Hydrogen-deuterium Exchange Data Research Articles

Integration of Hydrogen-Deuterium Exchange Mass Spectrometry with Molecular Dynamics Simulations and Ensemble Reweighting Enables High Resolution Protein-Ligand Modeling.

Hydrogen-Deuterium exchange mass spectrometry's (HDX-MS) utility in identifying and characterizing protein-small molecule interaction sites has been established. The regions that are seen to be protected from exchange upon ligand binding indicate regions that may be interacting with the ligand, giving a qualitative understanding of the ligand binding pocket. However, quantitatively deriving an accurate high-resolution structure of the protein-ligand complex from the HDX-MS data remains a challenge, often limiting its use in applications such as small molecule drug design. Recent efforts have focused on the development of methods to quantitatively model Hydrogen-Deuterium exchange (HDX) data from computationally modeled structures to garner atomic level insights from peptide-level resolution HDX-MS. One such method, HDX ensemble reweighting (HDXer), employs maximum entropy reweighting of simulated HDX data to experimental HDX-MS to model structural ensembles. In this study, we implement and validate a workflow which quantitatively leverages HDX-MS data to accurately model protein-small molecule ligand interactions. To that end, we employ a strategy combining computational protein-ligand docking, molecular dynamics simulations, HDXer, and dimensional reduction and clustering approaches to extract high-resolution drug binding poses that most accurately conform with HDX-MS data. We apply this workflow to model the interaction of ERK2 and FosA with small molecule compounds and inhibitors they are known to bind. In five out of six of the protein-ligand pairs tested, the HDX derived protein-ligand complexes result in a ligand root-mean-square deviation (RMSD) within 2.5 Å of the known crystal structure ligand.

Top-Down Structural Characterization of Native Ubiquitin Combining Solution-Stable Isotope Labeling, Trapped Ion Mobility Spectrometry, and Tandem Electron Capture Dissociation Mass Spectrometry.

Solution-phase hydrogen/deuterium exchange (HDX) coupled to native ion mobility spectrometry mass spectrometry (IMS-MS) can provide complementary structural information about the conformational dynamics of biological molecules. In the present work, the solution-stable isotope labeling (SIL) combined with trapped ion mobility spectrometry (TIMS) in tandem with top-down electron capture dissociation (ECD) is illustrated for the structural characterization of the solution native states of ubiquitin. Four different ubiquitin electrospray solution conditions: (i) single-tip nondeuterated, (ii) theta tip for online SIL HDX, (iii) single-tip SIL-deuterated, and (iv) theta tip for online SIL H/D back exchange (HDbX), were investigated to assess the H/D exchange reactivities of native ubiquitin. The combination of TIMS and ECD in a q-ToF MS instrument allowed for additional inspection of gas-phase HDbX added by top-down fragmentation, revealing the exposed and protected residues with limited scrambling effects (e.g., intramolecular H/D migration). A native charge state distribution (5+ to 7+) and TIMS profiles were observed under the single-tip nondeuterated solution conditions. Mass shift distributions of ∼40, ∼104, and ∼87D were observed when incorporating deuterium for online SIL HDX, SIL HDX, and online SIL HDbX, respectively, while retaining similar conformational states. ECD fragmentation allowed for the localization of the deuterated labeled residues of the peptide fragments, with a sequence coverage of ∼90%, for each of the ubiquitin solution condition. Changes in the TIMS trapping time settings (∼70 to ∼795 ms) were used to determine the H/D back exchange dynamics of native ubiquitin. HDbX-TIMS-q-ECD-MS/MS exhibited H/D back exchanges in the six-residue C-terminal tail as well as around Lys6, Lys11, Lys33, Lys48, and Lys63 residues, indicating that these regions are the most exposed area (less protected hydrogens) of ubiquitin as compared to the rest of the core residues that adopt a compact β-grasp fold (protected hydrogens), which was consistent with the accessible surface area of ubiquitin. The present data highlight for the first time consistency between the solution HDX and gas-phase HDbX-TIMS data for native studies.

