Structural refinement from restrained-ensemble simulations based on EPR/DEER data: application to T4 lysozyme

Designing surface exposed sites on Bacillus subtilis lipase A for spin-labeling and hydration studies

Spin-labeling with electron paramagnetic resonance spectroscopy (EPR) is a facile method for interrogating macromolecular flexibility, conformational changes, accessibility, and hydration. Within we present a computationally based approach for the rational selection of reporter sites in Bacillus subtilis lipase A (BSLA) for substitution to cysteine residues with subsequent modification with a spin-label that are expected to not significantly perturb the wild-type structure, dynamics, or enzymatic function. Experimental circular dichroism spectroscopy, Michaelis-Menten kinetic parameters and EPR spectroscopy data validate the success of this approach to computationally select reporter sites for future magnetic resonance investigations of hydration and hydration changes induced by polymer conjugation, tethering, immobilization, or amino acid substitution in BSLA. Analysis of molecular dynamic simulations of the impact of substitutions on the secondary structure agree well with experimental findings. We propose that this computationally guided approach for choosing spin-labeled EPR reporter sites, which evaluates relative surface accessibility coupled with hydrogen bonding occupancy of amino acids to the catalytic pocket via atomistic simulations, should be readily transferable to other macromolecular systems of interest including selecting sites for paramagnetic relaxation enhancement NMR studies, other spin-labeling EPR studies or any method requiring a tagging method where it is desirable to not alter enzyme stability or activity.

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.

DEERefiner-assisted structural refinement using pulsed dipolar spectroscopy: a study on multidrug transporter LmrP

Pulsed dipolar spectroscopy, such as double electron-electron resonance (DEER), has been underutilized in protein structure determination, despite its ability to provide valuable spatial information. In this study, we present DEERefiner, a user-friendly MATLAB-based GUI program that enables the modeling of protein structures by combining an initial structure and DEER distance restraints. We illustrate the effectiveness of DEERefiner by successfully modeling the ligand-dependent conformational changes of the proton-drug antiporter LmrP to an extracellular-open-like conformation with an impressive precision of 0.76 Å. Additionally, DEERefiner was able to uncover a previously hypothesized but experimentally unresolved proton-dependent conformation of LmrP, characterized as an extracellular-closed/partially intracellular-open conformation, with a precision of 1.16 Å. Our work not only highlights the ability of DEER spectroscopy to model protein structures but also reveals the potential of DEERefiner to advance the field by providing an accessible and applicable tool for precise protein structure modeling, thereby paving the way for deeper insights into protein function.

A novel approach to modeling side chain ensembles of the bifunctional spin label RX

We introduce a novel approach to modeling side chain ensembles of bifunctional spin labels. This approach utilizes rotamer libraries to generate side chain conformational ensembles. Because the bifunctional label is constrained by two attachment sites, the label is split into two monofunctional rotamers which are first attached to their respective sites, then rejoined by a local optimization in dihedral space. We validate this method against a set of previously published experimental data using the bifunctional spin label, RX. This method is relatively fast and can readily be used for both experimental analysis and protein modeling, providing significant advantages over modeling bifunctional labels with molecular dynamics simulations. Use of bifunctional labels for site directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy dramatically reduces label mobility, which can significantly improve resolution of small changes in protein backbone structure and dynamics. Coupling the use of bifunctional labels with side chain modeling methods allows for improved quantitative application of experimental SDSL EPR data to protein modeling.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Reconciling membrane protein simulations with experimental DEER spectroscopy data

