How amide hydrogens exchange in native proteins

Quantification of CH and NH/π-Stacking Interactions in Cells Using Nuclear Magnetic Resonance Spectroscopy

π-Stacking, a type of noncovalent interactions involving aromatic residues, plays an important role in protein folding and function. In this work, an attempt has been made to measure CH/π and NH/π stacking interactions in a protein in Escherichia coli cells using a combined double-mutant cycle and nuclear magnetic resonance spectroscopy method. The results show that the CH/π and NH/π stacking interactions are generally weaker in cells than those in the buffer. The transient intermolecular noncovalent interactions between the protein and the complex cellular environment may compete with and thus weaken the stacking interactions in the protein. The weakening of stacking interactions can enhance the local conformational opening of proteins in E. coli cells. This is evident from the faster rates of amide hydrogen/deuterium exchange observed in cells than in the buffer, for residues that undergo local conformational opening. This study highlights the influence of the cellular environment on π-stacking and the conformational dynamics of proteins.

Analysis of proteins in the light of mutations

Proteins have evolved through mutations-amino acid substitutions-since life appeared on Earth, some 109 years ago. The study of these phenomena has been of particular significance because of their impact on protein stability, function, and structure. This study offers a new viewpoint on how the most recent findings in these areas can be used to explore the impact of mutations on protein sequence, stability, and evolvability. Preliminary results indicate that: (1) mutations can be viewed as sensitive probes to identify 'typos' in the amino-acid sequence, and also to assess the resistance of naturally occurring proteins to unwanted sequence alterations; (2) the presence of 'typos' in the amino acid sequence, rather than being an evolutionary obstacle, could promote faster evolvability and, in turn, increase the likelihood of higher protein stability; (3) the mutation site is far more important than the substituted amino acid in terms of the marginal stability changes of the protein, and (4) the unpredictability of protein evolution at the molecular level-by mutations-exists even in the absence of epistasis effects. Finally, the Darwinian concept of evolution "descent with modification" and experimental evidence endorse one of the results of this study, which suggests that some regions of any protein sequence are susceptible to mutations while others are not. This work contributes to our general understanding of protein responses to mutations and may spur significant progress in our efforts to develop methods to accurately forecast changes in protein stability, their propensity for metamorphism, and their ability to evolve.

De Novo Synthesis and Structural Elucidation of CDR-H3 Loop Mimics

The binding affinity of antibodies to specific antigens stems from a remarkably broad repertoire of hypervariable loops known as complementarity-determining regions (CDRs). While recognizing the pivotal role of the heavy-chain 3 CDRs (CDR-H3s) in maximizing antibody-antigen affinity and specificity, the key structural determinants responsible for their adaptability to diverse loop sequences, lengths, and noncanonical structures are hitherto unknown. To address this question, we achieved a de novo synthesis of bulged CDR-H3 mimics excised from their full antibody context. CD and NMR data revealed that these stable standalone β-hairpin scaffolds are well-folded and retain many of the native bulge CDR-H3 features in water. In particular, the tryptophan residue, highly conserved across CDR-H3 sequences, was found to extend the kinked base of these β-bulges through a combination of stabilizing intramolecular hydrogen bond and CH/π interaction. The structural ensemble consistent with our NMR observations exposed the dynamic nature of residues at the base of the loop, suggesting that β-bulges act as molecular hinges connecting the rigid stem to the more flexible loops of CDR-H3s. We anticipate that this deeper structural understanding of CDR-H3s will lay the foundation to inform the design of antibody drugs broadly and engineer novel CDR-H3 peptide scaffolds as therapeutics.

Interpretation of Hydrogen/Deuterium Exchange Mass Spectrometry

This paper sheds light on the meaning of hydrogen/deuterium exchange-mass spectrometry (HDX-MS) data. HDX-MS data provide not structural information but dynamic information on an analyte protein. First, the reaction mechanism of backbone amide HDX reaction is considered and the correlation between the parameters from an X-ray crystal structure and the protection factors of HDX reactions of cytochrome c is evaluated. The presence of H-bonds in a protein structure has a strong influence on HDX rates which represent protein dynamics, while the solvent accessibility only weakly affects the HDX rates. Second, the energy diagrams of the HDX reaction at each residue in the presence and absence of perturbation are described. Whereas the free energy change upon mutation can be directly measured by the HDX rates, the free energy change upon ligand binding may be complicated due to the presence of unbound analyte protein in the protein-ligand mixture. Third, the meanings of HDX and other biophysical techniques are explained using a hypothetical protein folding well. The shape of the protein folding well describes the protein dynamics and provides Boltzmann distribution of open and closed states which yield HDX protection factors, while a protein's crystal structure represents a snapshot near the bottom of the well. All biophysical data should be consistent yet provide different information because they monitor different parts of the same protein folding well.

Identification of the Thermal Activation Network in Human 15-Lipoxygenase-2: Divergence from Plant Orthologs and Its Relationship to Hydrogen Tunneling Activation Barriers

The oxidation of polyunsaturated fatty acids by lipoxygenases (LOXs) is initiated by a C-H cleavage step in which the hydrogen atom is transferred quantum mechanically (i.e., via tunneling). In these reactions, protein thermal motions facilitate the conversion of ground-state enzyme-substrate complexes to tunneling-ready configurations and are thus important for transferring energy from the solvent to the active site for the activation of catalysis. In this report, we employed temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX-MS) to identify catalytically linked, thermally activated peptides in a representative animal LOX, human epithelial 15-LOX-2. TDHDX-MS of wild-type 15-LOX-2 was compared to two active site mutations that retain structural stability but have increased activation energies (Ea) of catalysis. The Ea value of one variant, V427L, is implicated to arise from suboptimal substrate positioning by increased active-site side chain rotamer dynamics, as determined by X-ray crystallography and ensemble refinement. The resolved thermal network from the comparative Eas of TDHDX-MS between wild-type and V426A is localized along the front face of the 15-LOX-2 catalytic domain. The network contains a clustering of isoleucine, leucine, and valine side chains within the helical peptides. This thermal network of 15-LOX-2 is different in location, area, and backbone structure compared to a model plant lipoxygenase from soybean that exhibits a low Ea value of catalysis compared to the human ortholog. The presented data provide insights into the divergence of thermally activated protein motions in plant and animal LOXs and their relationships to the enthalpic barriers for facilitating hydrogen tunneling.