TRAMP assembly alters the conformation and RNA binding of Mtr4 and Trf4-Air2.

The TRAMP complex contains two enzymatic activities essential for RNA processing upstream of the nuclear exosome. Within TRAMP, RNA is 3' polyadenylated by a sub-complex of Trf4/5 and Air1/2 and unwound 3' to 5' by Mtr4, a DExH helicase. The molecular mechanisms of TRAMP assembly and RNA shuffling between the two TRAMP catalytic sites are poorly understood. Here, we report solution hydrogen-deuterium exchange data with thermodynamic and functional assays to uncover these mechanisms for yeast TRAMP with Trf4 and Air2 homologs. We show that TRAMP assembly constrains RNA-recognition motifs that are peripheral to catalytic sites. These include the Mtr4 Arch and Air2 zinc knuckles 1, 2, and 3. While the Air2 Arch-interacting motif likely constrains the Mtr4 Arch via transient interactions, these do not fully account for the importance of the Mtr4 Arch in TRAMP assembly. We further show that tRNA binding by single active-site subunits, Mtr4 and Trf4-Air2, differs from the double active-site TRAMP. TRAMP has reduced tRNA binding on the Mtr4 Fist and RecA2 domains, offset by increased tRNA binding on Air2 zinc knuckles 2 and 3. Competition between these RNA-binding sites may drive tRNA transfer between TRAMP subunits. We identify dynamic changes upon TRAMP assembly and RNA-recognition motifs that transfer RNA between TRAMP catalytic sites.

Structural Dynamics of a Thermally Stressed Monoclonal Antibody Characterized by Temperature-Dependent H/D Exchange Mass Spectrometry.

Differential scanning calorimetry (DSC) is a standard tool for probing the resilience of monoclonal antibodies (mAbs) and other protein therapeutics against thermal degradation. Unfortunately, DSC usually only provides insights into global unfolding, although sequential steps are sometimes discernible for multidomain proteins. Temperature-dependent hydrogen/deuterium exchange (HDX) mass spectrometry (MS) has the potential to probe heat-induced events at a much greater level of detail. We recently proposed a strategy to deconvolute temperature-dependent HDX data into contributions from local dynamics, global unfolding/refolding, as well as chemical labeling. However, that strategy was validated only for a small protein (Tajoddin, N. N.; Konermann, L. Anal. Chem. 2020, 92, 10058). The current work explores the applicability of this HDX framework to the NIST reference mAb (NISTmAb), a large multidomain protein that is prone to aggregation and has three melting points. Using global fitting, we were able to model HDX profiles across the NISTmAb sequence between zero and 95 °C, and for time points between 15 s and 20 min. We uncovered the enthalpic and entropic contributions of local fluctuations that govern the conformational dynamics at low temperatures. The CH2 and CH3 domains were found to be increasingly affected by global unfolding/refolding in the vicinity of their melting points, although the transiently unfolded protein displayed significant residual protection. Global dynamics were not involved in the deuteration of the Fab domains (which have the highest melting point). Instead, global Fab unfolding was followed immediately by irreversible aggregation. Our results reveal that the thermodynamic HDX-MS strategy applied in this work is well suited for probing spatially resolved dynamics of thermally stressed large proteins such as mAbs, complementing data obtained by DSC.

Efficient Hydrogen-Deuterium Exchange in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging for Confident Metabolite Identification.

Highly efficient hydrogen-deuterium exchange (HDX) is developed for mass spectrometry imaging (MSI) with low-vacuum matrix-assisted laser desorption/ionization (MALDI). A HDX efficiency of 73-85% is achieved by introducing D2O vapor into a heated MALDI source in combination with a deuterium-labeled matrix, which allows correct determination of the number of possible H/D exchanges for up to 17 labile hydrogens. This provides valuable orthogonal information to supplement m/z, allowing for increased confidence in metabolite identification while retaining the spatial information MSI supplies. When combined with high-throughput METASPACE annotation, this approach can systematically improve untargeted metabolite annotations in MALDI-MS imaging. The developed method was applied to MALDI-MS imaging of the top surface, bottom surface, and middle section of Lemna minor fronds. Out of a total of 56 on-sample annotations made with the BraChem database using a 10% false discovery rate, 31 of these annotations (55%) matched our HDX data, providing additional confidence. For the remaining 45%, our data allowed us to narrow down structural possibilities and eliminate incorrect structures, greatly increasing confidence in metabolite identification.