Spectroscopy experiments are crucial to study membrane proteins for which traditional structure determination methods still prove challenging. Double electron-electron resonance (DEER) spectroscopy experiments provide protein residue-pair distance distributions that are indicative of their conformational heterogeneity. Atomistic molecular dynamics (MD) simulations are another tool that have been proven to be vital to study the structural dynamics of membrane proteins such as to identify inward-open, occluded, and outward-open conformations of transporter membrane proteins, among other partially open or closed states of the protein. Yet, studies have reported that there is no direct consensus between the distributional data from DEER experiments and MD simulations, which has challenged validation of structures obtained from long-timescale simulations and using simulations to design experiments. Current coping strategies for comparisons rely on heuristics, such as mapping the nearest matching peaks between two ensembles or biased simulations. Here we examine the differences in residue-pair distance distributions arising due to the choice of membranes around the protein and covalent modification of a pair of residues to nitroxide spin labels in DEER experiments. Through comparing MD simulations of two proteins, PepT_So and LeuT-both of which have been characterized using DEER experiments previously-we show that the proteins' dynamics are similar despite the choice of the detergent micelle as a membrane mimetic in DEER experiments. On the other hand, covalently modified residues show slight local differences in their dynamics and a huge divergence when the oxygen atom pair distances between spin labeled residues are measured rather than protein backbone distances. Given the computational expense associated with pairwise MTSSL labeled MD simulations, we examine the use of biased simulations to explore the conformational dynamics of the spin labels only to reveal that such simulations alter the underlying protein dynamics. Our study identifies the main cause for the mismatch between DEER experiments and MD simulations and will accelerate the development of potential mitigation strategies to improve the match.

Copper coordination states affect the flexibility of copper Metallochaperone Atox1: Insights from molecular dynamics simulations

Copper is an essential element in nature but in excess, it is toxic to the living cell. The human metallochaperone Atox1 participates in copper homeostasis and is responsible for copper transmission. In a previous multiscale simulation study, we noticed a change in the coordination state of the Cu(I) ion, from 4 bound cysteine residues to 3, in agreement with earlier studies. Here, we perform and analyze classical molecular dynamic simulations of various coordination states: 2, 3, and 4. The main observation is an increase in protein flexibility as a result of a decrease in the coordination state. In addition, we identified several populated conformations that correlate well with double electron-electron resonance distance distributions or an X-ray structure of Cu(I)-bound Atox1. We suggest that the increased flexibility might benefit the process of ion transmission between interacting proteins. Further experiments can scrutinize this hypothesis and shed additional light on the mechanism of action of Atox1.

Comparative evaluation of spin-label modeling methods for protein structural studies

Site-directed spin-labeling electron paramagnetic resonance spectroscopy is a powerful technique for the investigation of protein structure and dynamics. Accurate spin-label modeling methods are essential to make full quantitative use of site-directed spin-labeling electron paramagnetic resonance data for protein modeling and model validation. Using a set of double electron-electron resonance data from seven different site pairs on maltodextrin/maltose-binding protein under two different conditions using five different spin labels, we compare the ability of two widely used spin-label modeling methods, based on accessible volume sampling and rotamer libraries, to predict experimental distance distributions. We present a spin-label modeling approach inspired by canonical side-chain modeling methods and compare modeling accuracy with the established methods.

Proton-driven alternating access in a spinster lipid transporter

Spinster (Spns) lipid transporters are critical for transporting sphingosine-1-phosphate (S1P) across cellular membranes. In humans, Spns2 functions as the main S1P transporter in endothelial cells, making it a potential drug target for modulating S1P signaling. Here, we employed an integrated approach in lipid membranes to identify unknown conformational states of a bacterial Spns from Hyphomonas neptunium (HnSpns) and to define its proton- and substrate-coupled conformational dynamics. Our systematic study reveals conserved residues critical for protonation steps and their regulation, and how sequential protonation of these proton switches coordinates the conformational transitions in the context of a noncanonical ligand-dependent alternating access. A conserved periplasmic salt bridge (Asp60^TM2:Arg289^TM7) keeps the transporter in a closed conformation, while proton-dependent conformational dynamics are significantly enhanced on the periplasmic side, providing a pathway for ligand exchange.

The Spns lipid transporters use ion gradients to drive substrate transport, including bioactive sphingolipids. Here, Dastvan et al. investigated how binding of protons powers the conformational changes that enable broad transport by a bacterial Spns.

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.

