Conformational Landscape Of Proteins Research Articles

Exploring Protein Conformational Landscapes Using High-Pressure NMR.

Protein conformational landscapes define their functional properties as well as their proteostasis. Hence, detailed mapping of these landscapes is necessary to understand and modulate protein conformation. The combination of high pressure and NMR provides a particularly powerful approach to characterizing protein conformational transitions. First, pressure, because its effects on protein structure arise from elimination of solvent excluded void volume, represents a more subtle perturbation than chemical denaturants, favoring the population of intermediates. Second, the residue-specific and multifaceted nature of NMR observables informs on many local structural properties of proteins, aiding in the characterization of intermediate and excited states.

Lessons from pressure denaturation of proteins.

Although it is now relatively well understood how sequence defines and impacts global protein stability in specific structural contexts, the question of how sequence modulates the configurational landscape of proteins remains to be defined. Protein configurational equilibria are generally characterized by using various chemical denaturants or by changing temperature or pH. Another thermodynamic parameter which is less often used in such studies is high hydrostatic pressure. This review discusses the basis for pressure effects on protein structure and stability, and describes how the unique mechanisms of pressure-induced unfolding can provide unique insights into protein conformational landscapes.

Assessment and optimization of collective variables for protein conformational landscape: GB1 β-hairpin as a case study.

Collective variables (CVs), when chosen judiciously, can play an important role in recognizing rate-limiting processes and rare events in any biomolecular systems. However, high dimensionality and inherent complexities associated with such biochemical systems render the identification of an optimal CV a challenging task, which in turn precludes the elucidation of an underlying conformational landscape in sufficient details. In this context, a relevant model system is presented by a 16-residue β-hairpin of GB1 protein. Despite being the target of numerous theoretical and computational studies for understanding the protein folding, the set of CVs optimally characterizing the conformational landscape of the β-hairpin of GB1 protein has remained elusive, resulting in a lack of consensus on its folding mechanism. Here we address this by proposing a pair of optimal CVs which can resolve the underlying free energy landscape of the GB1 hairpin quite efficiently. Expressed as a linear combination of a number of traditional CVs, the optimal CV for this system is derived by employing the recently introduced time-structured independent component analysis approach on a large number of independent unbiased simulations. By projecting the replica-exchange simulated trajectories along these pair of optimized CVs, the resulting free energy landscape of this system is able to resolve four distinct well-separated metastable states encompassing the extensive ensembles of folded, unfolded, and molten globule states. Importantly, the optimized CVs were found to be capable of automatically recovering a novel partial helical state of this protein, without needing to explicitly invoke helicity as a constituent CV. Furthermore, a quantitative sensitivity analysis of each constituent in the optimized CV provided key insights on the relative contributions of the constituent CVs in the overall free energy landscapes. Finally, the kinetic pathways connecting these metastable states, constructed using a Markov state model, provide an optimum description of the underlying folding mechanism of the peptide. Taken together, this work offers a quantitatively robust approach toward comprehensive mapping of the underlying folding landscape of a quintessential model system along its optimized CV.

Reinforcement Learning Based Adaptive Sampling: REAPing Rewards by Exploring Protein Conformational Landscapes.

One of the key limitations of Molecular Dynamics (MD) simulations is the computational intractability of sampling protein conformational landscapes associated with either large system size or long time scales. To overcome this bottleneck, we present the REinforcement learning based Adaptive samPling (REAP) algorithm that aims to efficiently sample conformational space by learning the relative importance of each order parameter as it samples the landscape. To achieve this, the algorithm uses concepts from the field of reinforcement learning, a subset of machine learning, which rewards sampling along important degrees of freedom and disregards others that do not facilitate exploration or exploitation. We demonstrate the effectiveness of REAP by comparing the sampling to long continuous MD simulations and least-counts adaptive sampling on two model landscapes (L-shaped and circular) and realistic systems such as alanine dipeptide and Src kinase. In all four systems, the REAP algorithm consistently demonstrates its ability to explore conformational space faster than the other two methods when comparing the expected values of the landscape discovered for a given amount of time. The key advantage of REAP is on-the-fly estimation of the importance of collective variables, which makes it particularly useful for systems with limited structural information.