ZundEig: The Structure of the Proton in Liquid Water from Unsupervised Learning

The structure of the excess proton in liquid water has been the subject of lively debate on both experimental and theoretical fronts for the last century. Fluctuations of the proton are typically interpreted in terms of limiting states referred to as the Eigen and Zundel species. Here, we put these ideas under the microscope, taking advantage of recent advances in unsupervised learning that use local atomic descriptors to characterize environments of acidic water combined with advanced clustering techniques. Our agnostic approach leads to the observation of only one charged cluster and two neutral ones. We demonstrate that the charged cluster involving the excess proton is best seen as an ionic topological defect in water's hydrogen bond network, forming a single local minimum on the global free-energy landscape. This charged defect is a highly fluxional moiety, where the idealized Eigen and Zundel species are neither limiting configurations nor distinct thermodynamic states. Instead, the ionic defect enhances the presence of neutral water defects through strong interactions with the network. We dub the combination of the charged and neutral defect clusters as ZundEig, demonstrating that the fluctuations between these local environments provide a general framework for rationalizing more descriptive notions of the proton in the existing literature.

Structural mechanism of a drug-binding process involving a large conformational change of the protein target

Proteins often undergo large conformational changes when binding small molecules, but atomic-level descriptions of such events have been elusive. Here, we report unguided molecular dynamics simulations of Abl kinase binding to the cancer drug imatinib. In the simulations, imatinib first selectively engages Abl kinase in its autoinhibitory conformation. Consistent with inferences drawn from previous experimental studies, imatinib then induces a large conformational change of the protein to reach a bound complex that closely resembles published crystal structures. Moreover, the simulations reveal a surprising local structural instability in the C-terminal lobe of Abl kinase during binding. The unstable region includes a number of residues that, when mutated, confer imatinib resistance by an unknown mechanism. Based on the simulations, NMR spectra, hydrogen-deuterium exchange measurements, and thermostability measurements and estimates, we suggest that these mutations confer imatinib resistance by exacerbating structural instability in the C-terminal lobe, rendering the imatinib-bound state energetically unfavorable.

Engineering the Active Site Lid Dynamics to Improve the Catalytic Efficiency of Yeast Cytosine Deaminase

Conformational dynamics is important for enzyme catalysis. However, engineering dynamics to achieve a higher catalytic efficiency is still challenging. In this work, we develop a new strategy to improve the activity of yeast cytosine deaminase (yCD) by engineering its conformational dynamics. Specifically, we increase the dynamics of the yCD C-terminal helix, an active site lid that controls the product release. The C-terminal is extended by a dynamical single α-helix (SAH), which improves the product release rate by up to ~8-fold, and the overall catalytic rate kcat by up to ~2-fold. It is also shown that the kcat increase is due to the favorable activation entropy change. The NMR H/D exchange data indicate that the conformational dynamics of the transition state analog complex increases as the helix is extended, elucidating the origin of the enhanced catalytic entropy. This study highlights a novel dynamics engineering strategy that can accelerate the overall catalysis through the entropy-driven mechanism.

Integrating Hydrogen Deuterium Exchange-Mass Spectrometry with Molecular Simulations Enables Quantification of the Conformational Populations of the Sugar Transporter XylE

A yet unresolved challenge in structural biology is to quantify the conformational states of proteins underpinning function. This challenge is particularly acute for membrane proteins owing to the difficulties in stabilizing them for in vitro studies. To address this challenge, we present an integrative strategy that combines hydrogen deuterium exchange-mass spectrometry (HDX-MS) with ensemble modeling. We benchmark our strategy on wild-type and mutant conformers of XylE, a prototypical member of the ubiquitous Major Facilitator Superfamily (MFS) of transporters. Next, we apply our strategy to quantify conformational ensembles of XylE embedded in different lipid environments. Further application of our integrative strategy to substrate-bound and inhibitor-bound ensembles allowed us to unravel protein-ligand interactions contributing to the alternating access mechanism of secondary transport in atomistic detail. Overall, our study highlights the potential of integrative HDX-MS modeling to capture, accurately quantify, and subsequently visualize co-populated states of membrane proteins in association with mutations and diverse substrates and inhibitors.

Design of self-assembled glycopolymeric zwitterionic micelles as removable protein stabilizing agents

Developing stabilizers that protect proteins from denaturation under stress, and are easy to remove from solutions, is a challenge in protein therapeutics. In this study, micelles made of trehalose, a zwitterionic polymer (poly-sulfobetaine; poly-SPB), and polycaprolactone (PCL) were synthesized by a one-pot reversible addition-fragmentation chain-transfer (RAFT) polymerization reaction. The micelles protect lactate dehydrogenase (LDH) and human insulin from denaturation due to stresses like thermal incubation and freezing, and help them retain higher-order structures. Importantly, the protected proteins are readily isolated from the micelles by ultracentrifugation, with over 90% recovery, and almost all enzymatic activity is retained. This suggests the great potential of poly-SPB-based micelles for use in applications requiring protection and removal as required. The micelles may also be used to effectively stabilize protein-based vaccines and drugs.

Polyampholyte-Based Polymer Hydrogels for the Long-Term Storage, Protection and Delivery of Therapeutic Proteins

Protein storage and delivery are crucial for biomedical applications such as protein therapeutics and recombinant proteins. Lack of proper protocols results in the denaturation of proteins, rendering them inactive and manifesting undesired side effects. In this study, polyampholyte-based (succinylated ε-poly-l-lysine) hydrogels containing polyvinyl alcohol and polyethylene glycol polymer matrices to stabilize proteins are developed. These hydrogels facilitated the loading and release of therapeutic amounts of proteins and withstood thermal and freezing stress (15 freeze-thaw cycles and temperatures of -80 °C and 37 °C), without resulting in protein denaturation and aggregation. To the best of our knowledge, this strategy has not been applied to the design of hydrogels constituting polymers, (in particular, polyampholyte-based polymers) which have inherent efficiency to stabilize proteins and protect them from denaturation. Our findings can open up new avenues in protein biopharmaceutics for the design of materials that can store therapeutic proteins long-term under severe stress and safely deliver them.

Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromolecular complexes

Small-angle neutron scattering (SANS) with contrast variation (CV) is a valuable technique in the structural biology toolchest. Accurate structural parameters-e.g., radii of gyration, volumes, dimensions, and distance distribution(s)-can be derived from the SANS-CV data to yield the shape and disposition of the individual components within stable complexes. Contrast variation is achieved through the substitution of hydrogen isotopes (¹H for ²H) in molecules and solvents to alter the neutron scattering properties of each component of a complex. While SANS-CV can be used a stand-alone technique for interrogating the overall structure of biomacromolecules in solution, it also complements other methods such as small-angle X-ray scattering, crystallography, nuclear magnetic resonance, and cryo-electron microscopy. Undertaking a SANS-CV experiment is challenging, due in part to the preparation of significant quantities of monodisperse samples that may require deuterium (²H) labeling. Nevertheless, SANS-CV can be used to study a diverse range biomacromolecular complexes including protein-protein and protein-nucleic acid systems, membrane proteins, and flexible systems resistant to crystallization. This chapter describes how to approach the data analysis and modeling of SANS data, including: (1) Analysis of the forward scattering (I(0)) and calculation of theoretical estimates of contrast; (2) Analysis of the contrast dependence of the radius of gyration using the Stuhrmann plot and parallel axis theorem; (3) Calculation of composite scattering functions to evaluate the size, shape, and dispositions of individual components within a complex, and; (4) Development of real-space models to fit the SANS-CV data using volume-element bead modeling or atomistic rigid body modeling.

Temperature-dependent hydrogen deuterium exchange shows impact of analog binding on adenosine deaminase flexibility but not embedded thermal networks

The analysis of hydrogen deuterium exchange by mass spectrometry as a function of temperature and mutation has emerged as a generic and efficient tool for the spatial resolution of protein networks that are proposed to function in the thermal activation of catalysis. In this work, we extend temperature-dependent hydrogen deuterium exchange from apo-enzyme structures to protein-ligand complexes. Using adenosine deaminase as a prototype, we compared the impacts of a substrate analog (1-deaza-adenosine) and a very tight-binding inhibitor/transition state analog (pentostatin) at single and multiple temperatures. At a single temperature, we observed different hydrogen deuterium exchange-mass spectrometry properties for the two ligands, as expected from their 106-fold differences in strength of binding. By contrast, analogous patterns for temperature-dependent hydrogen deuterium exchange mass spectrometry emerge in the presence of both 1-deaza-adenosine and pentostatin, indicating similar impacts of either ligand on the enthalpic barriers for local protein unfolding. We extended temperature-dependent hydrogen deuterium exchange to a function-altering mutant of adenosine deaminase in the presence of pentostatin and revealed a protein thermal network that is highly similar to that previously reported for the apo-enzyme (Gao et al., 2020, JACS 142, 19936-19949). Finally, we discuss the differential impacts of pentostatin binding on overall protein flexibility versus site-specific thermal transfer pathways in the context of models for substrate-induced changes to a distributed protein conformational landscape that act in synergy with embedded protein thermal networks to achieve efficient catalysis.

Collective variable discovery in the age of machine learning: reality, hype and everything in between

Understanding the kinetics and thermodynamics profile of biomolecules is necessary to understand their functional roles which has a major impact in mechanism driven drug discovery. Molecular dynamics simulation has been routinely used to understand conformational dynamics and molecular recognition in biomolecules. Statistical analysis of high-dimensional spatiotemporal data generated from molecular dynamics simulation requires identification of a few low-dimensional variables which can describe the essential dynamics of a system without significant loss of information. In physical chemistry, these low-dimensional variables are often called collective variables. Collective variables are used to generate reduced representations of free energy surfaces and calculate transition probabilities between different metastable basins. However the choice of collective variables is not trivial for complex systems. Collective variables range from geometric criteria such as distances and dihedral angles to abstract ones such as weighted linear combinations of multiple geometric variables. The advent of machine learning algorithms led to increasing use of abstract collective variables to represent biomolecular dynamics. In this review, I will highlight several nuances of commonly used collective variables ranging from geometric to abstract ones. Further, I will put forward some cases where machine learning based collective variables were used to describe simple systems which in principle could have been described by geometric ones. Finally, I will put forward my thoughts on artificial general intelligence and how it can be used to discover and predict collective variables from spatiotemporal data generated by molecular dynamics simulations.

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.

Proteins' Evolution upon Point Mutations

As the reader must be already aware, state-of-the-art protein folding prediction methods have reached a smashing success in their goal of accurately determining the three-dimensional structures of proteins. Yet, a solution to simple problems such as the effects of protein point mutations on their (i) native conformation; (ii) marginal stability; (iii) ensemble of high-energy nativelike conformations; and (iv) metamorphism propensity and, hence, their evolvability, remains as an unsolved problem. As a plausible solution to the latter, some properties of the amide hydrogen-deuterium exchange, a highly sensitive probe of the structure, stability, and folding of proteins, are assessed from a new perspective. The preliminary results indicate that the protein marginal stability change upon point mutations provides the necessary and sufficient information to estimate, through a Boltzmann factor, the evolution of the amide hydrogen exchange protection factors and, consequently, that of the ensemble of folded conformations coexisting with the native state. This work contributes to our general understanding of the effects of point mutations on proteins and may spur significant progress in our efforts to develop methods to determine the appearance of new folds and functions accurately.

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.

Prediction and Validation of a Protein's Free Energy Surface Using Hydrogen Exchange and (Importantly) Its Denaturant Dependence

The denaturant dependence of hydrogen-deuterium exchange (HDX) is a powerful measurement to identify the breaking of individual H-bonds and map the free energy surface (FES) of a protein including the very rare states. Molecular dynamics (MD) can identify each partial unfolding event with atomic-level resolution. Hence, their combination provides a great opportunity to test the accuracy of simulations and to verify the interpretation of HDX data. For this comparison, we use Upside, our new and extremely fast MD package that is capable of folding proteins with an accuracy comparable to that of all-atom methods. The FESs of two naturally occurring and two designed proteins are so generated and compared to our NMR/HDX data. We find that Upside's accuracy is considerably improved upon modifying the energy function using a new machine-learning procedure that trains for proper protein behavior including realistic denatured states in addition to stable native states. The resulting increase in cooperativity is critical for replicating the HDX data and protein stability, indicating that we have properly encoded the underlying physiochemical interactions into an MD package. We did observe some mismatch, however, underscoring the ongoing challenges faced by simulations in calculating accurate FESs. Nevertheless, our ensembles can identify the properties of the fluctuations that lead to HDX, whether they be small-, medium-, or large-scale openings, and can speak to the breadth of the native ensemble that has been a matter of debate.

