, using a multi-Gauss mixture model for the distance distribution. The method uses Markov chain Monte Carlo (MCMC) sampling to determine a posterior probability distribution over model parameter space. This distribution contains all the information available from the data, including a full quantification of the uncertainty about the parameters. The corresponding uncertainty about the distance distribution is captured via an ensemble of posterior predictive distributions. Several synthetic examples illustrate the method. An experimental example shows the importance of model checking and comparison using residual analysis and Bayes factors. Overall, the Bayesian approach allows for more robust inference about protein conformations from DEER spectroscopy.

Supramolecular Approach to Electron Paramagnetic Resonance Distance Measurement of Spin-Labeled Proteins

We demonstrate a host-guest molecular recognition approach to advance double electron-electron resonance (DEER) distance measurements of spin-labeled proteins. We synthesized an iodoacetamide derivative of 2,6-diazaadamantane nitroxide (DZD) spin label that could be doubly incorporated into T4 Lysozyme (T4L) by site-directed spin labeling with efficiency up to 50% per cysteine. The rigidity of the fused ring structure and absence of mobile methyl groups increase the spin echo dephasing time (T_m) at temperatures above 80 K. This enables DEER measurements of distances >4 nm in DZD-labeled T4L in glycerol/water at temperatures up to 150 K with increased sensitivity compared to that of a common spin label such as MTSL. Addition of β-cyclodextrin reduces the rotational correlation time of the label, slightly increases T_m, and most importantly, narrows (and slightly lengthens) the interspin distance distributions. The distance distributions are in good agreement with simulated distance distributions obtained by rotamer libraries. These results provide a foundation for developing supramolecular recognition to facilitate long-distance DEER measurements at near physiological temperatures.

A CLC-ec1 mutant reveals global conformational change and suggests a unifying mechanism for the CLC Cl-/H+ transport cycle

Among coupled exchangers, CLCs uniquely catalyze the exchange of oppositely charged ions (Cl^– for H⁺). Transport-cycle models to describe and explain this unusual mechanism have been proposed based on known CLC structures. While the proposed models harmonize with many experimental findings, gaps and inconsistencies in our understanding have remained. One limitation has been that global conformational change – which occurs in all conventional transporter mechanisms – has not been observed in any high-resolution structure. Here, we describe the 2.6 Å structure of a CLC mutant designed to mimic the fully H⁺-loaded transporter. This structure reveals a global conformational change to improve accessibility for the Cl^– substrate from the extracellular side and new conformations for two key glutamate residues. Together with DEER measurements, MD simulations, and functional studies, this new structure provides evidence for a unified model of H⁺/Cl^– transport that reconciles existing data on all CLC-type proteins.

Cells are shielded from harmful molecules and other threats by a thin, flexible layer called the membrane. However, this barrier also prevents chloride, sodium, protons and other ions from moving in or out of the cell. Channels and transporters are two types of membrane proteins that form passageways for these charged particles.

Channels let ions flow freely from one side of the membrane to the other. To do so, these proteins change their three-dimensional shape to open or close as needed. On the other hand, transporters actively pump ions across the membrane to allow the charged particles to accumulate on one side. The shape changes needed for that type of movement are different: the transporters have to open a passageway on one side of the membrane while closing it on the other side, alternating openings to one side or the other.

In general, channels and transporters are not related to each other, but one exception is a group called CLCs proteins. Present in many organisms, this family contains a mixture of channels and transporters. For example, humans have nine CLC proteins: four are channels that allow chloride ions in and out, and five are ‘exchange transporters’ that make protons and chloride ions cross the membrane in opposite directions. These proteins let one type of charged particle move freely across the membrane, which generates energy that the transporter then uses to actively pump the other ion in the direction needed by the cell. Yet, the exact three-dimensional changes required for CLC transporters and channels to perform their roles are still unknown.

To investigate this question, Chavan, Cheng et al. harnessed a technique called X-ray crystallography, which allows scientists to look at biological molecules at the level of the atom. This was paired with other methods to examine a CLC mutant that adopts the shape of a normal CLC transporter when it is loaded with a proton. The experiments revealed how various elements in the transporter move relative to each other to adopt a structure that allows protons and chloride ions to enter the protein from opposite sides of the membrane, using separate pathways. While obtained on a bacterial CLC, these results can be applied to other CLC channels and transporters (including those in humans), shedding light on how this family transports charged particles across membranes.

From bone diseases to certain types of seizures, many human conditions are associated with poorly functioning CLCs. Understanding the way these structures change their shapes to perform their roles could help to design new therapies for these health problems.

