Selecting Conformational Ensembles Using Residual Electron and Anomalous Density (READ).

Heterogeneous and dynamic biomolecular complexes play a central role in many cellular processes but are poorly understood due to experimental challenges in characterizing their structural ensembles. To address these difficulties, we developed a hybrid methodology that combines X-ray crystallography with ensemble selections typically used in NMR studies to determine structural ensembles of heterogeneous biomolecular complexes. The method, termed READ, for residual electron and anomalous density, enables the visualization of heterogeneous conformational ensembles of complexes within crystals. Here we present a detailed protocol for performing the ensemble selections to construct READ ensembles. From a diverse pool of binding poses, a selection scheme is used to determine a subset of conformations that maximizes agreement with the X-ray data. Overall, READ is a general approach for obtaining a high-resolution view of dynamic protein-protein complexes.

The Mechanism of HdeA Unfolding and Chaperone Activation.

HdeA is a periplasmic chaperone that is rapidly activated upon shifting the pH to acidic conditions. This activation is thought to involve monomerization of HdeA. There is evidence that monomerization and partial unfolding allow the chaperone to bind to proteins denatured by low pH, thereby protecting them from aggregation. We analyzed the acid-induced unfolding of HdeA using NMR spectroscopy and fluorescence measurements, and obtained experimental evidence suggesting a complex mechanism in HdeA's acid-induced unfolding pathway, as previously postulated from molecular dynamics simulations. Counterintuitively, dissociation constant measurements show a stabilization of the HdeA dimer upon exposure to mildly acidic conditions. We provide experimental evidence that protonation of Glu37, a glutamate residue embedded in a hydrophobic pocket of HdeA, is important in controlling HdeA stabilization and thus the acid activation of this chaperone. Our data also reveal a sharp transition from folded dimer to unfolded monomer between pH3 and pH 2, and suggest the existence of a low-populated, partially folded intermediate that could assist in chaperone activation or function. Overall, this study provides a detailed experimental investigation into the mechanism by which HdeA unfolds and activates.

Exploring Protein-Nanoparticle Interactions with Coarse-Grained Protein Folding Models.

Understanding the fundamental biophysics behind protein-nanoparticle (NP) interactions is essential for the design and engineering bio-NP systems. The authors describe the development of a coarse-grained protein-NP model that utilizes a structure centric protein model. A key feature of the protein-NP model is the quantitative inclusion of the hydrophobic character of residues in the protein and their interactions with the NP surface. In addition, the curvature of the NP is taken into account, capturing the protein behavior on NPs of different size. The authors evaluate this model by comparison with experimental results for structure and adsorption of a model protein interacting with an NP. It is demonstrated that the simulation results recapitulate the structure of the small α/ß protein GB1 on the NP for data from circular dichroism and fluorescence spectroscopy. In addition, the calculated protein adsorption free energy agrees well with the experimental value. The authors predict the dependence of protein folding on the NP size, surface chemistry, and temperature. The model has the potential to guide NP design efforts by predicting protein behavior on NP surfaces with various chemical properties and curvatures.

Effect of the Crystal Environment on Side-Chain Conformational Dynamics in Cyanovirin-N Investigated through Crystal and Solution Molecular Dynamics Simulations.

Side chains in protein crystal structures are essential for understanding biochemical processes such as catalysis and molecular recognition. However, crystal packing could influence side-chain conformation and dynamics, thus complicating functional interpretations of available experimental structures. Here we investigate the effect of crystal packing on side-chain conformational dynamics with crystal and solution molecular dynamics simulations using Cyanovirin-N as a model system. Side-chain ensembles for solvent-exposed residues obtained from simulation largely reflect the conformations observed in the X-ray structure. This agreement is most striking for crystal-contacting residues during crystal simulation. Given the high level of correspondence between our simulations and the X-ray data, we compare side-chain ensembles in solution and crystal simulations. We observe large decreases in conformational entropy in the crystal for several long, polar and contacting residues on the protein surface. Such cases agree well with the average loss in conformational entropy per residue upon protein folding and are accompanied by a change in side-chain conformation. This finding supports the application of surface engineering to facilitate crystallization. Our simulation-based approach demonstrated here with Cyanovirin-N establishes a framework for quantitatively comparing side-chain ensembles in solution and in the crystal across a larger set of proteins to elucidate the effect of the crystal environment on protein conformations.

Determining crystal structures through crowdsourcing and coursework.

We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality.

Capturing a Dynamic Chaperone-Substrate Interaction Using NMR-Informed Molecular Modeling.

