Simulated Isotope Exchange Patterns Enable Protein Structure Determination.

Understanding the myriad protein-protein interactions required for cell function requires efficient leveraging of biophysical data to drive computational docking. The detailed insight into protein interfaces provided by isotope exchange endows this experimental technique with a unique importance for docking approaches. However, progress in coupling these methods is hindered by the inability to interpret the complex exchange patterns in relation to protein structure. A method to simulate protein isotope exchange patterns from docking outputs is described and its utility to guide the selection of native assemblies demonstrated. Unique signatures are generated for each docking pose, allowing high-throughput ranking of whole docking simulations by pairwise comparison to experimental outputs. Native assemblies are obtained using nothing but their simulated profiles as restraints and experimental difference data for individual proteins are sufficient to drive structure determination for the whole complex.

Assembling the pieces of macromolecular complexes: Hybrid structural biology approaches.

Hybrid approaches in structural biology have gained considerable interest for uncovering the molecular architectures of large and transient biological systems. In particular, MS-based methods and structural electron microscopy can complement conventional tools, such as X-ray crystallography and NMR spectroscopy. However, bringing together the data derived from diverse sources requires sophisticated methods that can efficiently deal with intrinsic ambiguities and heterogeneities of the vast amount of data available. Here, we highlight hybrid approaches for studying dynamic assemblies, such as transient soluble and integral membrane protein complexes. In this review, we emphasize the integration of the wide range of emerging MS-based methods, such as ion mobility, native MS, hydrogen-deuterium exchange MS and chemical cross-linking MS, with data acquired from cryo electron microscopy and X-ray crystallography and further provide a future outlook of hybrid structural biology approaches.

Ensemble Methods Enable a New Definition for the Solution to Gas-Phase Transfer of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) are important for health and disease, yet their lack of net structure precludes an understanding of their function using classical methods. Gas-phase techniques provide a promising alternative to access information on the structure and dynamics of IDPs, but the fidelity to which these methods reflect the solution conformations of these proteins has been difficult to ascertain. Here we use state of the art ensemble techniques to investigate the solution to gas-phase transfer of a range of different IDPs. We show that IDPs undergo a vast conformational space expansion in the absence of solvent to sample a conformational space 3-5 fold broader than in solution. Moreover, we show that this process is coupled to the electrospray ionization process, which brings about the generation of additional subpopulations for these proteins not observed in solution due to competing effects on protein charge and shape. Ensemble methods have permitted a new definition of the solution to gas-phase transfer of IDPs and provide a roadmap for future investigations into flexible systems by mass spectrometry.

Structure and dynamics of a protein-surfactant assembly studied by ion-mobility mass spectrometry and molecular dynamics simulations.

The structure and dynamics of a protein-surfactant assembly studied by ion-mobility mass spectrometry (IMS) and vacuum molecular dynamics (MD) simulations is reported. Direct evidence is provided for the ability of the surfactant dodecyl-ß-D-maltoside (DDM) to prevent charge-induced unfolding of the membrane protein (PagP) in the gas-phase. Restraints obtained by IMS are used to map the surfactant positions onto the protein surface. Surfactants occupying more exposed positions at the apexes of the ß-barrel structure are most in-line with the experimental observations. MD simulations provide additional evidence for this assembly organization through surfactant inversion and migration on the protein structure in the absence of solvent. Surfactant migration entails a net shift from apolar membrane spanning regions to more polar regions of the protein structure with the DDM molecule remaining attached to the protein via headgroup interactions. These data provide evidence for the role of protein-DDM headgroup interactions in stabilizing membrane protein structure from gas-phase unfolding.

Charge reduction stabilizes intact membrane protein complexes for mass spectrometry.

The study of intact soluble protein assemblies by means of mass spectrometry is providing invaluable contributions to structural biology and biochemistry. A recent breakthrough has enabled similar study of membrane protein complexes, following their release from detergent micelles in the gas phase. Careful optimization of mass spectrometry conditions, particularly with respect to energy regimes, is essential for maintaining compact folded states as detergent is removed. However, many of the saccharide detergents widely employed in structural biology can cause unfolding of membrane proteins in the gas phase. Here, we investigate the potential of charge reduction by introducing three membrane protein complexes from saccharide detergents and show how reducing their overall charge enables generation of compact states, as evidenced by ion mobility mass spectrometry. We find that charge reduction stabilizes the oligomeric state and enhances the stability of lipid-bound complexes. This finding is significant since maintaining native-like membrane proteins enables ligand binding to be assessed from a range of detergents that retain solubility while protecting the overall fold.