Interpretation of HDX Data by Maximum-Entropy Reweighting of Simulated Structural Ensembles

Hydrogen-deuterium exchange combined with mass spectrometry (HDX-MS) is a widely applied biophysical technique that probes the structure and dynamics of biomolecules without the need for site-directed modifications or bio-orthogonal labels. The mechanistic interpretation of HDX data, however, is often qualitative and subjective, owing to a lack of quantitative methods to rigorously translate observed deuteration levels into atomistic structural information. To help address this problem, we have developed a methodology to generate structural ensembles that faithfully reproduce HDX-MS measurements. In this approach, an ensemble of protein conformations is first generated, typically using molecular dynamics simulations. A maximum-entropy bias is then applied post hoc to the resulting ensemble such that averaged peptide-deuteration levels, as predicted by an empirical model, agree with target values within a given level of uncertainty. We evaluate this approach, referred to as HDX ensemble reweighting (HDXer), for artificial target data reflecting the two major conformational states of a binding protein. We demonstrate that the information provided by HDX-MS experiments and by the model of exchange are sufficient to recover correctly weighted structural ensembles from simulations, even when the relevant conformations are rarely observed. Degrading the information content of the target data—e.g., by reducing sequence coverage, by averaging exchange levels over longer peptide segments, or by incorporating different sources of uncertainty—reduces the structural accuracy of the reweighted ensemble but still allows for useful insights into the distinctive structural features reflected by the target data. Finally, we describe a quantitative metric to rank candidate structural ensembles according to their correspondence with target data and illustrate the use of HDXer to describe changes in the conformational ensemble of the membrane protein LeuT. In summary, HDXer is designed to facilitate objective structural interpretations of HDX-MS data and to inform experimental approaches and further developments of theoretical exchange models.

Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction

Despite advances in sampling and scoring strategies, Monte Carlo modeling methods still struggle to accurately predict de novo the structures of large proteins, membrane proteins, or proteins of complex topologies. Previous approaches have addressed these shortcomings by leveraging sparse distance data gathered using site-directed spin labeling and electron paramagnetic resonance spectroscopy to improve protein structure prediction and refinement outcomes. However, existing computational implementations entail compromises between coarse-grained models of the spin label that lower the resolution and explicit models that lead to resource-intense simulations. These methods are further limited by their reliance on distance distributions, which are calculated from a primary refocused echo decay signal and contain uncertainties that may require manual refinement. Here, we addressed these challenges by developing RosettaDEER, a scoring method within the Rosetta software suite capable of simulating double electron-electron resonance spectroscopy decay traces and distance distributions between spin labels fast enough to fold proteins de novo. We demonstrate that the accuracy of resulting distance distributions match or exceed those generated by more computationally intensive methods. Moreover, decay traces generated from these distributions recapitulate intermolecular background coupling parameters even when the time window of data collection is truncated. As a result, RosettaDEER can discriminate between poorly folded and native-like models by using decay traces that cannot be accurately converted into distance distributions using regularized fitting approaches. Finally, using two challenging test cases, we demonstrate that RosettaDEER leverages these experimental data for protein fold prediction more effectively than previous methods. These benchmarking results confirm that RosettaDEER can effectively leverage sparse experimental data for a wide array of modeling applications built into the Rosetta software suite.

Mechanism of allosteric modulation of P-glycoprotein by transport substrates and inhibitors

The ATP-binding cassette subfamily B member 1 (ABCB1) multidrug transporter P-glycoprotein plays a central role in clearance of xenobiotics in humans and is implicated in cancer resistance to chemotherapy. We used double electron electron resonance spectroscopy to uncover the basis of stimulation of P-glycoprotein adenosine 5'-triphosphate (ATP) hydrolysis by multiple substrates and illuminate how substrates and inhibitors differentially affect its transport function. Our results reveal that substrate-induced acceleration of ATP hydrolysis correlates with stabilization of a high-energy, post-ATP hydrolysis state characterized by structurally asymmetric nucleotide-binding sites. By contrast, this state is destabilized in the substrate-free cycle and by high-affinity inhibitors in favor of structurally symmetric nucleotide binding sites. Together with previous data, our findings lead to a general model of substrate and inhibitor coupling to P-glycoprotein.