Identifying the Optimal Level of Regularization in Deer Data Analysis

Double Electron-Electron Resonance (DEER) spectroscopy is an Electron Paramagnetic Resonance (EPR) experiment that accurately reports the distribution of distances, P(r), between two or more unpaired electrons over the range of about 10 to 160 ångströms. DEER is becoming increasingly important as a tool for structural biology due to its ability to elucidate protein conformational landscapes, as well as its amenability to complex samples such as membrane-bound proteins and large protein complexes. The spin-spin distance distribution, P(r), is most often inferred from the time-domain experimental data with a regularized least-squares method known as Tikhonov regularization. Although this method typically provides reliable estimates of P(r), it requires the input of a regularization parameter, α, which scales the magnitude of a penalty term with respect to the fitting error. This regularization parameter significantly affects the estimated P(r), so selecting its optimal value is crucial for accurate analysis of DEER data. The most popular procedure for selecting α in DEER data analysis is a graphical method called the L-curve criterion, which has empirical justification. However, to date, a systematic exploration of the many extant regularization parameter selection methods has not been carried out in the context of DEER data analysis. Here, we evaluate 16 methods, including the L-curve criterion, against a large, physically-derived test set of simulated DEER data. The test set of P(r)s was generated using a side-chain rotamer library in conjunction with a crystal structure (2LZM). This test set was then used to generate a large set of experimentally realistic simulated time-domain data.

Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis.

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.

Detecting intermediate protein conformations using algebraic topology

BackgroundUnderstanding protein structure and dynamics is essential for understanding their function. This is a challenging task due to the high complexity of the conformational landscapes of proteins and their rugged energy levels. In particular, it is important to detect highly populated regions which could correspond to intermediate structures or local minima.ResultsWe present a hierarchical clustering and algebraic topology based method that detects regions of interest in protein conformational space. The method is based on several techniques. We use coarse grained protein conformational search, efficient robust dimensionality reduction and topological analysis via persistent homology as the main tools. We use two dimensionality reduction methods as well, robust Principal Component Analysis (PCA) and Isomap, to generate a reduced representation of the data while preserving most of the variance in the data.ConclusionsOur hierarchical clustering method was able to produce compact, well separated clusters for all the tested examples.

Subzero Celsius separations in three-zone temperature controlled hydrogen deuterium exchange mass spectrometry

Hydrogen deuterium exchange mass spectrometry (HDX MS) reports on the conformational landscape of proteins by monitoring the exchange between backbone amide hydrogen atoms and deuterium in the solvent. To maintain the label for analysis, quench conditions of low temperature and pH are required during the chromatography step performed after protease digestion but before mass spectrometry. Separation at 0°C is often chosen as this is the temperature where the most deuterium can be recovered without freezing of the typical water and acetonitrile mobile phases. Several recent reports of separations at subzero Celsius emphasize the promise for retaining more deuterium and using a much longer chromatographic gradient or direct infusion time. Here we present the construction and validation of a modified Waters nanoACQUITY HDX manager with a third temperature-controlled zone for peptide separations at subzero temperatures. A new Peltier-cooled door replaces the door of a traditional main cooling chamber and the separations and trapping column are routed through the door housing. To prevent freezing, 35% methanol is introduced post online digestion. No new pumps are required and online digestion is performed as in the past. Subzero separations, using conventional HPLC column geometry of 3μ m particles in a 1×50mm column, did not result in major changes to chromatographic efficiency when lowering the temperature from 0 to −20°C. There were significant increases in deuterium recovery for both model peptides and biologically relevant protein systems. Given the higher levels of deuterium recovery, expanded gradient programs can be used to allow for higher chromatographic peak capacity and therefore the analysis of larger and more complex proteins and systems.

Lid opening and conformational stability of T1 Lipase is mediated by increasing chain length polar solvents.