Deep Learning Enables Automatic Correction of Experimental HDX-MS Data with Applications in Protein Modeling.

Observed mass shifts associated with deuterium incorporation in hydrogen-deuterium exchange mass spectrometry (HDX-MS) frequently deviate from the initial signals due to back and forward exchange. In typical HDX-MS experiments, the impact of these disparities on data interpretation is generally low because relative and not absolute mass changes are investigated. However, for more advanced data processing including optimization, experimental error correction is imperative for accurate results. Here the potential for automatic HDX-MS data correction using models generated by deep neural networks is demonstrated. A multilayer perceptron (MLP) is used to learn a mapping between uncorrected HDX-MS data and data with mass shifts corrected for back and forward exchange. The model is rigorously tested at various levels including peptide level mass changes, residue level protection factors following optimization, and ability to correctly identify native protein folds using HDX-MS guided protein modeling. AI is shown to demonstrate considerable potential for amending HDX-MS data and improving fidelity across all levels. With access to big data, online tools may eventually be able to predict corrected mass shifts in HDX-MS profiles. This should improve throughput in workflows that require the reporting of real mass changes as well as allow retrospective correction of historic profiles to facilitate new discoveries with these data.

Detergent release prolongs the lifetime of native-like membrane protein conformations in the gas-phase.

Recent studies have suggested that detergents can protect the structure of membrane proteins during their transition from solution to the gas-phase. Here we provide mechanistic insights into this process by interrogating the structures of membrane protein-detergent assemblies in the gas-phase using ion mobility mass spectrometry. We show a clear correlation between the population of native-like protein conformations and the degree of detergent attachment to the protein in the gas-phase. Interrogation of these protein-detergent assemblies, by tandem mass spectrometry, enables us to define the mechanism by which detergents preserve native-like protein conformations in a solvent free environment. We show that the release of detergent is more central to the survival of these conformations than the physical presence of detergent bound to the protein. We propose that detergent release competes with structural collapse for the internal energy of the ion and permits the observation of transient native-like membrane protein conformations that are otherwise lost to structural rearrangement in the gas-phase.

Mapping HDX-MS Data to Protein Conformations through Training Ensemble-Based Models.

An original approach that adopts machine learning inference to predict protein structural information using hydrogen-deuterium exchange mass spectrometry (HDX-MS) is described. The method exploits an in-house optimization program that increases the resolution of HDX-MS data from peptides to amino acids. A system is trained using Gradient Tree Boosting as a type of machine learning ensemble technique to assign a protein secondary structure. Using limited training data we generate a discriminative model that uses optimized HDX-MS data to predict protein secondary structure with an accuracy of 75%. This research could form the basis for new methods exploiting artificial intelligence to model protein conformations by HDX-MS.

Formation and dissociation processes of gas-phase detergent micelles.

Growing interest in micelles to protect membrane complexes during the transition from solution to gas phase prompts a better understanding of their properties. We have used ion mobility mass spectrometry to separate and assign detergent clusters formed from the n-trimethylammonium bromide series of detergents. We show that cluster size is independent of detergent concentration in solution, increases with charge state, but surprisingly decreases with alkyl chain length. This relationship contradicts the thermodynamics of micelle formation in solution. However, the liquid drop model, which considers both the surface energy and charge, correlates extremely well with the experimental cluster size. To explore further the properties of gas-phase micelles, we have performed collision-induced dissociation on them during tandem mass spectrometry. We observed both sequential asymmetric charge separation and neutral evaporation from the precursor ion cluster. Interestingly, however, we also found markedly different dissociation pathways for the longer alkyl chain detergents, with significantly fewer intermediate ions formed than for those with a shorter alkyl chain. These experiments provide an essential foundation for understanding the process of the gas-phase analysis of membrane protein complexes. Moreover they imply valuable mechanistic details of the protection afforded to protein complexes by detergent clusters during gas-phase activation processes.

