Probing the Structural Dynamics of a Bacterial Chaperone in Its Native Environment by Nitroxide-Based EPR Spectroscopy

One of the greatest current challenges in structural biology is to study protein dynamics over a wide range of timescales in complex environments, such as the cell. Among magnetic resonances suitable for this approach, electron paramagnetic resonance spectroscopy coupled to site-directed spin labeling (SDSL-EPR) has emerged as a promising tool to study protein local dynamics and conformational ensembles. In this work, we exploit the sensitivity of nitroxide labels to report protein local dynamics at room temperature. We demonstrate that such studies can be performed while preserving both the integrity of the cells and the activity of the protein under investigation. Using this approach, we studied the structural dynamics of the chaperone NarJ in its natural host, Escherichia coli. We established that spin-labeled NarJ is active inside the cell. We showed that the cellular medium affects NarJ structural dynamics in a site-specific way, while the structural flexibility of the protein is maintained. Finally, we present and discuss data on the time-resolved dynamics of NarJ in cellular context.     

Distance-independent Cross-correlated Relaxation and Isotropic Chemical Shift Modulation in Protein Dynamics Studies

Cross-correlated relaxation (CCR) in multiple-quantum coherences differs from other relaxation phenomena in its theoretical ability to be mediated across an infinite distance. The two interfering relaxation mechanisms may be dipolar interactions, chemical shift anisotropies, chemical shift modulations or quadrupolar interactions. These properties make multiple-quantum CCR an attractive probe for structure and dynamics of biomacromolecules not accessible from other measurements. Here, we review the use of multiple-quantum CCR measurements in dynamics studies of proteins. We compile a list of all experiments proposed for CCR rate measurements, provide an overview of the theory with a focus on protein dynamics, and present applications to various protein systems.     

Crossing the phase boundary to study protein dynamics and function: combination of amide hydrogen exchange in solution and ion fragmentation in the gas phase

Protein dynamics are the key to understanding their behavior. The static protein structure alone in most cases is insufficient to describe the vast array of complex functions they perform in vivo. Until recently there were relatively few techniques available to investigate the dynamic nature of these proteins. Mass spectrometry has recently emerged as a powerful biophysical method, capable of providing both structural and dynamic information. By utilizing the labile nature of amide hydrogens as a marker of the backbone dynamics in solution, combined with gas-phase dissociation techniques, we now have a high-resolution tool to locate these exchanging hydrogens within the sequence of the protein and to probe the functional importance of its structural elements. In this paper we describe several applications of these methodologies to illustrate the importance of dynamics to the biological functions of proteins.     

Replica exchange with guided annealing for accelerated sampling of disordered protein conformations

We critically examine a recently proposed convective replica exchange (cRE) method for enhanced sampling of protein conformation based on theoretical and numerical analysis. The results demonstrate that cRE and related replica exchange with guided annealing (RE‐GA) schemes lead to unbalanced exchange attempt probabilities and break detailed balance whenever the system undergoes slow conformational transitions (relative to the temperature diffusion timescale). Nonetheless, numerical simulations suggest that approximate canonical ensembles can be generated for systems with small conformational transition barriers. This suggests that RE‐GA maybe suitable for simulating intrinsically disordered proteins, an important class of newly recognized functional proteins. The efficacy of RE‐GA is demonstrated by calculating the conformational ensembles of intrinsically disordered kinase inducible domain protein. The results show that RE‐GA helps the protein to escape nonspecific compact states more efficiently and provides several fold speedups in generating converged and largely correct ensembles compared to the standard temperature RE. © 2014 Wiley Periodicals, Inc.     

Proximity‐Triggered Covalent Stabilization of Low‐Affinity Protein Complexes In Vitro and In Vivo

The characterization of low‐affinity protein complexes is challenging due to their dynamic nature. Here, we present a method to stabilize transient protein complexes in vivo by generating a covalent and conformationally flexible bridge between the interaction partners. A highly active pyrrolysyl tRNA synthetase mutant directs the incorporation of unnatural amino acids bearing bromoalkyl moieties (BrCnK) into proteins. We demonstrate for the first time that low‐affinity protein complexes between BrCnK‐containing proteins and their binding partners can be stabilized in vivo in bacterial and mammalian cells. Using this approach, we determined the crystal structure of a transient GDP‐bound complex between a small G‐protein and its nucleotide exchange factor. We envision that this approach will prove valuable as a general tool for validating and characterizing protein–protein interactions in vitro and in vivo.     