Modeling of protein conformational changes with Rosetta guided by limited experimental data

Conformational changes are an essential component of functional cycles of many proteins, but their characterization often requires an integrative structural biology approach. Here, we introduce and benchmark ConfChangeMover (CCM), a new method built into the widely used macromolecular modeling suite Rosetta that is tailored to model conformational changes in proteins using sparse experimental data. CCM can rotate and translate secondary structural elements and modify their backbone dihedral angles in regions of interest. We benchmarked CCM on soluble and membrane proteins with simulated Cα-Cα distance restraints and sparse experimental double electron-electron resonance (DEER) restraints, respectively. In both benchmarks, CCM outperformed state-of-the-art Rosetta methods, showing that it can model a diverse array of conformational changes. In addition, the Rosetta framework allows a wide variety of experimental data to be integrated with CCM, thus extending its capability beyond DEER restraints. This method will contribute to the biophysical characterization of protein dynamics.

Simulation-based inference with approximately correct parameters via maximum entropy

Inferring the input parameters of simulators from observations is a crucial challenge with applications from epidemiology to molecular dynamics. Here we show a simple approach in the regime of sparse data and approximately correct models, which is common when trying to use an existing model to infer latent variables with observed data. This approach is based on the principle of maximum entropy (MaxEnt) and provably makes the smallest change in the latent joint distribution to fit new data. This method requires no likelihood or model derivatives and its fit is insensitive to prior strength, removing the need to balance observed data fit with prior belief. The method requires the ansatz that data is fit in expectation, which is true in some settings and may be reasonable in all settings with few data points. The method is based on sample reweighting, so its asymptotic run time is independent of prior distribution dimension. We demonstrate this MaxEnt approach and compare with other likelihood-free inference methods across three systems: a point particle moving in a gravitational field, a compartmental model of epidemic spread and molecular dynamics simulation of a protein.

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Molecular Dynamics Simulations of the Apo and Holo States of the Copper Binding Protein CueR Reveal Principal Bending and Twisting Motions

Copper is essential for proper functioning of cells but is dangerous in unregulated concentrations. One of the members in the bacterial system responsible for facilitating copper homeostasis is the copper efflux regulator (CueR) protein. Upon copper binding, CueR induces transcription of additional copper homeostasis proteins via a cascade of events. There are some available crystal structures of CueR, in the holo (copper-bound), active (copper- and DNA-bound), and repressed (only DNA-bound) states, and these structures suggest that transcription initiation involves a distortion in the promoter DNA strand. In this work, we study the dynamic behavior of the protein, using molecular dynamics simulations, and compare with available electron paramagnetic resonance measurements for validation. We develop simple force-field parameters to describe the copper-binding motif, thus enabling the use of simplified, classical physics equations. This enabled us to access reasonable simulation times that illustrate global motions of the protein. Both in the holo and apo states of CueR, we observed large-scale helical bending motions that could be involved in the bending of a bound DNA molecule so that transcription activation can take place. Additionally, copper binding might afford increased rigidification of the active state via helix α6.

An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling

Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining sparse paramagnetic NMR with physical modelling to infer approximate protein structural ensembles. We use calmodulin in complex with the smooth muscle myosin light chain kinase peptide as a model system. Despite acquiring data from samples labeled only at the backbone amide positions, we are able to produce an ensemble with an average RMSD of ∼2.8 Å from a reference X-ray crystal structure. Our approach requires only backbone chemical shifts and measurements of the paramagnetic relaxation enhancement and residual dipolar couplings that can be obtained from sparsely labeled samples.

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.

Structure and regulation of the BsYetJ calcium channel in lipid nanodiscs

BsYetJ is a bacterial homolog of transmembrane BAX inhibitor-1 motif-containing 6 (TMBIM6) membrane protein that plays a key role in the control of calcium homeostasis. However, the BsYetJ (or TMBIM6) structure embedded in a lipid bilayer is uncharacterized, let alone the molecular mechanism of the calcium transport activity. Herein, we report structures of BsYetJ in lipid nanodiscs identified by double electron-electron resonance spectroscopy. Our results reveal that BsYetJ in lipid nanodiscs is structurally different from those crystallized in detergents. We show that BsYetJ conformation is pH-sensitive in apo state (lacking calcium), whereas in a calcium-containing solution it is stuck in an intermediate, inert to pH changes. Only when the transmembrane calcium gradient is established can the calcium-release activity of holo-BsYetJ occur and be mediated by pH-dependent conformational changes, suggesting a dual gating mechanism. Conformational substates involved in the process and a key residue D171 relevant to the gating of calcium are identified. Our study suggests that BsYetJ/TMBIM6 is a pH-dependent, voltage-gated calcium channel.