The 'sticky business' of cleaning gas-phase membrane proteins: a detergent oriented perspective.

In recent years the properties of gas-phase detergent clusters have come under close scrutiny due in part to their participation in the analysis of intact membrane protein complexes by mass spectrometry. The detergent molecules that cover the protein complex are removed in the gas-phase by thermally agitating the ions by collision-induced dissociation. This process however, is not readily controlled and can frequently result in the disruption of protein structure. Improved methods of releasing proteins from detergent clusters are clearly required. To facilitate this the structural properties of detergent clusters along with the mechanistic details of their dissociation need to be understood. Pivotal to understanding the properties of gas-phase detergent clusters is the technique of ion mobility mass spectrometry. This technique can be used to assign polydisperse detergent clusters and provide information about their geometries and packing densities. In this article we consider the shapes of detergent clusters and show that these clusters possess geometries that are inconsistent with those in solution. We analyse the distributions of clusters in detail using tandem mass spectrometry and suggest that the mean charge of clusters formed from certain detergents is governed by electrostatic repulsion. We discuss the dissociation of detergent clusters and propose that detergent evaporation it a key process in the protection of protein complexes during high energy collisions in the gas-phase.

Computational Modeling of Molecular Structures Guided by Hydrogen-Exchange Data.

Data produced by hydrogen-exchange monitoring experiments have been used in structural studies of molecules for several decades. Despite uncertainties about the structural determinants of hydrogen exchange itself, such data have successfully helped guide the structural modeling of challenging molecular systems, such as membrane proteins or large macromolecular complexes. As hydrogen-exchange monitoring provides information on the dynamics of molecules in solution, it can complement other experimental techniques in so-called integrative modeling approaches. However, hydrogen-exchange data have often only been used to qualitatively assess molecular structures produced by computational modeling tools. In this paper, we look beyond qualitative approaches and survey the various paradigms under which hydrogen-exchange data have been used to quantitatively guide the computational modeling of molecular structures. Although numerous prediction models have been proposed to link molecular structure and hydrogen exchange, none of them has been widely accepted by the structural biology community. Here, we present as many hydrogen-exchange prediction models as we could find in the literature, with the aim of providing the first exhaustive list of its kind. From purely structure-based models to so-called fractional-population models or knowledge-based models, the field is quite vast. We aspire for this paper to become a resource for practitioners to gain a broader perspective on the field and guide research toward the definition of better prediction models. This will eventually improve synergies between hydrogen-exchange monitoring and molecular modeling.

Structure of rat odorant-binding protein OBP1 at 1.6 A resolution.

The nasal mucosa is a specialist interfacial region sandwiched between the olfactory system and the gaseous chemical milieu. In mammals and insects, this region is rich in odorant-binding proteins that are thought to aid olfaction by assisting mass transfer of the many different organoleptic compounds that make up the olfactory landscape. However, in mammals at least, our grasp on the exact function of odorant-binding proteins is tentative and better insight into the role of these proteins is warranted, not least because of their apparent significance in the olfactory systems of insects. Here, the crystal structure of rat odorant-binding protein 1 is reported at 1.6 A resolution. This protein is one of the best-characterized mammalian odorant-binding proteins and only the third such protein structure to be solved at high resolution. The protein was crystallized in the holo form and contains an unidentifiable ligand that is probably an artefact from the Pichia pastoris expression system. Comparisons are made between this structure and a modelled OBP1 structure produced using the crystal structure of aphrodisin as a template. Comparisons are also made between OBP1 and the other two rat OBP subtypes, for which crystallographic data are unavailable. Interestingly, we also show that OBP1 is monomeric, which is in contrast to its previous assignment.

Quantitative Evaluation of Native Protein Folds and Assemblies by Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS).

