Computing H/D-exchange rates of single residues from data of proteolytic fragments

Computational Structure Prediction for Antibody-Antigen Complexes From Hydrogen-Deuterium Exchange Mass Spectrometry: Challenges and Outlook

Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.

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.

Exploiting the Propagation of Constrained Variables for Enhanced HDX-MS Data Optimization

Nonlinear programming has found useful applications in protein biophysics to help understand the microscopic exchange kinetics of data obtained using hydrogen-deuterium exchange mass spectrometry (HDX-MS). Finding a microscopic kinetic solution for HDX-MS data provides a window into local protein stability and energetics allowing them to be quantified and understood. Optimization of HDX-MS data is a significant challenge, however, due to the requirement to solve a large number of variables simultaneously with exceptionally large variable bounds. Modeled rates are frequently uncertain with an explicate dependency on the initial guess values. In order to enhance the search for a minimum solution in HDX-MS optimization, the ability of selected constrained variables to propagate throughout the data is considered. We reveal that locally bound constrained optimization induces a global effect on all variables. The global response to local constraints is large and surprisingly long-range, but the outcome is unpredictable, unexpectedly decreasing the overall accuracy of certain data sets depending on the stringency of the constraints. Utilizing previously described in-house validation criteria based on covariance matrices, a method is described that is able to accurately determine whether constraints benefit or impair the optimization of HDX-MS data. From this, we establish a new two-stage method for our online optimizer HDXmodeller that can effectively leverage locally bound variables to enhance HDX-MS data modeling.

Probing Universal Protein Dynamics Using Hydrogen-Deuterium Exchange Mass Spectrometry-Derived Residue-Level Gibbs Free Energy

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a powerful technique to monitor protein intrinsic dynamics. The technique provides high-resolution information on how protein intrinsic dynamics are altered in response to biological signals, such as ligand binding, oligomerization, or allosteric networks. However, identification, interpretation, and visualization of such events from HDX-MS data sets is challenging as these data sets consist of many individual data points collected across peptides, time points, and experimental conditions. Here, we present PyHDX, an open-source Python package and webserver, that allows the user to batch extract the universal quantity Gibbs free energy at residue levels over multiple protein conditions and homologues. The output is directly visualized on a linear map or 3D structures or is exported as .csv files or PyMOL scripts.

Advances in Hydrogen/Deuterium Exchange Mass Spectrometry and the Pursuit of Challenging Biological Systems

Solution-phase hydrogen/deuterium exchange (HDX) coupled to mass spectrometry (MS) is a widespread tool for structural analysis across academia and the biopharmaceutical industry. By monitoring the exchangeability of backbone amide protons, HDX-MS can reveal information about higher-order structure and dynamics throughout a protein, can track protein folding pathways, map interaction sites, and assess conformational states of protein samples. The combination of the versatility of the hydrogen/deuterium exchange reaction with the sensitivity of mass spectrometry has enabled the study of extremely challenging protein systems, some of which cannot be suitably studied using other techniques. Improvements over the past three decades have continually increased throughput, robustness, and expanded the limits of what is feasible for HDX-MS investigations. To provide an overview for researchers seeking to utilize and derive the most from HDX-MS for protein structural analysis, we summarize the fundamental principles, basic methodology, strengths and weaknesses, and the established applications of HDX-MS while highlighting new developments and applications.

A Review on Computational Approaches for Analyzing Hydrogen- Deuterium (H/D) Exchange of Proteins

Native state Hydrogen-Deuterium (H/D) exchange method has been used to study the structures and the unfolding pathways for quite a number of proteins. The H/D exchange method is generally monitored using nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) techniques. NMR-assisted H/D exchange methods primarily monitor the residue level fluctuation of proteins, whereas MS-assisted H/D exchange methods analyze multifold ensemble conformations of proteins. In this connection, quite a large number of computational tools and algorithms have been developed for processing and analyzing huge amount of the H/D exchange data generated from these techniques. In this review, most of the freely available computational tools associated with the H/D exchange of proteins have been comprehensively reviewed and scopes to improve/ develop novel computational approaches for analyzing the H/D exchange data of proteins have also been brought into fore.