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.

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.

Protein structure prediction using residue-resolved protection factors from hydrogen-deuterium exchange NMR

Hydrogen-deuterium exchange (HDX) measured by nuclear magnetic resonance (NMR) provides structural information for proteins relating to solvent accessibility and flexibility. While this structural information is beneficial, the data cannot be used exclusively to elucidate structures. However, the structural information provided by the HDX-NMR data can be supplemented by computational methods. In previous work, we developed an algorithm in Rosetta to predict structures using qualitative HDX-NMR data (categories of exchange rate). Here we expand on the effort, and utilize quantitative protection factors (PFs) from HDX-NMR for structure prediction. From observed correlations between PFs and solvent accessibility/flexibility measures, we present a scoring function to quantify the agreement with HDX data. Using a benchmark set of 10 proteins, an average improvement of 5.13Å in root-mean-square deviation (RMSD) is observed for cases of inaccurate Rosetta predictions. Ultimately, seven out of 10 predictions are accurate without including HDX data, and nine out of 10 are accurate when using our PF-based HDX score.

Protein Structure Prediction from NMR Hydrogen-Deuterium Exchange Data.

Amide hydrogen-deuterium exchange (HDX) has long been used to determine regional flexibility and binding sites in proteins; however, the data are too sparse for full structural characterization. Experiments that measure HDX rates, such as HDX-NMR, have far higher throughput compared to structure determination via X-ray crystallography, cryo-EM, or a full suite of NMR experiments. Data from HDX-NMR experiments encode information on the protein structure, making HDX a prime candidate to be supplemented by computational algorithms for protein structure prediction. We have developed a methodology to incorporate HDX-NMR data into ab initio protein structure prediction using the Rosetta software framework to predict structures based on experimental agreement. To demonstrate the efficacy of our algorithm, we examined 38 proteins with HDX-NMR data available, comparing the predicted model with and without the incorporation of HDX data into scoring. The root-mean-square deviation (rmsd, a measure of the average atomic distance between superimposed models) of the predicted model improved by 1.42 Å on average after incorporating the HDX-NMR data into scoring. The average rmsd improvement for the proteins where the selected model rmsd changed after incorporating HDX data was 3.63 Å, including one improvement of more than 11 Å and seven proteins improving by greater than 4 Å, with 12/15 proteins improving overall. Additionally, for independent verification, two proteins that were not part of the original benchmark were scored including HDX data, with a dramatic improvement of the selected model rmsd of nearly 9 Å for one of the proteins. Moreover, we have developed a confidence metric allowing us to successfully identify near-native models in the absence of a native structure. Improvement in model selection with a strong confidence measure demonstrates that protein structure prediction with HDX-NMR is a powerful tool which can be performed with minimal additional computational strain and expense.

Dried Protein Structure Revealed at the Residue Level by Liquid-Observed Vapor Exchange NMR.

Water is key to protein structure and stability, yet the relationship between protein-water interactions and structure is poorly understood, in part because there are few techniques that permit the study of dehydrated protein structure at high resolution. Here, we describe liquid-observed vapor exchange (LOVE) NMR, a solution NMR-based method that provides residue-level information about the structure of dehydrated proteins. Using the model protein GB1, we show that LOVE NMR measurements reflect the fraction of the dried protein population trapped in a conformation where a given residue is protected from exchange with D2O vapor. Comparisons to solution hydrogen-deuterium exchange data affirm that the dried protein structure is strongly influenced by local solution stability and that the mechanism of dehydration protection exerted by the widely used protectant trehalose differs from its mechanism of stabilization in solution. Our results highlight the need for refined models of cosolute-mediated dehydration protection and demonstrate the ability of LOVE NMR to inform such models.