Hydrogen deuterium exchange mass spectrometry (HDX-MS) has significant potential for protein structure initiatives but its relationship with protein conformations is unclear. We report on the efficacy of HDX-MS to distinguish between native and non-native proteins using a popular approach to calculate HDX protection factors (PFs) from protein structures. The ability of HDX-MS to identify native protein conformations is quantified by binary structural classification such that merits of the approach for protein modelling can be quantified and better understood. We show that highly accurate PF calculations are not a prerequisite for HDX-MS simulations that are capable of effectively discriminating between native and non-native protein folds. The simulations can also be performed directly on unique structures facilitating high-throughput evaluation of many alternate conformations. The ability of HDX-MS to classify the conformations of homo-protein assemblies is also investigated. In contrast to protein monomers, we show a significant lack of correspondence between the simulated and experimental HDX-MS data for these systems with a subsequent decrease in the ability of HDX-MS to identify native states. However, we demonstrate surprisingly high diagnostic ability of the simulated data for assemblies in which a significant proportion of the individual chains occupy protein-protein interfaces. We relate this to the number of peptides that can sample alternate subunit orientations and discuss these observations within the larger context of applying HDX-MS to evaluate protein structures. Graphical Abstract.

HDX and Native Mass Spectrometry Reveals the Different Structural Basis for Interaction of the Staphylococcal Pathogenicity Island Repressor Stl with Dimeric and Trimeric Phage dUTPases.

The dUTPase enzyme family plays an essential role in maintaining the genome integrity and are represented by two distinct classes of proteins; the ß-pleated homotrimeric and the all-α homodimeric dUTPases. Representatives of both trimeric and dimeric dUTPases are encoded by Staphylococcus aureus phage genomes and have been shown to interact with the Stl repressor protein of S. aureus pathogenicity island SaPIbov1. In the present work we set out to characterize the interactions between these proteins based on a range of biochemical and biophysical methods and shed light on the binding mechanism of the dimeric φNM1 phage dUTPase and Stl. Using hydrogen deuterium exchange mass spectrometry, we also characterize the protein regions involved in the dUTPase:Stl interactions. Based on these results we provide reasonable explanation for the enzyme inhibitory effect of Stl observed in both types of complexes. Our experiments reveal that Stl employs different peptide segments and stoichiometry for the two different phage dUTPases which allows us to propose a functional plasticity of Stl. The malleable character of Stl serves as a basis for the inhibition of both dimeric and trimeric dUTPases.

Direct protein-lipid interactions shape the conformational landscape of secondary transporters.

Secondary transporters undergo structural rearrangements to catalyze substrate translocation across the cell membrane - yet how such conformational changes happen within a lipid environment remains poorly understood. Here, we combine hydrogen-deuterium exchange mass spectrometry (HDX-MS) with molecular dynamics (MD) simulations to understand how lipids regulate the conformational dynamics of secondary transporters at the molecular level. Using the homologous transporters XylE, LacY and GlpT from Escherichia coli as model systems, we discover that conserved networks of charged residues act as molecular switches that drive the conformational transition between different states. We reveal that these molecular switches are regulated by interactions with surrounding phospholipids and show that phosphatidylethanolamine interferes with the formation of the conserved networks and favors an inward-facing state. Overall, this work provides insights into the importance of lipids in shaping the conformational landscape of an important class of transporters.

Structural model of human dUTPase in complex with a novel proteinaceous inhibitor.

Human deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase), essential for DNA integrity, acts as a survival factor for tumor cells and is a target for cancer chemotherapy. Here we report that the Staphylococcal repressor protein StlSaPIBov1 (Stl) forms strong complex with human dUTPase. Functional analysis reveals that this interaction results in significant reduction of both dUTPase enzymatic activity and DNA binding capability of Stl. We conducted structural studies to understand the mechanism of this mutual inhibition. Small-angle X-ray scattering (SAXS) complemented with hydrogen-deuterium exchange mass spectrometry (HDX-MS) data allowed us to obtain 3D structural models comprising a trimeric dUTPase complexed with separate Stl monomers. These models thus reveal that upon dUTPase-Stl complex formation the functional homodimer of Stl repressor dissociates, which abolishes the DNA binding ability of the protein. Active site forming dUTPase segments were directly identified to be involved in the dUTPase-Stl interaction by HDX-MS, explaining the loss of dUTPase activity upon complexation. Our results provide key novel structural insights that pave the way for further applications of the first potent proteinaceous inhibitor of human dUTPase.

A hydrodynamic comparison of solution and gas phase proteins and their complexes.