Characterization and Management of Noise in HDX-MS Data Modeling

Quantification of hydrogen deuterium exchange (HDX) kinetics can provide information on the stability of individual amino acids in proteins by finding the degree to which the local backbone environment corresponds to that of a random coil. When characterized by mass spectrometry, extraction of HDX kinetics is not possible because different residue exchange rates become merged depending on the peptides that are formed during proteolytic digestion. We have recently developed an advanced programming tool called HDXmodeller, which enables the exchange rates of individual amino acids to be understood by optimization of low-resolution HDX-mass spectrometry (MS) data. HDXmodeller is also uniquely able to appraise each optimization and quantify the accuracy of modeled exchange rates ab initio using a novel autovalidation method based on a covariance matrix. Here, we address the noise-handling capabilities of HDXmodeller and demonstrate the effectiveness of the algorithm on self-inconsistent datasets. Reference intervals for experimental HDX-MS data are also derived, and this information is presented in an updated online workflow for HDXmodeller, allowing users to evaluate the consistency of their data. The development of a modified version of HDXmodeller is also discussed with enhanced noise-handling capability brought about through loss function optimization. Changes in optimizer accuracy with different loss functions are also demonstrated along with the effectiveness of HDXmodeller to select the most effective optimizer for different data using currently embedded autovalidation criteria.

HDXmodeller: an online webserver for high-resolution HDX-MS with auto-validation

The extent to which proteins are protected from hydrogen deuterium exchange (HDX) provides valuable insight into their folding, dynamics and interactions. Characterised by mass spectrometry (MS), HDX benefits from negligible mass restrictions and exceptional throughput and sensitivity but at the expense of resolution. Exchange mechanisms which naturally transpire for individual residues cannot be accurately located or understood because amino acids are characterised in differently sized groups depending on the extent of proteolytic digestion. Here we report HDXmodeller, the world's first online webserver for high-resolution HDX-MS. HDXmodeller accepts low-resolution HDX-MS input data and returns high-resolution exchange rates quantified for each residue. Crucially, HDXmodeller also returns a set of unique statistics that can correctly validate exchange rate models to an accuracy of 99%. Remarkably, these statistics are derived without any prior knowledge of the individual exchange rates and facilitate unparallel user confidence and the capacity to evaluate different data optimisation strategies.

Avoiding H/D Scrambling with Minimal Ion Transmission Loss for HDX-MS/MS-ETD Analysis on a High-Resolution Q-TOF Mass Spectrometer

Hydrogen/deuterium exchange monitored by mass spectrometry (HDX-MS) enables the study of protein dynamics by measuring the time-resolved deuterium incorporation into a protein incubated in D₂O. Using electron-based fragmentation in the gas phase it is possible to measure deuterium uptake at single-residue resolution. However, a prerequisite for this approach is that the solution-phase labeling is conserved in the gas phase prior to precursor fragmentation. It is therefore essential to reduce or even avoid intramolecular hydrogen/deuterium migration, which causes randomization of the deuterium labels along the peptide (hydrogen scrambling). Here, we describe an optimization strategy for reducing scrambling to a negligible level while minimizing the impact on sensitivity on a high-resolution Q-TOF equipped with ETD and an electrospray ionization interface consisting of a glass transfer capillary followed by a dual ion funnel. In our strategy we narrowed down the optimization to two accelerating potentials, and we defined the optimization of these in a simple rule by accounting for their interdependency in relation to scrambling and transmission efficiency. Using this rule, we were able to reduce scrambling from 75% to below 5% on average using the highly scrambling-sensitive quadruply charged P1 peptide scrambling probe resulting in a minor 33% transmission loss. To demonstrate the applicability of this approach, we probe the dynamics of certain regions in cytochrome c.

Estimating Constraints for Protection Factors from HDX-MS Data

Hydrogen/deuterium exchange monitored by mass spectrometry is a promising technique for rapidly fingerprinting structural and dynamical properties of proteins. The time-dependent change in the mass of any fragment of the polypeptide chain depends uniquely on the rate of exchange of its amide hydrogens, but determining the latter from the former is generally not possible. Here, we show that, if time-resolved measurements are available for a number of overlapping peptides that cover the whole sequence, rate constants for each amide hydrogen exchange (or equivalently, their protection factors) may be extracted and the uniqueness of the solutions obtained depending on the degree of peptide overlap. However, in most cases, the solution is not unique, and multiple alternatives must be considered. We provide a statistical method that clusters the solutions to further reduce their number. Such analysis always provides meaningful constraints on protection factors and can be used in situations in which obtaining more refined experimental data is impractical. It also provides a systematic way to improve data collection strategies to obtain unambiguous information at single-residue level (e.g., for assessing protein structure predictions at atomistic level).