HD-eXplosion: visualization of hydrogen-deuterium exchange data as chiclet and volcano plots with statistical filtering.

Hydrogen-Deuterium eXchange coupled to mass spectrometry is a powerful tool for the analysis of protein dynamics and interactions. Bottom-up experiments looking at deuterium uptake differences between various conditions are the most common. These produce multi-dimensional data that can be challenging to depict in a single visual format. Each user must also set significance thresholds to define meaningful differences and make these apparent in data presentation. To assist in this process, we have created HD-eXplosion, an open-source, web-based application for the generation of chiclet and volcano plots with statistical filters. HD-eXplosion fills a void in available software packages and produces customizable plots that are publication quality. The HD-eXplosion application is available at http://hd-explosion.utdallas.edu. The source code can be found at https://github.com/HD-Explosion.

Laser Ablation Electrospray Ionization Hydrogen/Deuterium Exchange Ambient Mass Spectrometry Imaging.

Identification and confirmation of known as well as unknown (bio)chemical entities in ambient mass spectrometry (MS) and MS imaging (MSI) mostly involve accurate mass determination, often in combination with MS/MS or MSn work flows. To further improve structural assignment, additional molecular information is required. Here we present an ambient hydrogen/deuterium exchange (HDX) laser ablation electrospray ionization (LAESI) MS method in which, apart from the accurate mass and MS/MS data, the number of exchangeable protons in (un)known molecules is obtained. While eventually presenting ambient HDX-LAESI-MSI, samples were not preincubated with deuterated solvents, but instead HDX occurred following fusion of ablated sample material with microdroplets generated by ESI of deuterated solvents. Therefore, the degree of HDX was first studied following ablation of nondeuterated sample solutions of melamine and monosaccharides. From these experiments, it was concluded that the set-up used could provide meaningful HDX data in support of molecular structure elucidation by significantly reducing the number of structure options from a measured elemental composition. This reduction was demonstrated with an unknown accurate m/z value obtained in the analysis of an orange slice, reducing the possible number of molecular structures having the same elemental composition by 87% due to the number of H/D exchanges observed. Next, deuterated and nondeuterated MS/MS experiments showed the number of exchangeable protons in the substructures from deuterated neutral losses in the product ion spectra, confirming the compound to be arginine. Finally, the potential of ambient HDX-LAESI-MSI was demonstrated by the imaging of (secondary) plant metabolites in a Phalaenopsis petal.

FACT caught in the act of manipulating the nucleosome.

The organization of genomic DNA into nucleosomes profoundly affects all DNA-related processes in eukaryotes. The histone chaperone ‘FAcilitates Chromatin Transcription’ (FACT, consisting of subunits SPT16 and SSRP11) promotes both disassembly and reassembly of nucleosomes during gene transcription, DNA replication, and repair2. The mechanism by which FACT causes these opposing outcomes is unknown. Here we report two cryo-EM structures of human FACT in complex with partially assembled ‘sub-nucleosomes’, with supporting biochemical and hydrogen-deuterium exchange (HDX) data. FACT is engaged in extensive interactions with nucleosomal DNA and all histones. The large DNA-binding surface on FACT appears to be protected by the C-terminal domains of both subunits, and this inhibition is released by interaction with H2A-H2B, allowing FACT-H2A-H2B to dock onto a (H3-H4)2-DNA complex3. SPT16 binds nucleosomal DNA and tethers H2A-H2B through its C-terminal domain by acting as a placeholder for DNA. SSRP1 also contributes to DNA binding, and can assume two conformations, depending on whether a second H2A-H2B dimer is present. Our data suggest a compelling mechanism for how FACT maintains chromatin integrity during polymerase passage, by facilitating H2A-H2B dimer removal, stabilizing intermediate ‘subnucleosomal’ states, and promoting nucleosome reassembly. Our findings reconcile discrepancies regarding the many roles of FACT and underscore the dynamic interactions between histone chaperones and nucleosomes.

