Conformational variability of solution nuclear magnetic resonance structures

Inference of Joint Conformational Distributions from Separately Acquired Experimental Measurements

Flexible proteins serve vital roles in a multitude of biological processes. However, determining their full conformational ensembles is extremely difficult because this requires detailed knowledge about the heterogeneity of the protein's degrees of freedom. Label-based experiments such as double electron-electron resonance (DEER) are very useful in studying flexible proteins, as they provide distributional data on heterogeneity. These experiments are typically performed separately, so information about correlation between distributions is lost. We have developed a method to recover correlation information using nonequilibrium work estimates in molecular dynamics refinement. We tested this method on a simple model of an alternating-access transporter for which the true joint distributions are known, and it successfully recovered the true joint distribution. We also applied our method to the protein syntaxin-1a, where it discarded physically implausible conformations. Our method thus provides a way to recover correlation structure in separate experimental measurements of conformational ensembles and refines the resulting structural ensemble.

Hybrid Refinement of Heterogeneous Conformational Ensembles Using Spectroscopic Data

Multistructured biomolecular systems play crucial roles in a wide variety of cellular processes but have resisted traditional methods of structure determination, which often resolve only a few low-energy states. High-resolution structure determination using experimental methods that yield distributional data remains extremely difficult, especially when the underlying conformational ensembles are quite heterogeneous. We have therefore developed a method to integrate sparse, multimultimodal spectroscopic data to obtain high-resolution estimates of conformational ensembles. We have tested our method by incorporating double electron-electron resonance data on the soluble N-ethylmaleimide-sensitive factor attachment receptor (SNARE) protein syntaxin-1a into biased molecular dynamics simulations. We find that our method substantially outperforms existing state-of-the-art methods in capturing syntaxin's open-closed conformational equilibrium and further yields new conformational states that are consistent with experimental data and may help in understanding syntaxin's function. Our improved methods for refining heterogeneous conformational ensembles from spectroscopic data will greatly accelerate the structural understanding of such systems.

Refinement of Highly Flexible Protein Structures using Simulation-Guided Spectroscopy

Highly flexible proteins present a special challenge for structure determination because they are multi-structured yet not disordered, so their conformational ensembles are essential for understanding function. Because spectroscopic measurements of multiple conformational populations often provide sparse data, experiment selection is a limiting factor in conformational refinement. A molecular simulations- and information-theory based approach to select which experiments best refine conformational ensembles has been developed. This approach was tested on three flexible proteins. For proteins where a clear mechanistic hypothesis exists, experiments that test this hypothesis were systematically identified. When available data did not yield such mechanistic hypotheses, experiments that significantly outperform structure-guided approaches in conformational refinement were identified. This approach offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

Probing Structural Changes among Analogous Inhibitor-Bound Forms of HIV-1 Protease and a Drug-Resistant Mutant in Solution by Nuclear Magnetic Resonance

In the era of state-of-the-art inhibitor design and high-resolution structural studies, detection of significant but small protein structural differences in the inhibitor-bound forms is critical to further developing the inhibitor. Here, we probed differences in HIV-1 protease (PR) conformation among darunavir and four analogous inhibitor-bound forms and compared them with a drug-resistant mutant using nuclear magnetic resonance chemical shifts. Changes in amide chemical shifts of wild-type (WT) PR among these inhibitor-bound forms, ΔCSP, were subtle but detectable and extended >10 Å from the inhibitor-binding site, asymmetrically between the two subunits of PR. Molecular dynamics simulations revealed differential local hydrogen bonding as the molecular basis of this remote asymmetric change. Inhibitor-bound forms of the drug-resistant mutant also showed a similar long-range ΔCSP pattern. Differences in ΔCSP values of the WT and the mutant (ΔΔCSPs) were observed at the inhibitor-binding site and in the surrounding region. Comparing chemical shift changes among highly analogous inhibitors and ΔΔCSPs effectively eliminated local environmental effects stemming from different chemical groups and enabled exploitation of these sensitive parameters to detect subtle protein conformational changes and to elucidate asymmetric and remote conformational effects upon inhibitor interaction.

eNORA2 Exact NOE Analysis Program

We have recently developed an NMR protocol to extract exact distances between nuclei in proteins from an exact interpretation of NOESY buildup intensities (eNOEs). This enabled us to calculate multistate structural ensembles that exhibit realistic spatial sampling and long-range correlations. Our initial studies were laborious and required a deep understanding of the underlying spin dynamics. Here, we present a MatLab package that integrates all data processing steps required to convert intensities of assigned peaks in NOESY series into upper and lower distance limits for structure calculation. Those steps include organization of the data in object format, extraction of autorelaxation and cross-relaxation rate constants by fitting of diagonal peak decays and cross peak buildups, validation of the data, correction for spin diffusion, graphical display of the results, and generation of distance limits in CYANA compatible format. The analysis may be carried out using a full relaxation matrix or a simplified "divide and conquer" approach that allows for partial deuteration of protons. As the program does not require expertise beyond that of standard resonance assignment/structure calculation, it is suitable for experts and nonexperts alike.