The dynamics and conformational landscape of proteins in organic solvents are events of potential interest in nonaqueous process catalysis. Conformational changes, folding transitions, and stability often correspond to structural rearrangements that alter contacts between solvent molecules and amino acid residues. However, in nonaqueous enzymology, organic solvents limit stability and further application of proteins. In the present study, molecular dynamics (MD) of a thermostable Geobacillus zalihae T1 lipase was performed in different chain length polar organic solvents (methanol, ethanol, propanol, butanol, and pentanol) and water mixture systems to a concentration of 50%. On the basis of the MD results, the structural deviations of the backbone atoms elucidated the dynamic effects of water/organic solvent mixtures on the equilibrium state of the protein simulations in decreasing solvent polarity. The results show that the solvent mixture gives rise to deviations in enzyme structure from the native one simulated in water. The drop in the flexibility in H2O, MtOH, EtOH and PrOH simulation mixtures shows that greater motions of residues were influenced in BtOH and PtOH simulation mixtures. Comparing the root mean square fluctuations value with the accessible solvent area (SASA) for every residue showed an almost correspondingly high SASA value of residues to high flexibility and low SASA value to low flexibility. The study further revealed that the organic solvents influenced the formation of more hydrogen bonds in MtOH, EtOH and PrOH and thus, it is assumed that increased intraprotein hydrogen bonding is ultimately correlated to the stability of the protein. However, the solvent accessibility analysis showed that in all solvent systems, hydrophobic residues were exposed and polar residues tended to be buried away from the solvent. Distance variation of the tetrahedral intermediate packing of the active pocket was not conserved in organic solvent systems, which could lead to weaknesses in the catalytic H-bond network and most likely a drop in catalytic activity. The conformational variation of the lid domain caused by the solvent molecules influenced its gradual opening. Formation of additional hydrogen bonds and hydrophobic interactions indicates that the contribution of the cooperative network of interactions could retain the stability of the protein in some solvent systems. Time-correlated atomic motions were used to characterize the correlations between the motions of the atoms from atomic coordinates. The resulting cross-correlation map revealed that the organic solvent mixtures performed functional, concerted, correlated motions in regions of residues of the lid domain to other residues. These observations suggest that varying lengths of polar organic solvents play a significant role in introducing dynamic conformational diversity in proteins in a decreasing order of polarity.

Exploiting computationally derived out-of-the-box protein conformations for drug design.

Structural plasticity is an intrinsic property of proteins that allows each gene product to accomplish its tasks in a strictly regulated manner at a precise time and cellular location. Moreover, protein motions allow protein-ligand and protein-protein recognition. The knowledge of the conformational ensemble that a drug target populates may be crucial for the design of small molecules that can differently modulate its function. X-ray crystallography and NMR have endlessly provided snapshots of protein states. However, experimental structure determination is not always straightforward. Therefore, attempts have been made to depict protein conformational landscapes through molecular dynamics and enhanced sampling methods. Here, we review how accounting for protein dynamics through in silico generated out-of-the-box protein conformations has started to impact on drug discovery.

A perspective on conformational control of electron transfer in nitric oxide synthases

This perspective reviews single molecule and ensemble fluorescence spectroscopy studies of the three tissue specific nitric oxide synthase (NOS) isoenzymes and the related diflavin oxidoreductase cytochrome P450 reductase. The focus is on the role of protein dynamics and the protein conformational landscape and we discuss how recent fluorescence-based studies have helped in illustrating how the nature of the NOS conformational landscape relates to enzyme turnover and catalysis.

Conformational Mobility in Cytochrome P450 3A4 Explored by Pressure-Perturbation EPR Spectroscopy

We used high hydrostatic pressure as a tool for exploring the conformational landscape of human cytochrome P450 3A4 (CYP3A4) by electron paramagnetic resonance and fluorescence spectroscopy. Site-directed incorporation of a luminescence resonance energy transfer donor-acceptor pair allowed us to identify a pressure-dependent equilibrium between two states of the enzyme, where an increase in pressure increased the spatial separation between the two distantly located fluorophores. This transition is characterized by volume change (ΔV°) and P1/2 values of −36.8 ± 5.0 mL/mol and 1.45 ± 0.33 kbar, respectively, which corresponds to a Keq° of 0.13 ± 0.06, so that only 15% of the enzyme adopts the pressure-promoted conformation at ambient pressure. This pressure-promoted displacement of the equilibrium is eliminated by the addition of testosterone, an allosteric activator. Using site-directed spin labeling, we demonstrated that the pressure- and testosterone-sensitive transition is also revealed by pressure-induced changes in the electron paramagnetic resonance spectra of a nitroxide side chain placed at position 85 or 409 of the enzyme. Furthermore, we observed a pressure-induced displacement of the emission maxima of a solvatochromic fluorophore (7-diethylamino-3-((((2-maleimidyl)ethyl)amino)carbonyl) coumarin) placed at the same positions, which suggests a relocation to a more polar environment. Taken together, the results reveal an effector-dependent conformational equilibrium between open and closed states of CYP3A4 that involves a pronounced change at the interface between the region of α-helices A/A′ and the meander loop of the enzyme, where residues 85 and 409 are located. Our study demonstrates the high potential of pressure-perturbation strategies for studying protein conformational landscapes.