Chaperones maintain a healthy proteome by preventing aggregation and by aiding in protein folding. Precisely how chaperones influence the conformational properties of their substrates, however, remains unclear. To achieve a detailed description of dynamic chaperone-substrate interactions, we fused site-specific NMR information with coarse-grained simulations. Our model system is the binding and folding of a chaperone substrate, immunity protein 7 (Im7), with the chaperone Spy. We first used an automated procedure in which NMR chemical shifts inform the construction of system-specific force fields that describe each partner individually. The models of the two binding partners are then combined to perform simulations on the chaperone-substrate complex. The binding simulations show excellent agreement with experimental data from multiple biophysical measurements. Upon binding, Im7 interacts with a mixture of hydrophobic and hydrophilic residues on Spy's surface, causing conformational exchange within Im7 to slow down as Im7 folds. Meanwhile, the motion of Spy's flexible loop region increases, allowing for better interaction with different substrate conformations, and helping offset losses in Im7 conformational dynamics that occur upon binding and folding. Spy then preferentially releases Im7 into a well-folded state. Our strategy has enabled a residue-level description of a dynamic chaperone-substrate interaction, improving our understanding of how chaperones facilitate substrate folding. More broadly, we validate our approach using two other binding partners, showing that this approach provides a general platform from which to investigate other flexible biomolecular complexes through the integration of NMR data with efficient computational models.

Visualizing chaperone-assisted protein folding.

Challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone-substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperone Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.

Coupled folding and binding with 2D Window-Exchange Umbrella Sampling.

Intrinsically disordered regions of proteins can gain structure by binding to a partner. This process, of coupled folding and binding (CFaB), is a fundamental part of many important biological processes. Structure-based models have proven themselves capable of revealing fundamental aspects of how CFaB occurs, however, typical methods to enhance the sampling of these transitions, such as replica exchange, do not adequately sample the transition state region of this extremely rare process. Here, we use a variant of Umbrella Sampling to enforce sampling of the transition states of CFaB of HdeA monomers at neutral pH, an extremely rare process that occurs over timescales ranging from seconds to hours. Using high resolution sampling in the transition state region, we cluster states along the principal transition path to obtain a detailed description of coupled binding and folding for the HdeA dimer, revealing new insight into the ensemble of states that are accessible to client recognition. We then demonstrate that exchanges between umbrella sampling windows, as done in previous work, significantly improve relaxation in variables orthogonal to the restraints used. Altogether, these results show that Window-Exchange Umbrella Sampling is a promising approach for systems that exhibit flexible binding, and can reveal transition state ensembles of these systems in high detail. © 2015 Wiley Periodicals, Inc.

Predicting protein backbone chemical shifts from Cα coordinates: extracting high resolution experimental observables from low resolution models.

Given the demonstrated utility of coarse-grained modeling and simulations approaches in studying protein structure and dynamics, developing methods that allow experimental observables to be directly recovered from coarse-grained models is of great importance. In this work, we develop one such method that enables protein backbone chemical shifts (1HN, 1Hα, 13Cα, 13C, 13Cß, and 15N) to be predicted from Cα coordinates. We show that our Cα-based method, LARMORCα, predicts backbone chemical shifts with comparable accuracy to some all-atom approaches. More importantly, we demonstrate that LARMORCα predicted chemical shifts are able to resolve native structure from decoy pools that contain both native and non-native models, and so it is sensitive to protein structure. As an application, we use LARMORCα to characterize the transient state of the fast-folding protein gpW using recently published NMR relaxation dispersion derived backbone chemical shifts. The model we obtain is consistent with the previously proposed model based on independent analysis of the chemical shift dispersion pattern of the transient state. We anticipate that LARMORCα will find utility as a tool that enables important protein conformational substates to be identified by "parsing" trajectories and ensembles generated using coarse-grained modeling and simulations.

Multiscale modeling of a conditionally disordered pH-sensing chaperone.

The pH-sensing chaperone HdeA promotes the survival of enteropathogenic bacteria during transit through the harshly acidic environment of the mammalian stomach. At low pH, HdeA transitions from an inactive, folded, dimer to chaperone-active, disordered, monomers to protect against the acid-induced aggregation of periplasmic proteins. Toward achieving a detailed mechanistic understanding of the pH response of HdeA, we develop a multiscale modeling approach to capture its pH-dependent thermodynamics. Our approach combines pK(a) (logarithmic acid dissociation constant) calculations from all-atom constant pH molecular dynamics simulations with coarse-grained modeling and yields new, atomic-level, insights into HdeA chaperone function that can be directly tested by experiment. "pH triggers" that significantly destabilize the dimer are each located near the N-terminus of a helix, suggesting that their neutralization at low pH destabilizes the helix macrodipole as a mechanism of monomer disordering. Moreover, we observe a non-monotonic change in the pH-dependent stability of HdeA, with maximal stability of the dimer near pH5. This affect is attributed to the protonation Glu37, which exhibits an anomalously high pK(a) value and is located within the hydrophobic dimer interface. Finally, the pH-dependent binding pathway of HdeA comprises a partially unfolded, dimeric intermediate that becomes increasingly stable relative to the native dimer at lower pH values and displays key structural features for chaperone-substrate interaction. We anticipate that the insights from our model will help inform ongoing NMR and biochemical investigations.

Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

Molecular recognition by intrinsically disordered proteins (IDPs) plays a central role in many critical cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here we employ the "Hamiltonian mapping" methodology, which is rooted in the weighted histogram analysis method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing reference simulations on a given Hamiltonian, we illustrate for two model IDPs how this method can extrapolate thermodynamic behavior under a range of modified Hamiltonians, in this case representing changes in the binding affinity (Kd) of the system. Given sufficient conformational sampling in a single trajectory, Hamiltonian mapping accurately reproduces Kd values from direct simulation. This method may be generally applied to systems beyond IDPs in force field optimization and in describing changes in thermodynamic behavior as a function of external conditions for connection with experiment.