Structure and dynamics of nanoconfined water and aqueous solutions

This review is devoted to discussing recent progress on the structure, thermodynamic, reactivity, and dynamics of water and aqueous systems confined within different types of nanopores, synthetic and biological. Currently, this is a branch of water science that has attracted enormous attention of researchers from different fields interested to extend the understanding of the anomalous properties of bulk water to the nanoscopic domain. From a fundamental perspective, the interactions of water and solutes with a confining surface dramatically modify the liquid's structure and, consequently, both its thermodynamical and dynamical behaviors, breaking the validity of the classical thermodynamic and phenomenological description of the transport properties of aqueous systems. Additionally, man-made nanopores and porous materials have emerged as promising solutions to challenging problems such as water purification, biosensing, nanofluidic logic and gating, and energy storage and conversion, while aquaporin, ion channels, and nuclear pore complex nanopores regulate many biological functions such as the conduction of water, the generation of action potentials, and the storage of genetic material. In this work, the more recent experimental and molecular simulations advances in this exciting and rapidly evolving field will be reported and critically discussed.

Dynamics and Conformational Changes in Human NEIL2 DNA Glycosylase Analyzed by Hydrogen/Deuterium Exchange Mass Spectrometry

Base excision DNA repair (BER) is necessary for removal of damaged nucleobases from the genome and their replacement with normal nucleobases. BER is initiated by DNA glycosylases, the enzymes that cleave the N-glycosidic bonds of damaged deoxynucleotides. Human endonuclease VIII-like protein 2 (hNEIL2), belonging to the helix-two-turn-helix structural superfamily of DNA glycosylases, is an enzyme uniquely specific for oxidized pyrimidines in non-canonical DNA substrates such as bubbles and loops. The structure of hNEIL2 has not been solved; its closest homologs with known structures are NEIL2 from opossum and from giant mimivirus. Here we analyze the conformational dynamics of free hNEIL2 using a combination of hydrogen/deuterium exchange mass spectrometry, homology modeling and molecular dynamics simulations. We show that a prominent feature of vertebrate NEIL2 - a large insert in its N-terminal domain absent from other DNA glycosylases - is unstructured in solution. It was suggested that helix-two-turn-helix DNA glycosylases undergo open-close transition upon DNA binding, with the large movement of their N- and C-terminal domains, but the open conformation has been elusive to capture. Our data point to the open conformation as favorable for free hNEIL2 in solution. Overall, our results are consistent with the view of hNEIL2 as a conformationally flexible protein, which may be due to its participation in the repair of non-canonical DNA structures and/or to the involvement in functional and regulatory protein-protein interactions.

Hydrogen/Deuterium Exchange Measurements May Provide an Incomplete View of Protein Dynamics: a Case Study on Cytochrome c

Many aspects of protein function rely on conformational fluctuations. Hydrogen/deuterium exchange (HDX) mass spectrometry (MS) provides a window into these dynamics. Despite the widespread use of HDX-MS, it remains unclear whether this technique provides a truly comprehensive view of protein dynamics. HDX is mediated by H-bond-opening/closing events, implying that HDX methods provide an H-bond-centric view. This raises the question if there could be fluctuations that leave the H-bond network unaffected, thereby rendering them undetectable by HDX-MS. We explore this issue in experiments on cytochrome c (cyt c). Compared to the Fe(II) protein, Fe(III) cyt c shows enhanced deuteration on both the distal and proximal sides of the heme. Previous studies have attributed the enhanced dynamics of Fe(III) cyt c to the facile and reversible rupture of the distal M80-Fe(III) bond. Using molecular dynamics (MD) simulations, we conducted a detailed analysis of various cyt c conformers. Our MD data confirm that rupture of the M80-Fe(III) contact triggers major reorientation of the distal Ω loop. Surprisingly, this event takes place with only miniscule H-bonding alterations. In other words, the distal loop dynamics are almost "HDX-silent". Moreover, distal loop movements cannot account for enhanced dynamics on the opposite (proximal) side of the heme. Instead, enhanced deuteration of Fe(III) cyt c is attributed to sparsely populated conformers where both the distal (M80) and proximal (H18) coordination bonds have been ruptured, along with opening of numerous H-bonds on both sides of the heme. We conclude that there can be major structural fluctuations that are only weakly coupled to changes in H-bonding, making them virtually impossible to track by HDX-MS. In such cases, HDX-MS may provide an incomplete view of protein dynamics.

Thoughts on the Protein's Native State

The presence of metamorphism in the protein's native state is not yet fully understood. To shed light on this issue, we present an assessment, in terms of the amide hydrogen exchange protection factor, that aims to determine the possible existence of structural fluctuations in the native-state consistent with both the upper-bound marginal stability of proteins and the presence of metamorphism. The preliminary results enable us to conclude that the native-state metamorphism is, indeed, more probable than previously thought.

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

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

Hydrogen-Deuterium Exchange within Adenosine Deaminase, a TIM Barrel Hydrolase, Identifies Networks for Thermal Activation of Catalysis

Proteins are intrinsically flexible macromolecules that undergo internal motions with time scales spanning femtoseconds to milliseconds. These fluctuations are implicated in the optimization of reaction barriers for enzyme catalyzed reactions. Time, temperature, and mutation dependent hydrogen-deuterium exchange coupled to mass spectrometry (HDX-MS) has been previously employed to identify spatially resolved, catalysis-linked dynamical regions of enzymes. We now extend this technique to pursue the correlation of protein flexibility and chemical reactivity within the diverse and widespread TIM barrel proteins, targeting murine adenosine deaminase (mADA) that catalyzes the irreversible deamination of adenosine to inosine and ammonia. Following a structure-function analysis of rate and activation energy for a series of mutations at a second sphere phenylalanine positioned in proximity to the bound substrate, the catalytically impaired Phe61Ala with an elevated activation energy (Ea = 7.5 kcal/mol) and the wild type (WT) mADA (Ea = 5.0 kcal/mol) were selected for HDX-MS experiments. The rate constants and activation energies of HDX for peptide segments are quantified and used to assess mutation-dependent changes in local and distal motions. Analyses reveal that approximately 50% of the protein sequence of Phe61Ala displays significant changes in the temperature dependence of HDX behaviors, with the dominant change being an increase in protein flexibility. Utilizing Phe61Ile, which displays the same activation energy for k_cat as WT, as a control, we were able to further refine the HDX analysis, highlighting the regions of mADA that are altered in a functionally relevant manner. A map is constructed that illustrates the regions of protein that are proposed to be essential for the thermal optimization of active site configurations that dominate reaction barrier crossings in the native enzyme.