Mapping Protein Conformational Landscapes under Strongly Native Conditions with Hydrogen Exchange Mass Spectrometry.

The thermodynamic stability and kinetic barriers separating protein conformations under native conditions are critical for proper protein function and for understanding dysfunction in diseases of protein conformation. Traditional methods to probe protein unfolding and folding employ denaturants and highly non-native conditions, which may destabilize intermediate species or cause irreversible aggregation, especially at the high protein concentrations typically required. Hydrogen exchange (HX) is ideal for detecting conformational behavior under native conditions without the need for denaturants, but detection by NMR is limited to small highly soluble proteins. Mass spectrometry (MS) can, in principle, greatly extend the applicability of native-state HX to larger proteins and lower concentrations. However, quantitative analysis of HXMS profiles is currently limited by experimental and theoretical challenges. Here we address both limitations, by proposing an approach based on using standards to eliminate the systematic experimental artifacts in HXMS profiles, and developing the theoretical framework to describe HX behavior across all regimes based on the Linderstrøm-Lang formalism. We demonstrate proof of principle by a practical application to native-state HX of a globular protein. The framework and the practical tools developed advance the ability of HXMS to extract thermodynamic and kinetic conformational parameters of proteins under native conditions.

Protein Conformational Landscapes and Catalysis. Influence of Active Site Conformations in the Reaction Catalyzed by L-Lactate Dehydrogenase.

In the last decade L-Lactate Dehydrogenase (LDH) has become an extremely useful marker in both clinical diagnosis and in monitoring the course of many human diseases. It has been assumed from the 80s that the full catalytic process of LDH starts with the binding of the cofactor and the substrate followed by the enclosure of the active site by a mobile loop of the protein before the reaction to take place. In this paper we show that the chemical step of the LDH catalyzed reaction can proceed within the open loop conformation, and the different reactivity of the different protein conformations would be in agreement with the broad range of rate constants measured in single molecule spectrometry studies. Starting from a recently solved X-ray diffraction structure that presented an open loop conformation in two of the four chains of the tetramer, QM/MM free energy surfaces have been obtained at different levels of theory. Depending on the level of theory used to describe the electronic structure, the free energy barrier for the transformation of pyruvate into lactate with the open conformation of the protein varies between 12.9 and 16.3 kcal/mol, after quantizing the vibrations and adding the contributions of recrossing and tunneling effects. These values are very close to the experimentally deduced one (14.2 kcal·mol-1) and ~2 kcal·mol-1 smaller than the ones obtained with the closed loop conformer. Calculation of primary KIEs and IR spectra in both protein conformations are also consistent with our hypothesis and in agreement with experimental data. Our calculations suggest that the closure of the active site is mainly required for the inverse process; the oxidation of lactate to pyruvate. According to this hypothesis H4 type LDH enzyme molecules, where it has been propose that lactate is transformed into pyruvate, should have a better ability to close the mobile loop than the M4 type LDH molecules.

Mechanical Aspects of Protein Thermostability

Because thermophilic proteins are stable and functional at high temperature but generally lack activity under ambient conditions, it was suggested that thermal stability can correspond to enhanced mechanical rigidity. While this concept has initially found wide experimentally support, its generality has been later questioned. It is then natural to inquire the correlation between protein thermal and mechanical stabilities using single-molecule force-spectroscopy experiments. Here, we will present results of a combination of computational techniques, mainly based on Molecular Dynamics simulations, to tackle these problems for several mesophilic/thermophilic homologues of different molecular complexity.By applying innovative network analysis to map the protein conformational landscape, we first question the universality of the rigidity paradigm. In fact we show that for several paris of homologues, thermophiles can be as flexible as their mesophilic variant with important effects coming from the local partition of rigid/flexible regions, protein oligomerization state, or the time and length scales considered.We will then focus on the correlation among thermostability and mechanical resistance. The object under investigation is a pair of mesophilic/thermophilic cold-shock proteins for which experimental data are available. We have first implemented an enhanced-sampling algorithm which allows us to explore the proteins’ free-energy landscape over a wide range of temperatures, and we have used constant-force steered MD to investigate the effect of mechanical force. Our results suggest that thermal stability does not guarantee a mechanical one and that the associated unfolding mechanisms, of which our simulations provide extensive details, are very different. We also aim at identifying the weak-points of the protein mechanical stability and how more stable mutants can be designed. If such mutants also exhibit increased thermal stability, our approach could prove useful in numerous applications.