A Disorder-to-Order Transition Activates an ATP-Independent Membrane Protein Chaperone

The 43 kDa subunit of the chloroplast signal recognition particle, cpSRP43, is an ATP-independent chaperone essential for the biogenesis of the light harvesting chlorophyll-binding proteins (LHCP), the most abundant membrane protein family on earth. cpSRP43 is activated by a stromal factor, cpSRP54, to more effectively capture and solubilize LHCPs. The molecular mechanism underlying this chaperone activation is unclear. Here, a combination of hydrogen-deuterium exchange, electron paramagnetic resonance, and NMR spectroscopy experiments reveal that a disorder-to-order transition of the ankyrin repeat motifs in the substrate binding domain of cpSRP43 drives its activation. An analogous coil-to-helix transition in the bridging helix, which connects the ankyrin repeat motifs to the cpSRP54 binding site in the second chromodomain, mediates long-range allosteric communication of cpSRP43 with its activating binding partner. Our results provide a molecular model to explain how the conformational dynamics of cpSRP43 enables regulation of its chaperone activity and suggest a general mechanism by which ATP-independent chaperones with cooperatively folding domains can be regulated.

Molecular Dynamics Simulations Based on Newly Developed Force Field Parameters for Cu2+ Spin Labels Provide Insights into Double-Histidine-Based Double Electron-Electron Resonance

Electron paramagnetic resonance (EPR) in combination with the recently developed double-histidine (dHis)-based Cu²⁺ spin labeling has provided valuable insights into protein structure and conformational dynamics. To relate sparse distance constraints measured by EPR to protein fluctuations in solution, modeling techniques are needed. In this work, we have developed force field parameters for Cu²⁺-nitrilotriacetic and Cu²⁺-iminodiacetic acid spin labels. We employed molecular dynamics (MD) simulations to capture the atomic-level details of dHis-labeled protein fluctuations. The interspin distances extracted from 200 ns MD trajectories show good agreement with the experimental results. The MD simulations also illustrate the dramatic rigidity of the Cu²⁺ labels compared to the standard nitroxide spin label. Further, the relative orientations between spin-labeled sites were measured to provide insight into the use of double electron-electron resonance (DEER) methods for such labels. The relative mean angles, as well as the standard deviations of the relative angles, agree well in general with the spectral simulations published previously. The fluctuations of relative orientations help rationalize why orientation selectivity effects are minimal at X-band frequencies, but observable at the Q-band for such labels. In summary, the results show that by combining the experimental results with MD simulations precise information about protein conformations as well as flexibility can be obtained.

Resolving dynamics and function of transient states in single enzyme molecules

We use a hybrid fluorescence spectroscopic toolkit to monitor T4 Lysozyme (T4L) in action by unraveling the kinetic and dynamic interplay of the conformational states. In particular, by combining single-molecule and ensemble multiparameter fluorescence detection, EPR spectroscopy, mutagenesis, and FRET-positioning and screening, and other biochemical and biophysical tools, we characterize three short-lived conformational states over the ns-ms timescale. The use of 33 FRET-derived distance sets, to screen available T4L structures, reveal that T4L in solution mainly adopts the known open and closed states in exchange at 4 µs. A newly found minor state, undisclosed by, at present, more than 500 crystal structures of T4L and sampled at 230 µs, may be actively involved in the product release step in catalysis. The presented fluorescence spectroscopic toolkit will likely accelerate the development of dynamic structural biology by identifying transient conformational states that are highly abundant in biology and critical in enzymatic reactions.

T4 Lysozyme (T4L) is a model protein whose structure is extensively studied. Here the authors combine single-molecule and ensemble FRET measurements, FRET-positioning and screening and EPR spectroscopy to study the structural dynamics of T4L and describe its conformational landscape during the catalytic cycle by an extended Michaelis–Menten mechanism and identify an excited conformational state of the enzyme.

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.