Dynamics of an LPS translocon induced by substrate and an antimicrobial peptide

Lipopolysaccharide (LPS) transport to the outer membrane (OM) is a crucial step in the biogenesis of microbial surface defenses. Although many features of the translocation mechanism have been elucidated, molecular details of LPS insertion via the LPS transport (Lpt) OM protein LptDE remain elusive. Here, we integrate native MS with hydrogen-deuterium exchange MS and molecular dynamics simulations to investigate the influence of substrate and peptide binding on the conformational dynamics of LptDE. Our data reveal that LPS induces opening of the LptD β-taco domain, coupled with conformational changes on β-strands adjacent to the putative lateral exit gate. Conversely, an antimicrobial peptide, thanatin, stabilizes the β-taco, thereby preventing LPS transport. Our results illustrate that LPS insertion into the OM relies on concerted opening movements of both the β-barrel and β-taco domains of LptD, and suggest a means for developing antimicrobial therapeutics targeting this essential process in Gram-negative ESKAPE pathogens.

Insight to Functional Conformation and Noncovalent Interactions of Protein-Protein Assembly Using MALDI Mass Spectrometry

Noncovalent interactions are the keys to the structural organization of biomolecule e.g., proteins, glycans, lipids in the process of molecular recognition processes e.g., enzyme-substrate, antigen-antibody. Protein interactions lead to conformational changes, which dictate the functionality of that protein-protein complex. Besides biophysics techniques, noncovalent interaction and conformational dynamics, can be studied via mass spectrometry (MS), which represents a powerful tool, due to its low sample consumption, high sensitivity, and label-free sample. In this review, the focus will be placed on Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) and its role in the analysis of protein-protein noncovalent assemblies exploring the relationship within noncovalent interaction, conformation, and biological function.

Dramatic Shape Changes Occur as Cytochrome c Folds

Extensive experimental studies on the folding of cytochrome c (Cyt c) make this small protein an ideal target for atomic detailed simulations for the purposes of quantitatively characterizing the structural transitions and the associated time scales for folding to the native state from an ensemble of unfolded states. We use previously generated atomically detailed folding trajectories by the stochastic difference equation in length to calculate the time-dependent changes in the small-angle X-ray scattering (SAXS) profiles. Excellent agreement is obtained between experiments and simulations for the time-dependent SAXS spectra, allowing us to identify the structures of the folding intermediates, which shows that Cyt c reaches the native state by a sequential folding mechanism. Using the ensembles of structures along the folding pathways, we show that compaction and the sphericity of Cyt c change dramatically from the prolate ellipsoid shape in the unfolded state to the spherical native state. Our data, which are in unprecedented quantitative agreement with all aspects of time-resolved SAXS experiments, show that hydrophobic collapse and amide group protection coincide on the 100 microseconds time scale, which is in accordance with ultrafast hydrogen/deuterium exchange studies. Based on these results, we propose that compaction of polypeptide chains, accompanied by dramatic shape changes, is a universal characteristic of globular proteins, regardless of the underlying folding mechanism.

Polyol and sugar osmolytes can shorten protein hydrogen bonds to modulate function

Polyol and sugar osmolytes are commonly used in therapeutic protein formulations. How they may affect protein structure and function is an important question. In this work, through NMR measurements, we show that glycerol and sorbitol (polyols), as well as glucose (sugar), can shorten protein backbone hydrogen bonds. The hydrogen bond shortening is also captured by molecular dynamics simulations, which suggest a hydrogen bond competition mechanism. Specifically, osmolytes weaken hydrogen bonds between the protein and solvent to strengthen those within the protein. Although the hydrogen bond change is small, with the average experimental cross hydrogen bond 3hJNC' coupling of two proteins GB3 and TTHA increased by ~ 0.01 Hz by the three osmolytes (160 g/L), its effect on protein function should not be overlooked. This is exemplified by the PDZ3-peptide binding where several intermolecular hydrogen bonds are formed and osmolytes shift the equilibrium towards the bound state.

Paramagnetic relaxation enhancement-assisted structural characterization of a partially disordered conformation of ubiquitin

Nuclear magnetic resonance (NMR) is a powerful tool to study three-dimensional structures as well as protein conformational fluctuations in solution, but it is compromised by increases in peak widths and missing signals. We previously reported that ubiquitin has two folded conformations, N₁ and N₂ and plus another folded conformation, I, in which some amide group signals of residues 33-41 almost disappeared above 3 kbar at pH 4.5 and 273 K. Thus, well-converged structural models could not be obtained for this region owing to the absence of distance restraints. Here, we reexamine the problem using the ubiquitin Q41N variant as a model for this locally disordered conformation, I. We demonstrate that the variant shows pressure-induced loss of backbone amide group signals at residues 28, 33, 36, and 39-41 like the wild-type, with a similar but smaller effect on CαH and CβH signals. In order to characterize this I structure, we measured paramagnetic relaxation enhancement (PRE) under high pressure to obtain distance restraints, and calculated the structure assisted by Bayesian inference. We conclude that the more disordered I conformation observed at pH 4.0, 278 K, and 2.5 kbar largely retained the N₂ conformation, although the amide groups at residues 33-41 have more heterogeneous conformations and more contact with water, which differ from the N₁ and N₂ states. The PRE-assisted strategy has the potential to improve structural characterization of proteins that lack NMR signals, especially for relatively more open and hydrated protein conformations.

Structural predictions of the functions of membrane proteins from HDX-MS

HDX-MS has emerged as a powerful tool to interrogate the structure and dynamics of proteins and their complexes. Recent advances in the methodology and instrumentation have enabled the application of HDX-MS to membrane proteins. Such targets are challenging to investigate with conventional strategies. Developing new tools are therefore pertinent for improving our fundamental knowledge of how membrane proteins function in the cell. Importantly, investigating this central class of biomolecules within their native lipid environment remains a challenge but also a key goal ahead. In this short review, we outline recent progresses in dissecting the conformational mechanisms of membrane proteins using HDX-MS. We further describe how the use of computational strategies can aid the interpretation of experimental data and enable visualisation of otherwise intractable membrane protein states. This unique integration of experiments with computations holds significant potential for future applications.