Direct Investigation of Slow Correlated Dynamics in Proteins via Dipolar Interactions

The synchronization of native state motions as they transition between microstates influences catalysis kinetics, mediates allosteric interactions, and reduces the conformational entropy of proteins. However, it has proven difficult to describe native microstates because they are usually minimally frustrated and may interconvert on the micro- to millisecond time scale. Direct observation of concerted equilibrium fluctuations would therefore be an important tool for describing protein native states. Here we propose a strategy that relates NMR cross-correlated relaxation (CCR) rates between dipolar interactions to residual dipolar couplings (RDCs) of individual consecutive H(N)-N and H(α)-C(α) bonds, which act as a proxy for the peptide planes and the side chains, respectively. Using Xplor-NIH ensemble structure calculations restrained with the RDC and CCR data, we observe collective motions on time scales slower than nanoseconds in the backbone for GB3. To directly access the correlations from CCR, we develop a structure-free data analysis. The resulting dynamic correlation map is consistent with the ensemble-restrained simulations and reveals a complex network. In general, we find that the bond motions are on average slightly correlated and that the local environment dominates many observations. Despite this, some patterns are typical over entire secondary structure elements. In the β-sheet, nearly all bonds are weakly correlated, and there is an approximately binary alternation in correlation intensity corresponding to the solvent exposure/shielding alternation of the side chains. For α-helices, there is also a weak correlation in the H(N)-N bonds. The degree of correlation involving H(α)-C(α) bonds is directly affected by side-chain fluctuations, whereas loops show complex and nonuniform behavior.

Solid-State NMR-Restrained Ensemble Dynamics of a Membrane Protein in Explicit Membranes

Solid-state NMR has been used to determine the structures of membrane proteins in native-like lipid bilayer environments. Most structure calculations based on solid-state NMR observables are performed using simulated annealing with restrained molecular dynamics and an energy function, where all nonbonded interactions are represented by a single, purely repulsive term with no contributions from van der Waals attractive, electrostatic, or solvation energy. To our knowledge, this is the first application of an ensemble dynamics technique performed in explicit membranes that uses experimental solid-state NMR observables to obtain the refined structure of a membrane protein together with information about its dynamics and its interactions with lipids. Using the membrane-bound form of the fd coat protein as a model membrane protein and its experimental solid-state NMR data, we performed restrained ensemble dynamics simulations with different ensemble sizes in explicit membranes. For comparison, a molecular dynamics simulation of fd coat protein was also performed without any restraints. The average orientation of each protein helix is similar to a structure determined by traditional single-conformer approaches. However, their variations are limited in the resulting ensemble of structures with one or two replicas, as they are under the strong influence of solid-state NMR restraints. Although highly consistent with all solid-state NMR observables, the ensembles of more than two replicas show larger orientational variations similar to those observed in the molecular dynamics simulation without restraints. In particular, in these explicit membrane simulations, Lys(40), residing at the C-terminal side of the transmembrane helix, is observed to cause local membrane curvature. Therefore, compared to traditional single-conformer approaches in implicit environments, solid-state NMR restrained ensemble simulations in explicit membranes readily characterize not only protein dynamics but also protein-lipid interactions in detail.

Understanding the molecular basis of EGFR kinase domain/MIG-6 peptide recognition complex using computational analyses

Background

Epidermal growth factor receptor (EGFR) signalling plays a major role in biological processes, including cell proliferation, differentiation and survival. Since the over-expression of EGFR causes human cancers, EGFR is an attractive drug target. A tumor suppressor endogenous protein, MIG-6, is known to suppress EGFR over-expression by binding to the C-lobe of EGFR kinase. Thus, this C-lobe of the EGFR kinase is a potential new target for EGFR kinase activity inhibition. In this study, molecular dynamics (MD) simulations and binding free energy calculations were used to investigate the protein-peptide interactions between EGFR kinase and a 27-residue peptide derived from MIG-6_s1 segment (residues 336–362).

Results

These 27 residues of MIG-6_s1 were modeled from the published MIG-6 X-ray structure. The binding dynamics were detailed by applying the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method to predict the binding free energy. Both van der Waals interactions and non-polar solvation were favorable driving forces for binding process. Six residues of EGFR kinase and eight residues of MIG-6_s1 residues were shown to be responsible for interface binding in which we investigated per residue free energy decomposition and the results from the computational alanine scanning approach. These residues also had higher hydrogen bond occupancies than other residues at the binding interface. The results from the aforementioned calculations reasonably agreed with the previous experimental mutagenesis studies.