Pulse EPR in biological systems - Beyond the expert's courtyard

Application of EPR to biological systems includes many techniques and applications. In this short perspective, which dares to look into the future, I focus on pulse EPR, which is my field of expertise. Generally, pulse EPR techniques can be divided into two main groups: (1) hyperfine spectroscopy, which explores electron-nuclear interactions, and (2) pulse-dipolar (PD) EPR spectroscopy, which is based on electron-electron spin interactions. Here I focus on PD-EPR because it has a better chance of becoming a widely applied, easy-to-use table-top method to study the structural and dynamic aspects of bio-molecules. I will briefly introduce this technique, its current state of the art, the challenges it is facing, and finally I will describe futuristic scenarios of low-cost PD-EPR approaches that can cross the diffusion barrier from the core of experts to the bulk of the scientific community.

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.

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).

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

Given its ability to measure multicomponent distance distributions between electron-spin probes, double electron-electron resonance (DEER) spectroscopy has become a leading technique to assess the structural dynamics of biomolecules. However, methodologies to evaluate the statistical error of these distributions are not standard, often hampering a rigorous interpretation of the experimental results. Distance distributions are often determined from the experimental DEER data through a mathematical method known as Tikhonov regularization, but this approach makes rigorous error estimates difficult. Here, we build upon an alternative, model-based approach in which the distance probability distribution is represented as a sum of Gaussian components, and use propagation of errors to calculate an associated confidence band. Our approach considers all sources of uncertainty, including the experimental noise, the uncertainty in the fitted background signal, and the limited time span of the data collection. The resulting confidence band reveals the most and least reliable features of the probability distribution, thereby informing the structural interpretation of DEER experiments. To facilitate this interpretation, we also generalize the molecular simulation method known as ensemble-biased metadynamics (EBMetaD). This method, originally designed to generate maximal-entropy structural ensembles consistent with one or more probability distributions, now also accounts for the uncertainty in those target distributions exactly as dictated by their confidence bands. After careful benchmarks, we demonstrate the proposed techniques using DEER results from spin-labeled T4 lysozyme.

Molecular dynamics ensemble refinement of the heterogeneous native state of NCBD using chemical shifts and NOEs

Many proteins display complex dynamical properties that are often intimately linked to their biological functions. As the native state of a protein is best described as an ensemble of conformations, it is important to be able to generate models of native state ensembles with high accuracy. Due to limitations in sampling efficiency and force field accuracy it is, however, challenging to obtain accurate ensembles of protein conformations by the use of molecular simulations alone. Here we show that dynamic ensemble refinement, which combines an accurate atomistic force field with commonly available nuclear magnetic resonance (NMR) chemical shifts and NOEs, can provide a detailed and accurate description of the conformational ensemble of the native state of a highly dynamic protein. As both NOEs and chemical shifts are averaged on timescales up to milliseconds, the resulting ensembles reflect the structural heterogeneity that goes beyond that probed, e.g., by NMR relaxation order parameters. We selected the small protein domain NCBD as object of our study since this protein, which has been characterized experimentally in substantial detail, displays a rich and complex dynamical behaviour. In particular, the protein has been described as having a molten-globule like structure, but with a relatively rigid core. Our approach allowed us to describe the conformational dynamics of NCBD in solution, and to probe the structural heterogeneity resulting from both short- and long-timescale dynamics by the calculation of order parameters on different time scales. These results illustrate the usefulness of our approach since they show that NCBD is rather rigid on the nanosecond timescale, but interconverts within a broader ensemble on longer timescales, thus enabling the derivation of a coherent set of conclusions from various NMR experiments on this protein, which could otherwise appear in contradiction with each other.