Assessing Site-Specific Enhancements Imparted by Hyperpolarized Water in Folded and Unfolded Proteins by 2D HMQC NMR

Hyperpolarized water can be a valuable aid in protein NMR, leading to amide group ¹H polarizations that are orders of magnitude larger than their thermal counterparts. Suitable procedures can exploit this to deliver 2D ¹H–¹⁵N correlations with good resolution and enhanced sensitivity. These enhancements depend on the exchange rates between the amides and the water, thereby yielding diagnostic information about solvent accessibility. This study applied this “HyperW” method to four proteins exhibiting a gamut of exchange behaviors: PhoA^(350–471), an unfolded 122-residue fragment; barstar, a fully folded ribonuclease inhibitor; R17, a 13.3 kDa system possessing folded and unfolded forms under slow interconversion; and drkN SH3, a protein domain whose folded and unfolded forms interchange rapidly and with temperature-dependent population ratios. For PhoA4^(350–471) HyperW sensitivity enhancements were ≥300×, as expected for an unfolded protein sequence. Though fully folded, barstar also exhibited substantial enhancements; these, however, were not uniform and, according to CLEANEX experiments, reflected the solvent-exposed residues. R17 showed the expected superposition of ≥100-fold enhancements for its unfolded form, coexisting with more modest enhancements for their folded counterparts. Unexpected, however, was the behavior of drkN SH3, for which HyperW enhanced the unfolded but, surprisingly, enhanced even more certain folded protein sites. These preferential enhancements were repeatedly and reproducibly observed. A number of explanations—including three-site exchange magnetization transfers between water and the unfolded and folded states; cross-correlated relaxation processes from hyperpolarized “structural” waters and labile side-chain protons; and the possibility that faster solvent exchange rates characterize certain folded sites over their unfolded counterparts—are considered to account for them.

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

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

Reconciling Simulated Ensembles of Apomyoglobin with Experimental Hydrogen/Deuterium Exchange Data Using Bayesian Inference and Multiensemble Markov State Models

Hydrogen/deuterium exchange (HDX) is a powerful technique to investigate protein conformational dynamics at amino acid resolution. Because HDX provides a measurement of solvent exposure of backbone hydrogens, ensemble-averaged over potentially slow kinetic processes, it has been challenging to use HDX protection factors to refine structural ensembles obtained from molecular dynamics simulations. This entails dual challenges: (1) identifying structural observables that best correlate with backbone amide protection from exchange and (2) restraining these observables in molecular simulations to model ensembles consistent with experimental measurements. Here, we make significant progress on both fronts. First, we describe an improved predictor of HDX protection factors from structural observables in simulated ensembles, parametrized from ultralong molecular dynamics simulation trajectory data, with a Bayesian inference approach used to retain the full posterior distribution of model parameters. We next present a new method for obtaining simulated ensembles in agreement with experimental HDX protection factors, in which molecular simulations are performed at various temperatures and restraint biases and used to construct multiensemble Markov State Models (MSMs). Finally, the BICePs (Bayesian Inference of Conformational Populations) algorithm is then used with our HDX protection factor predictor to infer which thermodynamic ensemble agrees best with the experiment and estimate populations of each conformational state in the MSM. To illustrate the approach, we use a combination of HDX protection factor restraints and chemical shift restraints to model the conformational ensemble of apomyoglobin at pH 6. The resulting ensemble agrees well with the experiment and gives insight into the all-atom structure of disordered helices F and H in the absence of heme.

Integrating hydrogen-deuterium exchange mass spectrometry with molecular dynamics simulations to probe lipid-modulated conformational changes in membrane proteins

Biological membranes define the boundaries of cells and are composed primarily of phospholipids and membrane proteins. It has become increasingly evident that direct interactions of membrane proteins with their surrounding lipids play key roles in regulating both protein conformations and function. However, the exact nature and structural consequences of these interactions remain difficult to track at the molecular level. Here, we present a protocol that specifically addresses this challenge. First, hydrogen-deuterium exchange mass spectrometry (HDX-MS) of membrane proteins incorporated into nanodiscs of controlled lipid composition is used to obtain information on the lipid species that are involved in modulating the conformational changes in the membrane protein. Then molecular dynamics (MD) simulations in lipid bilayers are used to pinpoint likely lipid-protein interactions, which can be tested experimentally using HDX-MS. By bringing together the MD predictions with the conformational readouts from HDX-MS, we have uncovered key lipid-protein interactions implicated in stabilizing important functional conformations. This protocol can be applied to virtually any integral membrane protein amenable to classic biophysical studies and for which a near-atomic-resolution structure or homology model is available. This protocol takes ~4 d to complete, excluding the time for data analysis and MD simulations, which depends on the size of the protein under investigation.

How internal cavities destabilize a protein

Although many proteins possess a distinct folded structure lying at a minimum in a funneled free energy landscape, thermal energy causes any protein to continuously access lowly populated excited states. The existence of excited states is an integral part of biological function. Although transitions into the excited states may lead to protein misfolding and aggregation, little structural information is currently available for them. Here, we show how NMR spectroscopy, coupled with pressure perturbation, brings these elusive species to light. As pressure acts to favor states with lower partial molar volume, NMR follows the ensuing change in the equilibrium spectroscopically, with residue-specific resolution. For T4 lysozyme L99A, relaxation dispersion NMR was used to follow the increase in population of a previously identified "invisible" folded state with pressure, as this is driven by the reduction in cavity volume by the flipping-in of a surface aromatic group. Furthermore, multiple partly disordered excited states were detected at equilibrium using pressure-dependent H/D exchange NMR spectroscopy. Here, unfolding reduced partial molar volume by the removal of empty internal cavities and packing imperfections through subglobal and global unfolding. A close correspondence was found for the distinct pressure sensitivities of various parts of the protein and the amount of internal cavity volume that was lost in each unfolding event. The free energies and populations of excited states allowed us to determine the energetic penalty of empty internal protein cavities to be 36 cal⋅Å^-3.

Protein dynamics revealed by hydrogen/deuterium exchange mass spectrometry: Correlation between experiments and simulation

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a powerful technique for studying protein dynamics, which is an important factor governing protein functions. However, the process of hydrogen/deuterium exchange (HDX) of proteins is highly complex and the underlying mechanism has not yet been fully elucidated. Meanwhile, molecular dynamics (MD) simulation is a computational technique that can be used to elucidate HDX behaviour on proteins and facilitate interpretation of HDX-MS data. This article aims to summarize the current understandings on the mechanism of HDX and its correlation with MD simulation, to discuss the recent developments in the techniques of HDX-MS and MD simulation and to extend the perspectives of these two techniques in protein dynamics study.

Characterization of H/D exchange in type 1 pili by proton-detected solid-state NMR and molecular dynamics simulations

Uropathogenic Escherichia coli invades and colonizes hosts by attaching to cells using adhesive pili on the bacterial surface. Although many biophysical techniques have been used to study the structure and mechanical properties of pili, many important details are still unknown. Here we use proton-detected solid-state NMR experiments to investigate solvent accessibility and structural dynamics. Deuterium back-exchange at labile sites of the perdeuterated, fully proton back-exchanged pili was conducted to investigate hydrogen/deuterium (H/D) exchange patterns of backbone amide protons in pre-assembled pili. We found distinct H/D exchange patterns in lateral and axial intermolecular interfaces in pili. Amide protons protected from H/D exchange in pili are mainly located in the core region of the monomeric subunit and in the lateral intermolecular interface, whereas the axial intermolecular interface and the exterior region of pili are highly exposed to H/D exchange. Additionally, we performed molecular dynamics simulations of the type 1 pilus rod and estimated the probability of H/D exchange based on hydrogen bond dynamics. The comparison of the experimental observables and simulation data provides insights into stability and mechanical properties of pili.