Conclusions

Molecular dynamics simulations were used to investigate the interactions of MIG-6_s1 to EGFR kinase domain. Our study provides an insight into such interactions that is useful in guiding the design of novel anticancer therapeutics. The information on our modelled peptide interface with EGFR kinase could be a possible candidate for an EGFR dimerization inhibitor.

A relationship between the transient structure in the monomeric state and the aggregation propensities of α-synuclein and β-synuclein

α-Synuclein is an intrinsically disordered protein whose aggregation is implicated in Parkinson's disease. A second member of the synuclein family, β-synuclein, shares significant sequence similarity with α-synuclein but is much more resistant to aggregation. β-Synuclein is missing an 11-residue stretch in the central non-β-amyloid component region that forms the core of α-synuclein amyloid fibrils, yet insertion of these residues into β-synuclein to produce the βSHC construct does not markedly increase the aggregation propensity. To investigate the structural basis of these different behaviors, quantitative nuclear magnetic resonance data, in the form of paramagnetic relaxation enhancement-derived interatomic distances, are combined with molecular dynamics simulations to generate ensembles of structures representative of the solution states of α-synuclein, β-synuclein, and βSHC. Comparison of these ensembles reveals that the differing aggregation propensities of α-synuclein and β-synuclein are associated with differences in the degree of residual structure in the C-terminus coupled to the shorter separation between the N- and C-termini in β-synuclein and βSHC, making protective intramolecular contacts more likely.

The nuclear Overhauser effect from a quantitative perspective

The nuclear Overhauser enhancement or effect (NOE) is the most important measure in liquid-state NMR with macromolecules. Thus, the NOE is the subject of numerous reviews and books. Here, the NOE is revisited in light of our recently introduced measurements of exact nuclear Overhauser enhancements (eNOEs), which enabled the determination of multiple-state 3D protein structures. This review encompasses all relevant facets from the theoretical considerations to the use of eNOEs in multiple-state structure calculation. Important aspects include a detailed presentation of the relaxation theory relevant for the nuclear Overhauser effect, the estimation of the correction for spin diffusion, the experimental determination of the eNOEs, the conversion of eNOE rates into distances and validation of their quality, the distance-restraint classification and the protocols for calculation of structures and ensembles.

NMR-based simulation studies of Pf1 coat protein in explicit membranes

As time- and ensemble-averaged measures, NMR observables contain information about both protein structure and dynamics. This work represents a computational study to extract such information for membrane proteins from orientation-dependent NMR observables: solid-state NMR chemical shift anisotropy and dipolar coupling, and solution NMR residual dipolar coupling. We have performed NMR-restrained molecular dynamics simulations to refine the structure of the membrane-bound form of Pf1 coat protein in explicit lipid bilayers using the recently measured chemical shift anisotropy, dipolar coupling, and residual dipolar coupling data. From the simulations, we have characterized detailed protein-lipid interactions and explored the dynamics. All simulations are stable and the NMR restraints are well satisfied. The C-terminal transmembrane (TM) domain of Pf1 finds its optimal position in the membrane quickly (within 6 ns), illustrating efficient solvation of TM domains in explicit bilayer environments. Such rapid convergence also leads to well-converged interaction patterns between the TM helix and the membrane, which clearly show the interactions of interfacial membrane-anchoring residues with the lipids. For the N-terminal periplasmic helix of Pf1, we identify a stable, albeit dynamic, helix orientation parallel to the membrane surface that satisfies the amphiphatic nature of the helix in an explicit lipid bilayer. Such detailed information cannot be obtained solely from NMR observables. Therefore, the present simulations illustrate the usefulness of NMR-restrained MD refinement of membrane protein structure in explicit membranes.

Dynamic conformational switching in the chemokine ligand is essential for G-protein-coupled receptor activation

Chemokines mediate diverse functions from organogenesis to mobilizing leucocytes, and are unusual agonists for class-A GPCRs (G-protein-coupled receptors) because of their large size and multi-domain structure. The current model for receptor activation, which involves interactions between chemokine N-loop and receptor N-terminal residues (Site-I) and between chemokine N-terminal and receptor extracellular loop/transmembrane residues (Site-II), fails to describe differences in ligand/receptor selectivity and the activation of multiple signalling pathways. In the present study, we show in neutrophil-activating chemokine CXCL8 that the highly conserved GP (glycine-proline) motif located distal to both N-terminal and N-loop residues couples Site-I and Site-II interactions. GP mutants showed large differences from native-like to complete loss of function that could not be correlated with the specific mutation, receptor affinity or subtype, or a specific signalling pathway. NMR studies indicated that the GP motif does not influence Site-I interactions, but molecular dynamics simulations suggested that this motif dictates substates of the CXCL8 conformational ensemble. We conclude that the GP motif enables diverse receptor functions by controlling cross-talk between Site-I and Site-II, and further propose that the repertoire of chemokine functions is best described by a conformational ensemble model in which a network of long-range coupled indirect interactions mediate receptor activity.