Slow Dynamics around a Protein and Its Coupling to Solvent

Solvent is essential for protein dynamics and function, but its role in regulating the dynamics remains debated. Here, we employ saturation transfer electron spin resonance (ST-ESR) to explore the issue and characterize the dynamics on a longer (from μs to s) time scale than has been extensively studied. We first demonstrate the reliability of ST-ESR by showing that the dynamical changeovers revealed in the spectra agree to liquid-liquid transition (LLT) in the state diagram of the glycerol/water system. Then, we utilize ST-ESR with four different probes to systematically map out the variation in local (site-specific) dynamics around a protein surface at subfreezing temperatures (180-240 K) in 10 mol % glycerol/water mixtures. At highly exposed sites, protein and solvent dynamics are coupled, whereas they deviate from each other when temperature is greater than LLT temperature (∼190 K) of the solvent. At less exposed sites, protein however exhibits a dynamic, which is distinct from the bulk solvent, throughout the temperature range studied. Dominant dynamic components are thus revealed, showing that (from low to high temperatures) the overall structural fluctuation, rotamer dynamics, and internal side-chain dynamics, in turn, dominate the temperature dependence of spin-label motions. The structural fluctuation component is relatively slow, collective, and independent of protein structural segments, which is thus inferred to a fundamental dynamic component intrinsic to protein. This study corroborates that bulk solvent plasticizes protein and facilitates rather than slaves protein dynamics.

Conformational transitions of the sodium-dependent sugar transporter, vSGLT

Sodium-dependent transporters couple the flow of Na+ ions down their electrochemical potential gradient to the uphill transport of various ligands. Many of these transporters share a common core structure composed of a five-helix inverted repeat and deliver their cargo utilizing an alternating-access mechanism. A detailed characterization of inward-facing conformations of the Na+-dependent sugar transporter from Vibrio parahaemolyticus (vSGLT) has previously been reported, but structural details on additional conformations and on how Na+ and ligand influence the equilibrium between other states remains unknown. Here, double electron-electron resonance spectroscopy, structural modeling, and molecular dynamics are utilized to deduce ligand-dependent equilibria shifts of vSGLT in micelles. In the absence and presence of saturating amounts of Na+, vSGLT favors an inward-facing conformation. Upon binding both Na+ and sugar, the equilibrium shifts toward either an outward-facing or occluded conformation. While Na+ alone does not stabilize the outward-facing state, gating charge calculations together with a kinetic model of transport suggest that the resting negative membrane potential of the cell, absent in detergent-solubilized samples, may stabilize vSGLT in an outward-open conformation where it is poised for binding external sugars. In total, these findings provide insights into ligand-induced conformational selection and delineate the transport cycle of vSGLT.

The contribution of modern EPR to structural biology

Electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labelling is applicable to biomolecules and their complexes irrespective of system size and in a broad range of environments. Neither short-range nor long-range order is required to obtain structural restraints on accessibility of sites to water or oxygen, on secondary structure, and on distances between sites. Many of the experiments characterize a static ensemble obtained by shock-freezing. Compared with characterizing the dynamic ensemble at ambient temperature, analysis is simplified and information loss due to overlapping timescales of measurement and system dynamics is avoided. The necessity for labelling leads to sparse restraint sets that require integration with data from other methodologies for building models. The double electron–electron resonance experiment provides distance distributions in the nanometre range that carry information not only on the mean conformation but also on the width of the native ensemble. The distribution widths are often inconsistent with Anfinsen's concept that a sequence encodes a single native conformation defined at atomic resolution under physiological conditions.

Determination of helix orientations in a flexible DNA by multi-frequency EPR spectroscopy

Distance measurements are performed between a pair of spin labels attached to nucleic acids using Pulsed Electron-Electron Double Resonance (PELDOR, also called DEER) spectroscopy which is a complementary tool to other structure determination methods in structural biology. The rigid spin label Ç, when incorporated pairwise into two helical parts of a nucleic acid molecule, allows the determination of both the mutual orientation and the distance between those labels, since Ç moves rigidly with the helix to which it is attached. We have developed a two-step protocol to investigate the conformational flexibility of flexible nucleic acid molecules by multi-frequency PELDOR. In the first step, a library with a broad collection of conformers, which are in agreement with topological constraints, NMR restraints and distances derived from PELDOR, was created. In the second step, a weighted structural ensemble of these conformers was chosen, such that it fits the multi-frequency PELDOR time traces of all doubly Ç-labelled samples simultaneously. This ensemble reflects the global structure and the conformational flexibility of the two-way DNA junction. We demonstrate this approach on a flexible bent DNA molecule, consisting of two short helical parts with a five adenine bulge at the center. The kink and twist motions between both helical parts were quantitatively determined and showed high flexibility, in agreement with a Förster Resonance Energy Transfer (FRET) study on a similar bent DNA motif. The approach presented here should be useful to describe the relative orientation of helical motifs and the conformational flexibility of nucleic acid structures, both alone and in complexes with proteins and other molecules.