Investigating the Conformational Response of the Sortilin Receptor upon Binding Endogenous Peptide- and Protein Ligands by HDX-MS

Sortilin is a multifunctional neuronal receptor involved in sorting of neurotrophic factors and apoptosis signaling. So far, structural characterization of sortilin and its endogenous ligands has been limited to crystallographic studies of sortilin in complex with the neuropeptide neurotensin. Here, we use hydrogen/deuterium exchange mass spectrometry to investigate the conformational response of sortilin to binding biological ligands including the peptides neurotensin and the sortilin propeptide and the proteins progranulin and pro-nerve growth factor-β. The results show that the ligands use two binding sites inside the cavity of the β-propeller of sortilin. However, ligands have distinct differences in their conformational impact on the receptor. Interestingly, the protein ligands induce conformational stabilization in a remote membrane-proximal domain, hinting at an unknown conformational link between the ligand binding region and this membrane-proximal region of sortilin. Our findings improve our structural understanding of sortilin and how it mediates diverse ligand-dependent functions important in neurobiology.

Characterization of low-lying excited states of proteins by high-pressure NMR

Hydrostatic pressure alters the free energy of proteins by a few kJ mol^-1, with the amount depending on their partial molar volumes. Because the folded ground state of a protein contains cavities, it is always a state of large partial molar volume. Therefore pressure always destabilises the ground state and increases the population of partially and completely unfolded states. This is a mild and reversible conformational change, which allows the study of excited states under thermodynamic equilibrium conditions. Many of the excited states studied in this way are functionally relevant; they also seem to be very similar to kinetic folding intermediates, thus suggesting that evolution has made use of the 'natural' dynamic energy landscape of the protein fold and sculpted it to optimise function. This includes features such as ligand binding, structural change during the catalytic cycle, and dynamic allostery.

Interpreting Hydrogen-Deuterium Exchange Events in Proteins Using Atomistic Simulations: Case Studies on Regulators of G-Protein Signaling Proteins

Hydrogen-deuterium exchange (HDX) experiments are widely used in studies of protein dynamics. To predict the propensity of amide hydrogens for exchange with deuterium, several models have been reported in which computations of amide-hydrogen protection factors are carried out using molecular dynamics (MD) simulations. Given significant variation in the criteria used in different models, the robustness and broader applicability of these models to other proteins, especially homologous proteins showing distinct amide-exchange patterns, remains unknown. The sensitivity of the predictions when MD simulations are conducted with different force-fields is yet to tested and quantified. Using MD simulations and experimental HDX data on three homologous signaling proteins, we report detailed studies quantifying the performance of seven previously reported models (M1-M7) of two general types: empirical and fractional-population models. We find that the empirical models show inconsistent predictions but predictions of the fractional population models are robust. Contrary to previously reported work, we find that the solvent-accessible surface area of amide hydrogens is a useful metric when combined with a new metric defining the distances of amide hydrogens from the first polar atoms in proteins. On the basis of this, we report two new models, one empirical (M8) and one population-based (M9). We find strong protection of amide hydrogens from solvent exchange both within the stable helical motifs and also in the interhelical loops. We further observe that the exchange-competent states of amide hydrogens occur on the sub 100 ps time-scale via localized fluctuations, and such states among amides of a given protein do not appear to show any cooperativity or allosteric coupling.

Measurement and Characterization of Hydrogen-Deuterium Exchange Chemistry Using Relaxation Dispersion NMR Spectroscopy

One-dimensional heteronuclear relaxation dispersion NMR spectroscopy at ¹³C natural abundance successfully characterized the dynamics of the hydrogen-deuterium exchange reaction occurring at the N^ε position in l-arginine by monitoring C^δ in varying amounts of D₂O. A small equilibrium isotope effect was observed and quantified, corresponding to ΔG = -0.14 kcal mol^-1. A bimolecular rate constant of k_D = 5.1 × 10⁹ s^-1 M^-1 was determined from the pH*-dependence of k_ex (where pH* is the direct electrode reading of pH in 10% D₂O and k_ex is the nuclear spin exchange rate constant), consistent with diffusion-controlled kinetics. The measurement of ΔG serves to bridge the millisecond time scale lifetimes of the detectable positively charged arginine species with the nanosecond time scale lifetime of the nonobservable low-populated neutral arginine intermediate species, thus allowing for characterization of the equilibrium lifetimes of the various arginine species in solution as a function of fractional solvent deuterium content. Despite the system being in fast exchange on the chemical shift time scale, the magnitude of the secondary isotope shift due to the exchange reaction at N^ε was accurately measured to be 0.12 ppm directly from curve-fitting D₂O-dependent dispersion data collected at a single static field strength. These results indicate that relaxation dispersion NMR spectroscopy is a robust and general method for studying base-catalyzed hydrogen-deuterium exchange chemistry at equilibrium.

Differential Protein Dynamics of Regulators of G-Protein Signaling: Role in Specificity of Small-Molecule Inhibitors

Small-molecule inhibitor selectivity may be influenced by variation in dynamics among members of a protein family. Regulator of G-protein Signaling (RGS) proteins are a family that plays a key role in G-Protein Coupled Receptor (GPCR) signaling by binding to active Gα subunits and accelerating GTP hydrolysis, thereby terminating activity. Thiadiazolidinones (TDZDs) inhibit the RGS-Gα interaction by covalent modification of cysteine residues in RGS proteins. Some differences in specificity may be explained by differences in the complement of cysteines among RGS proteins. However, key cysteines shared by RGS proteins inhibited by TDZDs are not exposed on the protein surface, and differences in potency exist among RGS proteins containing only buried cysteines. We hypothesize that differential exposure of buried cysteine residues among RGS proteins partially drives TDZD selectivity. Hydrogen-deuterium exchange (HDX) studies and molecular dynamics (MD) simulations were used to probe the dynamics of RGS4, RGS8, and RGS19, three RGS proteins inhibited at a range of potencies by TDZDs. When these proteins were mutated to contain a single, shared cysteine, RGS19 was found to be most potently inhibited. HDX studies revealed differences in α4 and α6 helix flexibility among RGS isoforms, with particularly high flexibility in RGS19. This could cause differences in cysteine exposure and lead to differences in potency of TDZD inhibition. MD simulations of RGS proteins revealed motions that correspond to solvent exposure observed in HDX, providing further evidence for a role of protein dynamics in TDZD selectivity.