Dynamically achieved active site precision in enzyme catalysis.

ConspectusThe grand challenge in enzymology is to define and understand all of the parameters that contribute to enzymes’ enormous rate accelerations. The property of hydrogen tunneling in enzyme reactions has moved the focus of research away from an exclusive focus on transition state stabilization toward the importance of the motions of the heavy atoms of the protein, a role for reduced barrier width in catalysis, and the sampling of a protein conformational landscape to achieve a family of protein substates that optimize enzyme–substrate interactions and beyond.This Account focuses on a thermophilic alcohol dehydrogenase for which the chemical step of hydride transfer is rate determining across a wide range of experimental conditions. The properties of the chemical coordinate have been probed using kinetic isotope effects, indicating a transition in behavior below 30 °C that distinguishes nonoptimal from optimal C–H activation. Further, the introduction of single site mutants has the impact of either enhancing or eliminating the temperature dependent transition in catalysis. Biophysical probes, which include time dependent hydrogen/deuterium exchange and fluorescent lifetimes and Stokes shifts, have also been pursued. These studies allow the correlation of spatially resolved transitions in protein motions with catalysis. It is now possible to define a long-range network of protein motions in ht-ADH that extends from a dimer interface to the substrate binding domain across to the cofactor binding domain, over a distance of ca. 30 Å. The ongoing challenge to obtaining spatial and temporal resolution of catalysis-linked protein motions is discussed.

Role of Internal Water on Protein Thermal Stability: The Case of Homologous G Domains.

In this work, we address the question of whether the enhanced stability of thermophilic proteins has a direct connection with internal hydration. Our model systems are two homologous G domains of different stability: the mesophilic G domain of the elongation factor thermal unstable protein from E. coli and the hyperthermophilic G domain of the EF-1α protein from S. solfataricus. Using molecular dynamics simulation at the microsecond time scale, we show that both proteins host water molecules in internal cavities and that these molecules exchange with the external solution in the nanosecond time scale. The hydration free energy of these sites evaluated via extensive calculations is found to be favorable for both systems, with the hyperthermophilic protein offering a slightly more favorable environment to host water molecules. We estimate that, under ambient conditions, the free energy gain due to internal hydration is about 1.3 kcal/mol in favor of the hyperthermophilic variant. However, we also find that, at the high working temperature of the hyperthermophile, the cavities are rather dehydrated, meaning that under extreme conditions other molecular factors secure the stability of the protein. Interestingly, we detect a clear correlation between the hydration of internal cavities and the protein conformational landscape. The emerging picture is that internal hydration is an effective observable to probe the conformational landscape of proteins. In the specific context of our investigation, the analysis confirms that the hyperthermophilic G domain is characterized by multiple states and it has a more flexible structure than its mesophilic homologue.

The conformational response to Zn(II) and Ni(II) binding of Sporosarcina pasteurii UreG, an intrinsically disordered GTPase.

Urease is an essential Ni(II) enzyme involved in the nitrogen metabolism of bacteria, plants and fungi. Ni(II) delivery into the enzyme active site requires the presence of four accessory proteins, named UreD, UreF, UreG and UreE, acting through a complex protein network regulated by metal binding and GTP hydrolysis. The GTPase activity is catalyzed by UreG, which couples this function to a non-enzymatic role as a molecular chaperone. This moonlighting activity is reflected in a flexible fold that makes UreG the first discovered intrinsically disordered enzyme. UreG binds Ni(II) and Zn(II),which in turn modulate the interactions with other urease chaperones. The aim of this study is to understand the structural implications of metal binding to Sporosarcina pasteurii UreG (SpUreG). A combination of light scattering, calorimetry, mass spectrometry, and NMR spectroscopy revealed that SpUreG exists in monomer-dimer equilibrium (K(d)= 45 µM), sampling three distinct folding populations with different degrees of compactness. Binding of Zn(II) ions, occurring in two distinct sites (K(d1) = 3 nM, K(d2) = 0.53 µM), shifts the protein conformational landscape toward the more compact population, while maintaining the overall protein structural plasticity. Differently, binding of Ni(II) ions occurs in three binding sites (K(d1(= 14 µM; K(d2) = 270 µM; K(d3)= 160 µM), with much weaker influence on the protein conformational equilibrium. These distinct conformational responses of SpUreG to Ni(II) and Zn(II) binding suggest that selective metal binding modulates protein plasticity, possibly having an impact on the protein-protein interactions and the enzymatic activity of UreG.