Conformational landscapes of membrane proteins delineated by enhanced sampling molecular dynamics simulations

The expansion of computational power, better parameterization of force fields, and the development of novel algorithms to enhance the sampling of the free energy landscapes of proteins have allowed molecular dynamics (MD) simulations to become an indispensable tool to understand the function of biomolecules. The temporal and spatial resolution of MD simulations allows for the study of a vast number of processes of interest. Here, we review the computational efforts to uncover the conformational free energy landscapes of a subset of membrane proteins: ion channels, transporters and G-protein coupled receptors. We focus on the various enhanced sampling techniques used to study these questions, how the conclusions come together to build a coherent picture, and the relationship between simulation outcomes and experimental observables.

MMM: A toolbox for integrative structure modeling

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.

Drude Polarizable Force Field for Molecular Dynamics Simulations of Saturated and Unsaturated Zwitterionic Lipids

Additive force fields are designed to account for induced electronic polarization in a mean-field average way, using effective empirical fixed charges. The limitation of this approximation is cause for serious concerns, particularly in the case of lipid membranes, where the molecular environment undergoes dramatic variations over microscopic length scales. A polarizable force field based on the classical Drude oscillator offers a practical and computationally efficient framework for an improved representation of electrostatic interactions in molecular simulations. Building on the first-generation Drude polarizable force field for the dipalmitoylphosphatidylcholine 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) molecule, the present effort was undertaken to improve this initial model and expand the force field to a wider range of phospholipid molecules. New lipids parametrized include dimyristoylphosphatidylcholine (DMPC), dilauroylphosphatidylcholine (DLPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), dipalmitoylphosphatidylethanolamine (DPPE), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE). The iterative optimization protocol employed in this effort led to lipid models that achieve a good balance between reproducing quantum mechanical data on model compound representative of phospholipids and reproducing a range of experimental condensed phase properties of bilayers. A parametrization strategy based on a restrained ensemble-maximum entropy methodology was used to help accurately match the experimental NMR order parameters in the polar headgroup region. All the parameters were developed to be compatible with the remainder of the Drude polarizable force field, which includes water, ions, proteins, DNA, and selected carbohydrates.

CHARMM-GUI 10 years for biomolecular modeling and simulation

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

Alternating access mechanisms of LeuT-fold transporters: trailblazing towards the promised energy landscapes

Secondary active transporters couple the uphill translocation of substrates to electrochemical ion gradients. Transporter conformational motion, generically referred to as alternating access, enables a central ligand binding site to change its orientation relative to the membrane. Here we review themes of alternating access and the transduction of ion gradient energy to power this process in the LeuT-fold class of transporters where crystallographic, computational and spectroscopic approaches have converged to yield detailed models of transport cycles. Specifically, we compare findings for the Na⁺-coupled amino acid transporter LeuT and the Na⁺-coupled hydantoin transporter Mhp1. Although these studies have illuminated multiple aspects of transporter structures and dynamics, a number of questions remain unresolved that so far hinder understanding transport mechanisms in an energy landscape perspective.

Toward Precise Interpretation of DEER-Based Distance Distributions: Insights from Structural Characterization of V1 Spin-Labeled Side Chains

Pulsed electron paramagnetic resonance experiments can measure individual distances between two spin-labeled side chains in proteins in the range of ∼1.5-8 nm. However, the flexibility of traditional spin-labeled side chains leads to diffuse spin density loci and thus distance distributions with relatively broad peaks, thereby complicating the interpretation of protein conformational states. Here we analyzed the spin-labeled V1 side chain, which is internally anchored and hence less flexible. Crystal structures of V1-labeled T4 lysozyme constructs carrying the V1 side chain on α-helical segments suggest that V1 side chains adopt only a few discrete rotamers. In most cases, only one rotamer is observed at a given site, explaining the frequently observed narrow distance distribution for doubly V1-labeled proteins. We used the present data to derive guidelines that may allow distance interpretation of other V1-labeled proteins for higher-precision structural modeling.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.