A novel Porphyromonas gingivalis enzyme: An atypical dipeptidyl peptidase III with an ARM repeat domain

Porphyromonas gingivalis, an asaccharolytic Gram-negative oral anaerobe, is a major pathogen associated with adult periodontitis, a chronic infective disease that a significant percentage of the human population suffers from. It preferentially utilizes dipeptides as its carbon source, suggesting the importance of dipeptidyl peptidase (DPP) types of enzyme for its growth. Until now DPP IV, DPP5, 7 and 11 have been extensively investigated. Here, we report the characterization of DPP III using molecular biology, biochemical, biophysical and computational chemistry methods. In addition to the expected evolutionarily conserved regions of all DPP III family members, PgDPP III possesses a C-terminal extension containing an Armadillo (ARM) type fold similar to the AlkD family of bacterial DNA glycosylases, implicating it in alkylation repair functions. However, complementation assays in a DNA repair-deficient Escherichia coli strain indicated the absence of alkylation repair function for PgDPP III. Biochemical analyses of recombinant PgDPP III revealed activity similar to that of DPP III from Bacteroides thetaiotaomicron, and in the range between activities of human and yeast counterparts. However, the catalytic efficiency of the separately expressed DPP III domain is ~1000-fold weaker. The structure and dynamics of the ligand-free enzyme and its complex with two different diarginyl arylamide substrates was investigated using small angle X-ray scattering, homology modeling, MD simulations and hydrogen/deuterium exchange (HDX). The correlation between the experimental HDX and MD data improved with simulation time, suggesting that the DPP III domain adopts a semi-closed or closed form in solution, similar to that reported for human DPP III. The obtained results reveal an atypical DPP III with increased structural complexity: its superhelical C-terminal domain contributes to peptidase activity and influences DPP III interdomain dynamics. Overall, this research reveals multifunctionality of PgDPP III and opens direction for future research of DPP III family proteins.

An overview of hydrogen deuterium exchange mass spectrometry (HDX-MS) in drug discovery

INTRODUCTION

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a powerful methodology to study protein dynamics, protein folding, protein-protein interactions, and protein small molecule interactions. The development of novel methodologies and technical advancements in mass spectrometers has greatly expanded the accessibility and acceptance of this technique within both academia and industry. Areas covered: This review examines the theoretical basis of how amide exchange occurs, how different mass spectrometer approaches can be used for HDX-MS experiments, as well as the use of HDX-MS in drug development, specifically focusing on how HDX-MS is used to characterize bio-therapeutics, and its use in examining protein-protein and protein small molecule interactions. Expert opinion: HDX-MS has been widely accepted within the pharmaceutical industry for the characterization of bio-therapeutics as well as in the mapping of antibody drug epitopes. However, there is room for this technique to be more widely used in the drug discovery process. This is particularly true in the use of HDX-MS as a complement to other high-resolution structural approaches, as well as in the development of small molecule therapeutics that can target both active-site and allosteric binding sites.

Calcium-Mediated Control of S100 Proteins: Allosteric Communication via an Agitator/Signal Blocking Mechanism

Allosteric proteins possess dynamically coupled residues for the propagation of input signals to distant target binding sites. The input signals usually correspond to "effector is present" or "effector is not present". Many aspects of allosteric regulation remain incompletely understood. This work focused on S100A11, a dimeric EF-hand protein with two hydrophobic target binding sites. An annexin peptide (Ax) served as the target. Target binding is allosterically controlled by Ca²⁺ over a distance of ∼26 Å. Ca²⁺ promotes formation of a [Ca₄ S100 Ax₂] complex, where the Ax peptides are accommodated between helices III/IV and III'/IV'. Without Ca²⁺ these binding sites are closed, precluding interactions with Ax. The allosteric mechanism was probed by microsecond MD simulations in explicit water, complemented by hydrogen exchange mass spectrometry (HDX/MS). Consistent with experimental data, MD runs in the absence of Ca²⁺ and Ax culminated in target binding site closure. In simulations on [Ca₄ S100] the target binding sites remained open. These results capture the essence of allosteric control, revealing how Ca²⁺ prevents binding site closure. Both HDX/MS and MD data showed that the metalation sites become more dynamic after Ca²⁺ loss. However, these enhanced dynamics do not represent the primary trigger of the allosteric cascade. Instead, a labile salt bridge acts as an incessantly active "agitator" that destabilizes the packing of adjacent residues, causing a domino chain of events that culminates in target binding site closure. This agitator represents the starting point of the allosteric signal propagation pathway. Ca²⁺ binding rigidifies elements along this pathway, thereby blocking signal transmission. This blocking mechanism does not conform to the commonly held view that allosteric communication pathways generally originate at the sites where effectors interact with the protein.

Conformational characterization of nerve growth factor-β reveals that its regulatory pro-part domain stabilizes three loop regions in its mature part

Nerve growth factor-β (NGF) is essential for the correct development of the nervous system. NGF exists in both a mature form and a pro-form (proNGF). The two forms have opposing effects on neurons: NGF induces proliferation, whereas proNGF induces apoptosis via binding to a receptor complex of the common neurotrophin receptor (p75NTR) and sortilin. The overexpression of both proNGF and sortilin has been associated with several neurodegenerative diseases. Insights into the conformational differences between proNGF and NGF are central to a better understanding of the opposing mechanisms of action of NGF and proNGF on neurons. However, whereas the structure of NGF has been determined by X-ray crystallography, the structural details for proNGF remain elusive. Here, using a sensitive MS-based analytical method to measure the hydrogen/deuterium exchange of proteins in solution, we analyzed the conformational properties of proNGF and NGF. We detected the presence of a localized higher-order structure motif in the pro-part of proNGF. Furthermore, by comparing the hydrogen/deuterium exchange in the mature part of NGF and proNGF, we found that the presence of the pro-part in proNGF causes a structural stabilization of three loop regions in the mature part, possibly through a direct molecular interaction. Moreover, using tandem MS analyses, we identified two N-linked and two O-linked glycosylations in the pro-part of proNGF. These results advance our knowledge of the conformational properties of proNGF and NGF and help provide a rationale for the diverse biological effects of NGF and proNGF at the molecular level.