Measuring the hydrogen/deuterium exchange of proteins at high spatial resolution by mass spectrometry: overcoming gas-phase hydrogen/deuterium scrambling.

Proteins are dynamic molecules that exhibit conformational flexibility to function properly. Well-known examples of this are allosteric regulation of protein activity and ligand-induced conformational changes in protein receptors. Detailed knowledge of the conformational properties of proteins is therefore pertinent to both basic and applied research, including drug development, since the majority of drugs target protein receptors and a growing number of drugs introduced to the market are therapeutic peptides or proteins. X-ray crystallography provides a static picture at atomic resolution of the lowest-energy structure of the native ensemble. There is a growing need for sensitive analytical tools to explore all of the significant molecular structures in the conformational landscape of proteins. Hydrogen/deuterium exchange monitored by mass spectrometry (HDX-MS) has recently emerged as a powerful method for characterizing protein conformational dynamics. The basis of this method is the fact that backbone amides in stable hydrogen-bonded structures (e.g., α-helices and β-sheets) are protected against exchange with the aqueous solvent. All protein structures are dynamic, however, and eventually all of the protecting hydrogen bonds will transiently break as the protein--according to thermodynamic principles--cycles through partially unfolded states that correspond to excited free energy levels. As a result, all of the backbone amides will eventually become temporarily solvent-exposed and exchange-competent over time. Consequently, a folded protein in D2O will gradually incorporate deuterium into its backbone amides, and the kinetics of the process can be readily monitored by mass spectrometry. The deuterium uptake kinetics for the intact protein (global exchange kinetics) represents the sum of the exchange kinetics for the individual backbone amides. Local exchange kinetics is typically achieved by using pepsin digestion under quench conditions (i.e., under cold acidic conditions where the amide hydrogen exchange rate is slowed by many orders of magnitude). The ability to localize the individual deuterated residues (the spatial resolution) is determined by the size (typically ∼7-15 residues) and the number of peptic peptides. These peptides provide a relatively coarse-grained picture of the protein dynamics. A fundamental understanding of the relationship between protein function/dysfunction and conformational dynamics requires in many cases higher resolution and ultimately single-residue resolution. In this Account, we summarize our efforts to achieve single-residue deuterium levels in proteins by electron-based or laser-induced gas-phase fragmentation methods. A crucial analytical requirement for this approach is that the pattern of deuterium labeling from solution is retained in the gas-phase fragment ions. It is therefore essential to control and minimize any occurrence of gas-phase randomization of the solution deuterium label (H/D scrambling) during the MS experiment. For this purpose, we have developed model peptide probes to accurately measure the onset and extent of H/D scrambling. Our analytical procedures to control the occurrence of H/D scrambling are detailed along with the physical parameters that induce it during MS analysis. In light of the growing use of gas-phase dissociation experiments to measure the HDX of proteins in order to obtain a detailed characterization and understanding of the dynamic conformations and interactions of proteins at the molecular level, we discuss the perspectives and challenges of future high-resolution HDX-MS methodology.

Binding-competent states for L-arginine in E. coli arginine repressor apoprotein.

Arginine repressor of E. coli is a multifunctional hexameric protein that provides feedback regulation of arginine metabolism upon activation by the negatively cooperative binding of L-arginine. Interpretation of this complex system requires an understanding of the protein's conformational landscape. The ~50kDa hexameric C-terminal domain was studied by 100ns molecular dynamics simulations in the presence and absence of the six L-arg ligands that bind at the trimer-trimer interface. A rotational shift between trimers followed by rotational oscillation occurs in the production phase of the simulations only when L-arg is absent. Analysis of the system reveals that the degree of rotation is correlated with the number of hydrogen bonds across the trimer interface. The trajectory presents frames with one or more apparently open binding sites into which one L-arg could be docked successfully in three different instances, indicating that a binding-competent state of the system is occasionally sampled. Simulations of the resulting singly-liganded systems reveal for the first time that the binding of one L-arg results in a holoprotein-like conformational distribution.