Cryo-EM Structures of the Magnesium Channel CorA Reveal Symmetry Break upon Gating

CorA, the major Mg(2+) uptake system in prokaryotes, is gated by intracellular Mg(2+) (KD ∼ 1-2 mM). X-ray crystallographic studies of CorA show similar conformations under Mg(2+)-bound and Mg(2+)-free conditions, but EPR spectroscopic studies reveal large Mg(2+)-driven quaternary conformational changes. Here, we determined cryo-EM structures of CorA in the Mg(2+)-bound closed conformation and in two open Mg(2+)-free states at resolutions of 3.8, 7.1, and 7.1 Å, respectively. In the absence of bound Mg(2+), four of the five subunits are displaced to variable extents (∼ 10-25 Å) by hinge-like motions as large as ∼ 35° at the stalk helix. The transition between a single 5-fold symmetric closed state and an ensemble of low Mg(2+), open, asymmetric conformational states is, thus, the key structural signature of CorA gating. This mechanism is likely to apply to other structurally similar divalent ion channels.

Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes

The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.

Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions

We introduce an enhanced-sampling method for molecular dynamics (MD) simulations referred to as ensemble-biased metadynamics (EBMetaD). The method biases a conventional MD simulation to sample a molecular ensemble that is consistent with one or more probability distributions known a priori, e.g., experimental intramolecular distance distributions obtained by double electron-electron resonance or other spectroscopic techniques. To this end, EBMetaD adds an adaptive biasing potential throughout the simulation that discourages sampling of configurations inconsistent with the target probability distributions. The bias introduced is the minimum necessary to fulfill the target distributions, i.e., EBMetaD satisfies the maximum-entropy principle. Unlike other methods, EBMetaD does not require multiple simulation replicas or the introduction of Lagrange multipliers, and is therefore computationally efficient and straightforward in practice. We demonstrate the performance and accuracy of the method for a model system as well as for spin-labeled T4 lysozyme in explicit water, and show how EBMetaD reproduces three double electron-electron resonance distance distributions concurrently within a few tens of nanoseconds of simulation time. EBMetaD is integrated in the open-source PLUMED plug-in (www.plumed-code.org), and can be therefore readily used with multiple MD engines.

Solid-State NMR-Restrained Ensemble Dynamics of a Membrane Protein in Explicit Membranes

Solid-state NMR has been used to determine the structures of membrane proteins in native-like lipid bilayer environments. Most structure calculations based on solid-state NMR observables are performed using simulated annealing with restrained molecular dynamics and an energy function, where all nonbonded interactions are represented by a single, purely repulsive term with no contributions from van der Waals attractive, electrostatic, or solvation energy. To our knowledge, this is the first application of an ensemble dynamics technique performed in explicit membranes that uses experimental solid-state NMR observables to obtain the refined structure of a membrane protein together with information about its dynamics and its interactions with lipids. Using the membrane-bound form of the fd coat protein as a model membrane protein and its experimental solid-state NMR data, we performed restrained ensemble dynamics simulations with different ensemble sizes in explicit membranes. For comparison, a molecular dynamics simulation of fd coat protein was also performed without any restraints. The average orientation of each protein helix is similar to a structure determined by traditional single-conformer approaches. However, their variations are limited in the resulting ensemble of structures with one or two replicas, as they are under the strong influence of solid-state NMR restraints. Although highly consistent with all solid-state NMR observables, the ensembles of more than two replicas show larger orientational variations similar to those observed in the molecular dynamics simulation without restraints. In particular, in these explicit membrane simulations, Lys(40), residing at the C-terminal side of the transmembrane helix, is observed to cause local membrane curvature. Therefore, compared to traditional single-conformer approaches in implicit environments, solid-state NMR restrained ensemble simulations in explicit membranes readily characterize not only protein dynamics but also protein-lipid interactions in detail.

Constraint methods that accelerate free-energy simulations of biomolecules

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.