Computational methods and challenges in hydrogen/deuterium exchange mass spectrometry

Hydrogen/Deuterium exchange (HDX) has been applied, since the 1930s, as an analytical tool to study the structure and dynamics of (small) biomolecules. The popularity of using HDX to study proteins increased drastically in the last two decades due to the successful combination with mass spectrometry (MS). Together with this growth in popularity, several technological advances have been made, such as improved quenching and fragmentation. As a consequence of these experimental improvements and the increased use of protein-HDXMS, large amounts of complex data are generated, which require appropriate analysis. Computational analysis of HDXMS requires several steps. A typical workflow for proteins consists of identification of (non-)deuterated peptides or fragments of the protein under study (local analysis), or identification of the deuterated protein as a whole (global analysis); determination of the deuteration level; estimation of the protection extent or exchange rates of the labile backbone amide hydrogen atoms; and a statistically sound interpretation of the estimated protection extent or exchange rates. Several algorithms, specifically designed for HDX analysis, have been proposed. They range from procedures that focus on one specific step in the analysis of HDX data to complete HDX workflow analysis tools. In this review, we provide an overview of the computational methods and discuss outstanding challenges. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:649-667, 2017.

Computational method allowing Hydrogen-Deuterium Exchange Mass Spectrometry at single amide Resolution

Hydrogen-deuterium exchange (HDX) coupled with mass spectrometry (HDXMS) is a rapid and effective method for localizing and determining protein stability and dynamics. Localization is routinely limited to a peptide resolution of 5 to 20 amino acid residues. HDXMS data can contain information beyond that needed for defining protein stability at single amide resolution. Here we present a method for extracting this information from an HDX dataset to generate a HDXMS protein stability fingerprint. High resolution (HR)-HDXMS was applied to the analysis of a model protein of a spectrin tandem repeat that exemplified an intuitive stability profile based on the linkage of two triple helical repeats connected by a helical linker. The fingerprint recapitulated expected stability maximums and minimums with interesting structural features that corroborate proposed mechanisms of spectrin flexibility and elasticity. HR-HDXMS provides the unprecedented ability to accurately assess protein stability at the resolution of a single amino acid. The determination of HDX stability fingerprints may be broadly applicable in many applications for understanding protein structure and function as well as protein ligand interactions.

A Residue-Resolved Bayesian Approach to Quantitative Interpretation of Hydrogen-Deuterium Exchange from Mass Spectrometry: Application to Characterizing Protein-Ligand Interactions

Characterization of interactions between proteins and other molecules is crucial for understanding the mechanisms of action of biological systems and, thus, drug discovery. An increasingly useful approach to mapping these interactions is measurement of hydrogen/deuterium exchange (HDX) using mass spectrometry (HDX-MS), which measures the time-resolved deuterium incorporation of peptides obtained by enzymatic digestion of the protein. Comparison of exchange rates between apo- and ligand-bound conditions results in a mapping of the differential HDX (ΔHDX) of the ligand. Residue-level analysis of these data, however, must account for experimental error, sparseness, and ambiguity due to overlapping peptides. Here, we propose a Bayesian method consisting of a forward model, noise model, prior probabilities, and a Monte Carlo sampling scheme. This method exploits a residue-resolved exponential rate model of HDX-MS data obtained from all peptides simultaneously, and explicitly models experimental error. The result is the best possible estimate of ΔHDX magnitude and significance for each residue given the data. We demonstrate the method by revealing richer structural interpretation of ΔHDX data on two nuclear receptors: vitamin D-receptor (VDR) and retinoic acid receptor gamma (RORγ). The method is implemented in HDX Workbench and as a standalone module of the open source Integrative Modeling Platform.

Mapping residual structure in intrinsically disordered proteins at residue resolution using millisecond hydrogen/deuterium exchange and residue averaging

Measurement of residual structure in intrinsically disordered proteins can provide insights into the mechanisms by which such proteins undergo coupled binding and folding. The present work describes an approach to measure residual structure in disordered proteins using millisecond hydrogen/deuterium (H/D) exchange in a conventional bottom-up peptide-based workflow. We used the exchange mid-point, relative to a totally deuterated control, to quantify the rate of H/D exchange in each peptide. A weighted residue-by-residue average of these midpoints was used to map the extent of residual structure at near single-residue resolution. We validated this approach both by simulating a disordered protein and experimentally using the p300 binding domain of ACTR, a model disordered protein already well-characterized by other approaches. Secondary structure elements mapped in the present work are in good agreement with prior nuclear magnetic resonance measurements. The new approach was somewhat limited by a loss of spatial resolution and subject to artifacts because of heterogeneities in intrinsic exchange. Approaches to correct these limitations are discussed.