Future directions of structural mass spectrometry using hydroxyl radical footprinting

Hydroxyl radical protein footprinting coupled to mass spectrometry has been developed over the last decade and has matured to a powerful method for analyzing protein structure and dynamics. It has been successfully applied in the analysis of protein structure, protein folding, protein dynamics, and protein–protein and protein–DNA interactions. Using synchrotron radiolysis, exposure of proteins to a ‘white’ X‐ray beam for milliseconds provides sufficient oxidative modification to surface amino acid side chains, which can be easily detected and quantified by mass spectrometry. Thus, conformational changes in proteins or protein complexes can be examined using a time‐resolved approach, which would be a valuable method for the study of macromolecular dynamics. In this review, we describe a new application of hydroxyl radical protein footprinting to probe the time evolution of the calcium‐dependent conformational changes of gelsolin on the millisecond timescale. The data suggest a cooperative transition as multiple sites in different molecular subdomains have similar rates of conformational change. These findings demonstrate that time‐resolved protein footprinting is suitable for studies of protein dynamics that occur over periods ranging from milliseconds to seconds. In this review, we also show how the structural resolution and sensitivity of the technology can be improved as well. The hydroxyl radical varies in its reactivity to different side chains by over two orders of magnitude, thus oxidation of amino acid side chains of lower reactivity are more rarely observed in such experiments. Here we demonstrate that the selected reaction monitoring (SRM)‐based method can be utilized for quantification of oxidized species, improving the signal‐to‐noise ratio. This expansion of the set of oxidized residues of lower reactivity will improve the overall structural resolution of the technique. This approach is also suggested as a basis for developing hypothesis‐driven structural mass spectrometry experiments. Copyright © 2010 John Wiley & Sons, Ltd.     

Structure prediction of cyclic peptides by molecular dynamics + machine learning

Recent computational methods have made strides in discovering well-structured cyclic peptides that preferentially populate a single conformation. However, many successful cyclic-peptide therapeutics adopt multiple conformations in solution. In fact, the chameleonic properties of some cyclic peptides are likely responsible for their high cell membrane permeability. Thus, we require the ability to predict complete structural ensembles for cyclic peptides, including the majority of cyclic peptides that have broad structural ensembles, to significantly improve our ability to rationally design cyclic-peptide therapeutics. Here, we introduce the idea of using molecular dynamics simulation results to train machine learning models to enable efficient structure prediction for cyclic peptides. Using molecular dynamics simulation results for several hundred cyclic pentapeptides as the training datasets, we developed machine-learning models that can provide molecular dynamics simulation-quality predictions of structural ensembles for all the hundreds of thousands of sequences in the entire sequence space. The prediction for each individual cyclic peptide can be made using less than 1 second of computation time. Even for the most challenging classes of poorly structured cyclic peptides with broad conformational ensembles, our predictions were similar to those one would normally obtain only after running multiple days of explicit-solvent molecular dynamics simulations. The resulting method, termed StrEAMM (Structural Ensembles Achieved by Molecular Dynamics and Machine Learning), is the first technique capable of efficiently predicting complete structural ensembles of cyclic peptides without relying on additional molecular dynamics simulations, constituting a seven-order-of-magnitude improvement in speed while retaining the same accuracy as explicit-solvent simulations.

The StrEAMM method enables predicting the structural ensembles of cyclic peptides that adopt multiple conformations in solution.     

In situ AFM study of amelogenin assembly and disassembly dynamics on charged surfaces provides insights on matrix protein self-assembly

Because self-assembly of matrix proteins is a key step in hard tissue mineralization, developing an understanding of the assembly pathways and underlying mechanisms is likely to be important for successful hard tissue engineering. While many studies of matrix protein assembly have been performed on bulk solutions, in vivo these proteins are likely to be in contact with charged biological surfaces composed of lipids, proteins, or minerals. Here we report the results of an in situ atomic force microscopy (AFM) study of self-assembly by amelogenin--the principal protein of the extracellular matrix in developing enamel--in contact with two different charged substrates: hydrophilic negatively charged bare mica and positively charged 3-aminopropyl triethoxysilane (APS) silanized mica. First we demonstrate an AFM-based protocol for determining the size of both amelogenin monomers and oligomers. Using this protocol, we find that, although amelogenin exists primarily as ~26 nm in diameter nanospheres in bulk solution at a pH of 8.0 studied by dynamic light scattering, it behaves dramatically differently upon interacting with charged substrates at the same pH and exhibits complex substrate-dependent assembly pathways and dynamics. On positively charged APS-treated mica surfaces, amelogenin forms a relatively uniform population of decameric oligomers, which then transform into two main populations: higher-order assemblies of oligomers and amelogenin monomers, while on negatively charged bare mica surfaces, it forms a film of monomers that exhibits tip-induced desorption and patterning. The present study represents a successful attempt to identify the size of amelogenin oligomers and to directly monitor assembly and disassembly dynamics on surfaces. The findings have implications for amelogenin-controlled calcium phosphate mineralization in vitro and may offer new insights into in vivo self-assembly of matrix proteins as well as their control over hard tissue formation.     