Structure, Function, and Dynamics of the Gα Binding Domain of Ric-8A

Ric-8A is a 530-amino acid cytoplasmic molecular chaperone and guanine nucleotide exchange factor (GEF) for i, q, and 12/13 classes of heterortrimeric G protein alpha subunits (Gα). We report the 2.2-Å crystal structure of the Ric-8A Gα-binding domain with GEF activity, residues 1-452, and is phosphorylated at Ser435 and Thr440. Residues 1-429 adopt a superhelical fold comprised of Armadillo (ARM) and HEAT repeats, and the C terminus is disordered. One of the phosphorylated residues potentially binds to a basic cluster in an ARM motif. Amino acid sequence conservation and published hydrogen-deuterium exchange data indicate repeats 3 through 6 to be a putative Gα-binding surface. Normal mode modeling of small-angle X-ray scattering data indicates that phosphorylation induces relative rotation between repeats 1-4, 5-6, and 7-9. 2D 1H-15N-TROSY spectra of [2H,15N]-labeled Gαi1 in the presence of R452 reveals chemical shift perturbations of the C terminus and Gαi1 residues involved in nucleotide binding.

Conformational ensemble of native α-synuclein in solution as determined by short-distance crosslinking constraint-guided discrete molecular dynamics simulations.

Combining structural proteomics experimental data with computational methods is a powerful tool for protein structure prediction. Here, we apply a recently-developed approach for de novo protein structure determination based on the incorporation of short-distance crosslinking data as constraints in discrete molecular dynamics simulations (CL-DMD) for the determination of conformational ensemble of the intrinsically disordered protein α-synuclein in the solution. The predicted structures were in agreement with hydrogen-deuterium exchange, circular dichroism, surface modification, and long-distance crosslinking data. We found that α-synuclein is present in solution as an ensemble of rather compact globular conformations with distinct topology and inter-residue contacts, which is well-represented by movements of the large loops and formation of few transient secondary structure elements. Non-amyloid component and C-terminal regions were consistently found to contain β-structure elements and hairpins.

Current Trends in Biotherapeutic Higher Order Structure Characterization by Irreversible Covalent Footprinting Mass Spectrometry.

Biotherapeutics, particularly monoclonal antibodies (mAbs), are a maturing class of drugs capable of treating a wide range of diseases. Therapeutic function and solutionstability are linked to the proper three-dimensional organization of the primary sequence into Higher Order Structure (HOS) as well as the timescales of protein motions (dynamics). Methods that directly monitor protein HOS and dynamics are important for mapping therapeutically relevant protein-protein interactions and assessing properly folded structures. Irreversible covalent protein footprinting Mass Spectrometry (MS) tools, such as site-specific amino acid labeling and hydroxyl radical footprinting are analytical techniques capable of monitoring the side chain solvent accessibility influenced by tertiary and quaternary structure. Here we discuss the methodology, examples of biotherapeutic applications, and the future directions of irreversible covalent protein footprinting MS in biotherapeutic research and development. Bottom-up mass spectrometry using irreversible labeling techniques provide valuable information for characterizing solution-phase protein structure. Examples range from epitope mapping and protein-ligand interactions, to probing challenging structures of membrane proteins. By paring these techniques with hydrogen-deuterium exchange, spectroscopic analysis, or static-phase structural data such as crystallography or electron microscopy, a comprehensive understanding of protein structure can be obtained.

NMR Investigation of the Interaction between the RecQ C-Terminal Domain of Human Bloom Syndrome Protein and G-Quadruplex DNA from the Human c-Myc Promoter

Bloom syndrome protein (BLM) is one of five human RecQ helicases that participate in DNA metabolism. RecQ C-terminal (RQC) domain is the main DNA binding module of BLM and specifically recognizes G-quadruplex (G4) DNA structures. Because G4 processing by BLM is essential for regulating replication and transcription, both G4 and BLM are considered as potential targets for anticancer therapy. Although several studies have revealed the detailed mechanism of G4 unwinding by BLM, the initial recognition of the G4 structure by the RQC domain is unclear. Here, we investigated the interaction between BLM RQC and the G4 DNA from the c-Myc promoter by NMR spectroscopy. While the signals broadened upon reciprocal titrations, the β-wing of RQC had significant chemical shift perturbations and experienced millisecond timescale dynamics upon G4 binding. A point mutation in the β-wing (N1164A) reduced G4 binding affinity. Our hydrogen–deuterium exchange data indicate that imino protons of G4 were exchanged with deuterium much faster in the presence of RQC. We suggest that RQC binds to G4 by using the β-wing as a separating pin to destabilize the G4. By providing information about the RQC–G4 interaction, our study yields insight into potential strategies for preventing G4 processing by BLM.