Analytical Aspects of Hydrogen Exchange Mass Spectrometry

This article reviews the analytical aspects of measuring hydrogen exchange by mass spectrometry (HX MS). We describe the nature of analytical selectivity in hydrogen exchange, then review the analytical tools required to accomplish fragmentation, separation, and the mass spectrometry measurements under restrictive exchange quench conditions. In contrast to analytical quantitation that relies on measurements of peak intensity or area, quantitation in HX MS depends on measuring a mass change with respect to an undeuterated or deuterated control, resulting in a value between zero and the maximum amount of deuterium that can be incorporated. Reliable quantitation is a function of experimental fidelity and to achieve high measurement reproducibility, a large number of experimental variables must be controlled during sample preparation and analysis. The method also reports on important qualitative aspects of the sample, including conformational heterogeneity and population dynamics.

Protein hydrogen exchange at residue resolution by proteolytic fragmentation mass spectrometry analysis

Hydrogen exchange technology provides a uniquely powerful instrument for measuring protein structural and biophysical properties, quantitatively and in a nonperturbing way, and determining how these properties are implemented to produce protein function. A developing hydrogen exchange-mass spectrometry method (HX MS) is able to analyze large biologically important protein systems while requiring only minuscule amounts of experimental material. The major remaining deficiency of the HX MS method is the inability to deconvolve HX results to individual amino acid residue resolution. To pursue this goal we used an iterative optimization program (HDsite) that integrates recent progress in multiple peptide acquisition together with previously unexamined isotopic envelope-shape information and a site-resolved back-exchange correction. To test this approach, residue-resolved HX rates computed from HX MS data were compared with extensive HX NMR measurements, and analogous comparisons were made in simulation trials. These tests found excellent agreement and revealed the important computational determinants.

Peptide-column interactions and their influence on back exchange rates in hydrogen/deuterium exchange-MS

Hydrogen/deuterium exchange (HDX) methods generate useful information on protein structure and dynamics, ideally at the individual residue level. Most MS-based HDX methods involve a rapid proteolytic digestion followed by LC/MS analysis, with exchange kinetics monitored at the peptide level. Localizing specific sites of HDX is usually restricted to a resolution the size of the host peptide because gas-phase processes can scramble deuterium throughout the peptide. Subtractive methods may improve resolution, where deuterium levels of overlapping and nested peptides are used in a subtractive manner to localize exchange to smaller segments. In this study, we explore the underlying assumption of the subtractive method, namely, that the measured back exchange kinetics of a given residue is independent of its host peptide. Using a series of deuterated peptides, we show that secondary structure can be partially retained under quenched conditions, and that interactions between peptides and reversed-phase LC columns may both accelerate and decelerate residue HDX, depending upon peptide sequence and length. Secondary structure is induced through column interactions in peptides with a solution-phase propensity for structure, which has the effect of slowing HDX rates relative to predicted random coil values. Conversely, column interactions can orient random-coil peptide conformers to accelerate HDX, the degree to which correlates with peptide charge in solution, and which can be reversed by using stronger ion pairing reagents. The dependency of these effects on sequence and length suggest that subtractive methods for improving structural resolution in HDX-MS will not offer a straightforward solution for increasing exchange site resolution.