The extent to which protein structures are preserved on transfer from solution to gas phase is a central question for native mass spectrometry. Here we compare the collision cross sections (Ω) of a wide range of different proteins and protein complexes (15-500 kDa) with their corresponding Stokes radii (RS). Using these methods, we find that Ω and RS are well correlated, implying overall preservation of protein structure in the gas phase. Accounting for protein hydration, a scaling term is required to bring Ω and RS into parity. Interestingly, the magnitude of this scaling term agrees almost entirely with the drag factor proposed by Millikan. RS were then compared with various different predicted values of Ω taken from their atomic coordinates. We find that many of the approaches used to obtained Ω from atomic coordinates miscalculate the physical sizes of the proteins in solution by as much as 20%. Rescaling of Ω estimated from atomic coordinates may therefore seem appropriate as a general method to bring theoretical values in line with those observed in solution.

Rapid odorant release in mammalian odour binding proteins facilitates their temporal coupling to odorant signals.

We have measured the effect of rat odorant-binding protein 1 on the rates of ligand uptake and liquid-to-air transfer rates with a set of defined odorous compounds. Comparison of observed rate constants (k(obs)) with data simulated over a wide range of different kinetic and thermodynamic regimes shows that the data do not agree with the previously held view of a slow off-rate regime (k(off) <0.0004 s(-1)). We propose that a rapid k(off) would be a necessary requirement for such a system, since slow odorant-release rates would result in significant decorrelation between the olfactory world and odour perception.

Co-populated conformational ensembles of beta2-microglobulin uncovered quantitatively by electrospray ionization mass spectrometry.

Ordered assembly of monomeric human beta(2)-microglobulin (beta(2)m) into amyloid fibrils is associated with the disorder hemodialysis-related amyloidosis. Previously, we have shown that under acidic conditions (pH <5.0 at 37 degrees C), wild-type beta(2)m assembles spontaneously into fibrils with different morphologies. Under these conditions, beta(2)m populates a number of different conformational states in vitro. However, this equilibrium mixture of conformationally different species is difficult to resolve using ensemble techniques such as nuclear magnetic resonance or circular dichroism. Here we use electrospray ionization mass spectrometry to resolve different species of beta(2)m populated between pH 6.0 and 2.0. We show that by linear deconvolution of the charge state distributions, the extent to which each conformational ensemble is populated throughout the pH range can be determined and quantified. Thus, at pH 3.6, conditions under which short fibrils are produced, the conformational ensemble is dominated by a charge state distribution centered on the 9+ ions. By contrast, under more acidic conditions (pH 2.6), where long straight fibrils are formed, the charge state distribution is dominated by the 10+ and 11+ ions. The data are reinforced by investigations on two variants of beta(2)m (V9A and F30A) that have reduced stability to pH denaturation and show changes in the pH dependence of the charge state distribution that correlate with the decrease in stability measured by tryptophan fluorescence. The data highlight the potential of electrospray ionization mass spectrometry to resolve and quantify complex mixtures of different conformational species, one or more of which may be important in the formation of amyloid.

Separation of beta2-microglobulin conformers by high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to electrospray ionisation mass spectrometry.

An investigation into the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to electrospray ionisation mass spectrometry (ESI-MS) for the differentiation of co-populated protein conformers has been conducted on the amyloidogenic protein beta(2)-microglobulin (beta(2)m). Accumulation of beta(2)m in vivo can result in the deposition of insoluble fibrils whose formation is thought to originate from partially folded protein conformers; hence, the folding properties of beta(2)m are of significant interest. We have analysed beta(2)m using ESI-FAIMS-MS under a range of pH conditions and have studied the effect of the ion mobility spectrometry parameters on the behaviour of the various protein conformers. The data show that different protein conformers can be detected and analysed by ESI-FAIMS-MS, the results being consistent with observations of pH denaturation obtained using complementary biophysical techniques. A variant of beta(2)m with different folding characteristics has been analysed for comparison, and the distinctions observed in the data sets for the two proteins are consistent with their folding behaviour. ESI-FAIMS-MS offers significant opportunities for the study of the conformational properties of proteins and thus may present valuable insights into the roles that different conformers play in diseases related to protein folding.