A Mass‐Spectrometry‐Based Approach to Distinguish Annular and Specific Lipid Binding to Membrane Proteins

Membrane proteins engage in a variety of contacts with their surrounding lipids, but distinguishing between specifically bound lipids, and non‐specific, annular interactions is a challenging problem. Applying native mass spectrometry to three membrane protein complexes with different lipid‐binding properties, we explore the ability of detergents to compete with lipids bound in different environments. We show that lipids in annular positions on the presenilin homologue protease are subject to constant exchange with detergent. By contrast, detergent‐resistant lipids bound at the dimer interface in the leucine transporter show decreased k_off rates in molecular dynamics simulations. Turning to the lipid flippase MurJ, we find that addition of the natural substrate lipid‐II results in the formation of a 1:1 protein–lipid complex, where the lipid cannot be displaced by detergent from the highly protected active site. In summary, we distinguish annular from non‐annular lipids based on their exchange rates in solution.     

Paramagnetic-based NMR restraints lift residual dipolar coupling degeneracy in multidomain detergent-solubilized membrane proteins

Residual dipolar couplings (RDCs) are widely used as orientation-dependent NMR restraints to improve the resolution of the NMR conformational ensemble of biomacromolecules and define the relative orientation of multidomain proteins and protein complexes. However, the interpretation of RDCs is complicated by the intrinsic degeneracy of analytical solutions and protein dynamics that lead to ill-defined orientations of the structural domains (ghost orientations). Here, we illustrate how restraints from paramagnetic relaxation enhancement (PRE) experiments lift the orientational ambiguity of multidomain membrane proteins solubilized in detergent micelles. We tested this approach on monomeric phospholamban (PLN), a 52-residue membrane protein, which is composed of two helical domains connected by a flexible loop. We show that the combination of classical solution NMR restraints (NOEs and dihedral angles) with RDC and PRE constraints resolves topological ambiguities, improving the convergence of the PLN structural ensemble and giving the depth of insertion of the protein within the micelle. The combination of RDCs with PREs will be necessary for improving the accuracy and precision of membrane protein conformational ensembles, where three-dimensional structures are dictated by interactions with the membrane-mimicking environment rather than compact tertiary folds common in globular proteins.     

Protein Conformational Dynamics upon Association with the Surfaces of Lipid Membranes and Engineered Nanoparticles: Insights from Electron Paramagnetic Resonance Spectroscopy

Detailed study of conformational rearrangements and dynamics of proteins is central to our understanding of their physiological functions and the loss of function. This review outlines the applications of the electron paramagnetic resonance (EPR) technique to study the structural aspects of proteins transitioning from a solution environment to the states in which they are associated with the surfaces of biological membranes or engineered nanoobjects. In the former case these structural transitions generally underlie functional protein states. The latter case is mostly relevant to the application of protein immobilization in biotechnological industries, developing methods for protein purification, etc. Therefore, evaluating the stability of the protein functional state is particularly important. EPR spectroscopy in the form of continuous-wave EPR or pulse EPR distance measurements in conjunction with protein spin labeling provides highly versatile and sensitive tools to characterize the changes in protein local dynamics as well as large conformational rearrangements. The technique can be widely utilized in studies of both protein-membrane and engineered nanoobject-protein complexes.     

What induces pocket openings on protein surface patches involved in protein–protein interactions?

We previously showed for the proteins BCL-X_L, IL-2, and MDM2 that transient pockets at their protein–protein binding interfaces can be identified by applying the PASS algorithm to molecular dynamics (MD) snapshots. We now investigated which aspects of the natural conformational dynamics of proteins induce the formation of such pockets. The pocket detection protocol was applied to three different conformational ensembles for the same proteins that were extracted from MD simulations of the inhibitor bound crystal conformation in water and the free crystal/NMR structure in water and in methanol. Additional MD simulations studied the impact of backbone mobility. The more efficient CONCOORD or normal mode analysis (NMA) techniques gave significantly smaller pockets than MD simulations, whereas tCONCOORD generated pockets comparable to those observed in MD simulations for two of the three systems. Our findings emphasize the influence of solvent polarity and backbone rearrangements on the formation of pockets on protein surfaces and should be helpful in future generation of transient pockets as putative ligand binding sites at protein–protein interfaces. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A Method to Explore Protein Side Chain Conformational Variability Using Experimental Data