Minimizing back exchange in the hydrogen exchange-mass spectrometry experiment

The addition of mass spectrometry (MS) analysis to the hydrogen exchange (HX) proteolytic fragmentation experiment extends powerful HX methodology to the study of large biologically important proteins. A persistent problem is the degradation of HX information due to back exchange of deuterium label during the fragmentation-separation process needed to prepare samples for MS measurement. This paper reports a systematic analysis of the factors that influence back exchange (solution pH, ionic strength, desolvation temperature, LC column interaction, flow rates, system volume). The many peptides exhibit a range of back exchange due to intrinsic amino acid HX rate differences. Accordingly, large back exchange leads to large variability in D-recovery from one residue to another as well as one peptide to another that cannot be corrected for by reference to any single peptide-level measurement. The usual effort to limit back exchange by limiting LC time provides little gain. Shortening the LC elution gradient by 3-fold only reduced back exchange by ~2%, while sacrificing S/N and peptide count. An unexpected dependence of back exchange on ionic strength as well as pH suggests a strategy in which solution conditions are changed during sample preparation. Higher salt should be used in the first stage of sample preparation (proteolysis and trapping) and lower salt (<20 mM) and pH in the second stage before electrospray injection. Adjustment of these and other factors together with recent advances in peptide fragment detection yields hundreds of peptide fragments with D-label recovery of 90% ± 5%.

Biological insights from hydrogen exchange mass spectrometry

Over the past two decades, hydrogen exchange mass spectrometry (HXMS) has achieved the status of a widespread and routine approach in the structural biology toolbox. The ability of hydrogen exchange to detect a range of protein dynamics coupled with the accessibility of mass spectrometry to mixtures and large complexes at low concentrations result in an unmatched tool for investigating proteins challenging to many other structural techniques. Recent advances in methodology and data analysis are helping HXMS deliver on its potential to uncover the connection between conformation, dynamics and the biological function of proteins and complexes. This review provides a brief overview of the HXMS method and focuses on four recent reports to highlight applications that monitor structure and dynamics of proteins and complexes, track protein folding, and map the thermodynamics and kinetics of protein unfolding at equilibrium. These case studies illustrate typical data, analysis and results for each application and demonstrate a range of biological systems for which the interpretation of HXMS in terms of structure and conformational parameters provides unique insights into function. This article is part of a Special Issue entitled: Mass spectrometry in structural biology.

Improved sequence resolution by global analysis of overlapped peptides in hydrogen/deuterium exchange mass spectrometry

Management of the enormous amount of data produced during solution-phase hydrogen/deuterium exchange monitored by mass spectrometry has stimulated software analysis development. The proteolysis step of the experiment generates multiple peptide fragments, most of which overlap. Prior automated data reduction algorithms extract the deuteration level for individual peptides, but do not exploit the additional information arising from fragment overlap. Here, we describe an algorithm that determines discrete rate constant values to each of the amide hydrogens in overlapped fragments. By considering all of the overlapped peptide segments simultaneously, sequence resolution can be improved significantly, sometimes to the individual amino acid level. We have validated the method with simulated deuterium uptake data for seven overlapped fragments of a poly-Ala nonapeptide, and then applied it to extract rate constant values for the first 29 N-terminal amino acids of C22A FK506-binding protein.

HDXFinder: automated analysis and data reporting of deuterium/hydrogen exchange mass spectrometry

Hydrogen/deuterium exchange in combination with mass spectrometry (H/D MS) is a sensitive technique for detection of changes in protein conformation and dynamics. However, wide application of H/D MS has been hindered, in part, by the lack of computational tools necessary for efficient analysis of the large data sets associated with this technique. We report a novel web-based application for automatic analysis of H/D MS experimental data. This application relies on the high resolution of mass spectrometers to extract all isotopic envelopes before correlating these envelopes with individual peptides. Although a fully automatic analysis is possible, a variety of graphical tools are included to aid in the verification of correlations and rankings of the isotopic peptide envelopes. As a demonstration, the rate constants for H/D exchange of peptides from rabbit muscle pyruvate kinase are mapped onto the structure of this protein.

Many overlapping peptides for protein hydrogen exchange experiments by the fragment separation-mass spectrometry method

Measurement of the naturally occurring hydrogen exchange (HX) behavior of proteins can in principle provide highly resolved thermodynamic and kinetic information on protein structure, dynamics, and interactions. The HX fragment separation-mass spectrometry method (HX-MS) is able to measure hydrogen exchange in biologically important protein systems that are not accessible to NMR methods. In order to achieve high structural resolution in HX-MS experiments, it will be necessary to obtain many sequentially overlapping peptide fragments and be able to identify and analyze them efficiently and accurately by mass spectrometry. This paper describes operations which, when applied to four different proteins ranging in size from 140 to 908 residues, routinely provides hundreds of useful unique peptides, covering the entire protein length many times over. Coverage in terms of the average number of peptide fragments that span each amino acid exceeds 10. The ability to achieve these results required the integrated application of experimental methods that are described here and a computer analysis program, called ExMS, described in a following paper.