CHARMM-GUI DEER facilitator for spin-pair distance distribution calculations and preparation of restrained-ensemble molecular dynamics simulations

The double electron-electron resonance (DEER) is a powerful structural biology technique to obtain distance information in the range of 18 to 80 å by measuring the dipolar coupling between two unpaired electron spins. The distance distributions obtained from the experiment provide valuable structural information about the protein in its native environment that can be exploited using restrained ensemble molecular dynamics (reMD) simulations. We present a new tool DEER Facilitator in CHARMM-GUI that consists of two modules Spin-Pair Distributor and reMD Prepper to setup simulations that utilize information from DEER experiments. Spin-Pair Distributor provides a web-based interface to calculate the spin-pair distance distribution of labeled sites in a protein using MD simulations. The calculated distribution can be used to guide the selection of the labeling sites in experiments as well as validate different protein structure models. reMD Prepper facilities the setup of reMD simulations using different types of spin labels in four different environments including vacuum, solution, micelle, and bilayer. The applications of these two modules are demonstrated with several test cases. Spin-Pair Distributor and reMD Prepper are available at http://www.charmm-gui.org/input/deer and http://www.charmm-gui.org/input/deerre. DEER Facilitator is expected to facilitate advanced biomolecular modeling and simulation, thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems based on experimental DEER data. © 2019 Wiley Periodicals, Inc.

Interpretation of spectroscopic data using molecular simulations for the secondary active transporter BetP

Mechanistic understanding of dynamic membrane proteins such as transporters, receptors, and channels requires accurate depictions of conformational ensembles, and the manner in which they interchange as a function of environmental factors including substrates, lipids, and inhibitors. Spectroscopic techniques such as electron spin resonance (ESR) pulsed electron-electron double resonance (PELDOR), also known as double electron-electron resonance (DEER), provide a complement to atomistic structures obtained from x-ray crystallography or cryo-EM, since spectroscopic data reflect an ensemble and can be measured in more native solvents, unperturbed by a crystal lattice. However, attempts to interpret DEER data are frequently stymied by discrepancies with the structural data, which may arise due to differences in conditions, the dynamics of the protein, or the flexibility of the attached paramagnetic spin labels. Recently, molecular simulation techniques such as EBMetaD have been developed that create a conformational ensemble matching an experimental distance distribution while applying the minimal possible bias. Moreover, it has been proposed that the work required during an EBMetaD simulation to match an experimentally determined distribution could be used as a metric with which to assign conformational states to a given measurement. Here, we demonstrate the application of this concept for a sodium-coupled transport protein, BetP. Because the probe, protein, and lipid bilayer are all represented in atomic detail, the different contributions to the work, such as the extent of protein backbone movements, can be separated. This work therefore illustrates how ranking simulations based on EBMetaD can help to bridge the gap between structural and biophysical data and thereby enhance our understanding of membrane protein conformational mechanisms.

Singular Value Decomposition Method To Determine Distance Distributions in Pulsed Dipolar Electron Spin Resonance: II. Estimating Uncertainty

This paper is a continuation of the method introduced by Srivastava and Freed (2017) that is a new method based on truncated singular value decomposition (TSVD) for obtaining physical results from experimental signals without any need for Tikhonov regularization or other similar methods that require a regularization parameter. We show here how to estimate the uncertainty in the SVD-generated solutions. The uncertainty in the solution may be obtained by finding the minimum and maximum values over which the solution remains converged. These are obtained from the optimum range of singular value contributions, where the width of this region depends on the solution point location (e.g., distance) and the signal-to-noise ratio (SNR) of the signal. The uncertainty levels typically found are very small with substantial SNR of the (denoised) signal, emphasizing the reliability of the method. With poorer SNR, the method is still satisfactory but with greater uncertainty, as expected. Pulsed dipolar electron spin resonance spectroscopy experiments are used as an example, but this TSVD approach is general and thus applicable to any similar experimental method wherein singular matrix inversion is needed to obtain the physically relevant result. We show that the Srivastava-Freed TSVD method along with the estimate of uncertainty can be effectively applied to pulsed dipolar electron spin resonance signals with SNR > 30, and even for a weak signal (e.g., SNR ≈ 3) reliable results are obtained by this method, provided the signal is first denoised using wavelet transforms (WavPDS).

Precision DEER Distances from Spin-Label Ensemble Refinement

Double electron-electron resonance (DEER) experiments probe nanometer-scale distances in spin-labeled proteins and nucleic acids. Rotamer libraries of the covalently attached spin-labels help reduce position uncertainties. Here we show that rotamer reweighting is essential for precision distance measurements, making it possible to resolve Ångstrom-scale domain motions. We analyze extensive DEER measurements on the three N-terminal polypeptide transport-associated (POTRA) domains of the outer membrane protein Omp85. Using the "Bayesian inference of ensembles" maximum-entropy method, we extract rotamer weights from the DEER measurements. Small weight changes suffice to eliminate otherwise significant discrepancies between experiments and model and unmask 1-3 Å domain motions relative to the crystal structure. Rotamer-weight refinement is a simple yet powerful tool for precision distance measurements that should be broadly applicable to label-based measurements including DEER, paramagnetic relaxation enhancement, and fluorescence resonance energy transfer (FRET).