Experimentally measured values of molecular properties or observables of biomolecules such as proteins are generally averages over time and space, which do not contain su?cient information to determine the underlying conformational distribution of the molecules in solution. The relationship between experimentally measured NMR ³J‐coupling values and the corresponding dihedral angle values is a particularly complicated case due to its nonlinear, multiple‐valued nature. Molecular dynamics (MD) simulations at constant temperature can generate Boltzmann ensembles of molecular structures that are free from a priori assumptions about the nature of the underlying conformational distribution. They suffer, however, from limited sampling with respect to time and conformational space. Moreover, the quality of the obtained structures is dependent on the choice of force ?eld and solvation model. A recently proposed method that uses time‐averaging with local‐elevation (LE) biasing of the conformational search provides an elegant means of overcoming these three problems. Using a set of side chain ³J‐coupling values for the FK506 binding protein (FKBP), we ?rst investigate the uncertainty in the angle values predicted theoretically. We then propose a simple MD‐based technique to detect inconsistencies within an experimental data set and identify degrees of freedom for which conformational averaging takes place or for which force ?eld parameters may be de?cient. Finally, we show that LE MD is the best method for producing ensembles of structures that, on average, ?t the experimental data.     

Predicting protein folding rates using the concept of Chou's pseudo amino acid composition

One of the most important challenges in computational and molecular biology is to understand the relationship between amino acid sequences and the folding rates of proteins. Recent works suggest that topological parameters, amino acid properties, chain length and the composition index relate well with protein folding rates, however, sequence order information has seldom been considered as a property for predicting protein folding rates. In this study, amino acid sequence order was used to derive an effective method, based on an extended version of the pseudo-amino acid composition, for predicting protein folding rates without any explicit structural information. Using the jackknife cross validation test, the method was demonstrated on the largest dataset (99 proteins) reported. The method was found to provide a good correlation between the predicted and experimental folding rates. The correlation coefficient is 0.81 (with a highly significant level) and the standard error is 2.46. The reported algorithm was found to perform better than several representative sequence-based approaches using the same dataset. The results indicate that sequence order information is an important determinant of protein folding rates.     

Protein Structural Ensembles Visualized by Solvent Paramagnetic Relaxation Enhancement

A protein can be in different conformations when fulfilling its function. Yet depiction of protein structural ensembles remains difficult. Here we show that the accurate measurement of solvent paramagnetic relaxation enhancement (sPRE) in the presence of an inert paramagnetic cosolute allows the assessment of protein dynamics. Demonstrated with two multi‐domain proteins, we present a method to characterize protein microsecond–millisecond dynamics based on the analysis of the sPRE. Provided with the known structures of a protein, our method uncovers an ensemble of structures that fully accounts for the observed sPRE. In conjunction with molecular dynamics simulations, our method can identify protein alternative conformation that has only been theorized before. Together, our method expands the application of sPRE beyond structural characterization of rigid proteins and complements the established PRE NMR technique.     

The Active Site of a Prototypical “Rigid” Drug Target is Marked by Extensive Conformational Dynamics

Drug discovery, in particular optimization of candidates using medicinal chemistry, is generally guided by structural biology. However, for optimizing binding kinetics, relevant for efficacy and off-target effects, information on protein motion is important. Herein, we demonstrate for the prototypical textbook example of an allegedly “rigid protein” that substantial active-site dynamics have generally remained unrecognized, despite thousands of medicinal-chemistry studies on this model over decades. Comparing cryogenic X-ray structures, solid-state NMR on micro-crystalline protein at room temperature, and solution NMR structure and dynamics, supported by MD simulations, we show that under physiologically relevant conditions the pocket is in fact shaped by pronounced open/close conformational-exchange dynamics. The study, which is of general significance for pharmacological research, evinces a generic pitfall in drug discovery routines.     

Low-temperature studies of encapsulated proteins

Water-soluble proteins encapsulated within reverse micelles may be studied under a variety of conditions, including low temperature and a wide range of buffer conditions. Direct high-resolution detection of information relating to protein folding intermediates and pathways can be monitored by low-temperature solution NMR. Ubiquitin encapsulated within AOT reverse micelles was studied using multidimensional multinuclear solution NMR to determine the relationship between protein structure, temperature, and ionic strength. Ubiquitin resonances were monitored by 15N HSQC NMR experiments at varying temperatures and salt concentrations. Our results indicate that the structure of the encapsulated protein at low temperature experiences perturbation arising from two major influences, which are reverse micelle-protein interactions and low-temperature effects (e.g., cold denaturation). These two effects are impossible to distinguish under conditions of low ionic strength. Elevated concentrations of nondenaturing salt solutions defeat the effects of reverse micelle-protein interactions and reveal low-temperature protein unfolding. High ionic strength shielding stabilizes the reverse micelle at low temperatures, which reduces the electrostatic interaction between the protein and reverse micelle surfaces, allowing the phenomenon of cold denaturation to be explored.