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.

Reconciling Simulated Ensembles of Apomyoglobin with Experimental HDX Data

Hydrogen/deuterium exchange (HDX) is a powerful tool to investigate protein conformational dynamics at equilibrium. In the classic model of HDX, each of the amide hydrogens of a protein can either exist in an “open” conformation, where HDX can occur with the exchange rate kint, or in a “closed” conformation, where HDX rate, kex, gets much slower. The extent of protection for a residue i, is characterized by a protection factor, PFi = kex,i/kint,i, which is related to the effective free energy difference between open and closed states, ΔG, through ln(PFi ) = βΔGi. However, it has been challenging to make direct connections between molecular simulations of native-state protein dynamics, both in predicting HDX PF from trajectory data, and in using experimental protection factors as restraints in simulated ensembles. In this study, we propose an expression, ln(PF)= βc<Nc> + βh<Nh> + β0, to predict the protection factors based on the average number of heavy-atom contacts <Nc> and hydrogen bonds <Nh> observed in simulations. The model parameters are trained on ultra-long, all-atom trajectories of proteins with experimentally measured protection factors (BPTI and ubiquitin). Using Bayesian inference to propagate the uncertainties in model parameters, we then use this model to refine conformational ensembles of apomyoglobin at neutral pH. To minimize bias, we simulated apomyoglobin using a range of weak to strong amide exposure restraints. We applied a transition-based reweighting method, TRAM, to construct a Multi-ensemble Markov model from the combined simulation data, and then used our Bayesian Inference of Conformational Populations (BICePs) algorithm to refine a conformational ensemble that best matched the experimental structural data. The resulting ensemble shows a partially-disordered F/H helix, and atomically detailed information that was previously missing from 2D NMR studies.

A Dynamical Model for Insulin Degrading Enzyme Conformational Transition between Closed and Open States

Insulin Degrading Enzyme (IDE) is involved in the deconstruction of insulin, amylin, and glucagon peptides involved in controlling blood glucose level and has also been found to break down amyloid-β, a peptide involved in Alzheimer's disease. IDE has two homologous N- and C-terminal domains, IDE-N and IDE-C. For IDE to degrade its substrates, both domains must come together for the catalytic cleft to assume closed conformation. New Cryo-Electron Microscopy (Cryo-EM) data suggests IDE passes through five conformations: completely closed with substrate bound, partially closed with substrate bound, partially open with substrate unbound, and open without substrate. Dynamical details of how these conformations connect are unknown. We investigated this process using long all atom molecular dynamics simulations (MD) of IDE monomer and dimer structures with and without substrate. Our simulations showed that IDE without insulin (pdb-code 4IOF) has larger relative motion between four subdomains (D1, D2, D3, D4) in the N- and C-terminal domains compared to an IDE with insulin (pdb-code 2WBY). Analysis of the insulin inside the catalytic chamber suggested that insulin was stabilized by interactions of its residues Gly1, Tyr14, Glu17 form its chain A and Phe1 and Ph25 from its chain B with IDE residues via a combination of hydrogen bonding and π - π interactions. We used, Essential Dynamics Analysis (EDA) to calculate principal normal modes of IDE motion from our trajectories. These normal modes were then applied as coordinate transformations combined with short MD simulations to gradually open the IDE-closed conformation. We used cross-comparison with Cryo-EM and hydrogen-deuterium exchange data of IDE as a guide to obtain a realistic model of how IDE changes between closed and open conformations.