Packing interface energetics in different crystal forms of the λ Cro dimer.

Variation among crystal structures of the λ Cro dimer highlights conformational flexibility. The structures range from a wild type closed to a mutant fully open conformation, but it is unclear if each represents a stable solution state or if one may be the result of crystal packing. Here we use molecular dynamics (MD) simulation to investigate the energetics of crystal packing interfaces and the influence of site-directed mutagenesis on them in order to examine the effect of crystal packing on wild type and mutant Cro dimer conformation. Replica exchange MD of mutant Cro in solution shows that the observed conformational differences between the wild type and mutant protein are not the direct consequence of mutation. Instead, simulation of Cro in different crystal environments reveals that mutation affects the stability of crystal forms. Molecular Mechanics Poisson-Boltzmann Surface Area binding energy calculations reveal the detailed energetics of packing interfaces. Packing interfaces can have diverse properties in strength, energetic components, and some are stronger than the biological dimer interface. Further analysis shows that mutation can strengthen packing interfaces by as much as ∼5 kcal/mol in either crystal environment. Thus, in the case of Cro, mutation provides an additional energetic contribution during crystal formation that may stabilize a fully open higher energy state. Moreover, the effect of mutation in the lattice can extend to packing interfaces not involving mutation sites. Our results provide insight into possible models for the effect of crystallization on Cro conformational dynamics and emphasize careful consideration of protein crystal structures.

Network visualization of conformational sampling during molecular dynamics simulation.

Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions.

Binding and folding of the small bacterial chaperone HdeA.

The small pH stress-sensing chaperone HdeA helps pathogenic enteric E. coli survive passage through the severely acidic environment of the mammalian stomach. Under stress conditions, HdeA transitions from an inactive folded dimer to a chaperone-active unfolded monomer to prevent the acid-induced aggregation of periplasmic proteins. Here we use a topology-based Go-like model to delineate the relationship between dimer interface formation and monomer folding and to better understand the structural details of the chaperone activation mechanism. Free energy surfaces show that dimer interface formation and monomer folding proceed concurrently through an on-pathway dimeric intermediate in which one monomer is partially unfolded. The absence of a preexisting fully folded monomer in the proposed binding mechanism is in agreement with HdeA's rapid chaperone response. Binding between unfolded monomers exhibits an enhancement of molecular recognition reminiscent of the fly-casting mechanism. Overall, our simulations further highlight the efficient nature of HdeA's chaperone response and we anticipate that knowledge of a dimeric intermediate will facilitate the interpretation of experimental studies.

Molecular simulation uncovers the conformational space of the λ Cro dimer in solution.

The significant variation among solved structures of the λ Cro dimer suggests its flexibility. However, contacts in the crystal lattice could have stabilized a conformation which is unrepresentative of its dominant solution form. Here we report on the conformational space of the Cro dimer in solution using replica exchange molecular dynamics in explicit solvent. The simulated ensemble shows remarkable correlation with available x-ray structures. Network analysis and a free energy surface reveal the predominance of closed and semi-open dimers, with a modest barrier separating these two states. The fully open conformation lies higher in free energy, indicating that it requires stabilization by DNA or crystal contacts. Most NMR models are found to be unstable conformations in solution. Intersubunit salt bridging between Arg(4) and Glu(53) during simulation stabilizes closed conformations. Because a semi-open state is among the low-energy conformations sampled in simulation, we propose that Cro-DNA binding may not entail a large conformational change relative to the dominant dimer forms in solution.

The N-terminus of the intrinsically disordered protein α-synuclein triggers membrane binding and helix folding.

Alpha-synuclein (αS) is a 140-amino-acid protein that is involved in a number of neurodegenerative diseases. In Parkinson's disease, the protein is typically encountered in intracellular, high-molecular-weight aggregates. Although αS is abundant in the presynaptic terminals of the central nervous system, its physiological function is still unknown. There is strong evidence for the membrane affinity of the protein. One hypothesis is that lipid-induced binding and helix folding may modulate the fusion of synaptic vesicles with the presynaptic membrane and the ensuing transmitter release. Here we show that membrane recognition of the N-terminus is essential for the cooperative formation of helical domains in the protein. We used circular dichroism spectroscopy and isothermal titration calorimetry to investigate synthetic peptide fragments from different domains of the full-length αS protein. Site-specific truncation and partial cleavage of the full-length protein were employed to further characterize the structural motifs responsible for helix formation and lipid-protein interaction. Unilamellar vesicles of varying net charge and lipid compositions undergoing lateral phase separation or chain melting phase transitions in the vicinity of physiological temperatures served as model membranes. The results suggest that the membrane-induced helical folding of the first 25 residues may be driven simultaneously by electrostatic attraction and by a change in lipid ordering. Our findings highlight the significance of the αS N-terminus for folding nucleation, and provide a framework for elucidating the role of lipid-induced conformational transitions of the protein within its intracellular milieu.