Interdomain dynamics explored by paramagnetic NMR

An ensemble-based approach is presented to explore the conformational space sampled by a multidomain protein showing moderate interdomain dynamics in terms of translational and rotational motions. The strategy was applied on a complex of calmodulin (CaM) with the IQ-recognition motif from the voltage-gated calcium channel Ca(v)1.2 (IQ), which adopts three different interdomain orientations in the crystal. The N60D mutant of calmodulin was used to collect pseudocontact shifts and paramagnetically induced residual dipolar couplings for six different lanthanide ions. Then, starting from the crystal structure, pools of conformations were generated by free MD. We found the three crystal conformations in solution, but four additional MD-derived conformations had to be included into the ensemble to fulfill all the paramagnetic data and cross-validate optimally against unused paramagnetic data. Alternative approaches led to similar ensembles. Our "ensemble" approach is a simple and efficient tool to probe and describe the interdomain dynamics and represents a general method that can be used to provide a proper ensemble description of multidomain proteins.

Characterization of the interdomain motions in hen lysozyme using residual dipolar couplings as replica-averaged structural restraints in molecular dynamics simulations

Hen lysozyme is an enzyme characterized by the presence of two domains whose relative motions are involved in the mechanism of binding and release of the substrates. By using residual dipolar couplings as replica-averaged structural restraints in molecular dynamics simulations, we characterize the breathing motions describing the interdomain fluctuations of this protein. We found that the ensemble of conformations that we determined spans the entire range of structures of hen lysozyme deposited in the Protein Data Bank, including both the free and bound states, suggesting that the thermal motions in the free state provide access to the structures populated upon binding. The approach that we present illustrates how the use of residual dipolar couplings as replica-averaged structural restraints in molecular dynamics simulations makes it possible to explore conformational fluctuations of a relatively large amplitude in proteins.

Ensemble-based interpretations of NMR structural data to describe protein internal dynamics

NMR spectroscopy is the leading technique to characterize protein internal dynamics at the atomic level and on multiple time scales. However, the structural interpretation of the observables obtained by various measurements is not always straightforward and in many cases dynamics-related parameters are only used to “decorate” static structural models without offering explicit description of conformational heterogeneity. To overcome such limitations, several computational techniques have been developed to generate ensemble-based representations of protein structure and dynamics with the use of NMR-derived data. An important common aspect of the methods is that NMR observables and derived parameters are interpreted as properties of the ensemble instead of individual conformers. The resulting ensembles reflect the experimentally determined internal mobility of proteins at a given time scale and can be used to understand the role of internal motions in biological processes at atomic detail. In this review we provide an overview of the calculation methods currently available and examples of biological insights obtained by the ensemble-based models of the proteins investigated.

Molecular dynamics simulations with replica-averaged structural restraints generate structural ensembles according to the maximum entropy principle

In order to characterise the dynamics of proteins, a well-established method is to incorporate experimental parameters as replica-averaged structural restraints into molecular dynamics simulations. Here, we justify this approach in the case of interproton distance information provided by nuclear Overhauser effects by showing that it generates ensembles of conformations according to the maximum entropy principle. These results indicate that the use of replica-averaged structural restraints in molecular dynamics simulations, given a force field and a set of experimental data, can provide an accurate approximation of the unknown Boltzmann distribution of a system.

Structural aspects of amyloid formation

Amyloid fibrils are highly organized and generally insoluble protein aggregates rich in β secondary structure that can be formed by a wide range of sequences. They have been the object of intense scrutiny because their formation has been associated with a number of neurodegenerative disorders such as Alzheimer's, Parkinson's, Huntington's, and Creutzfeldt-Jakob's diseases. As a consequence of these efforts, much is now known about the properties of proteins that render them prone to form amyloid fibrils, about the mechanism of fibrillation, about the molecular structures of the fibrils, and about the forces that stabilize them. The relationship between the structural properties of the monomeric protein and those of the corresponding aggregate has been, in particular, intensively studied. In this chapter, we will provide an account of current knowledge on this intriguing relationship and provide the reader with key references about this topic.

Assessing and refining molecular dynamics simulations of proteins with nuclear magnetic resonance data

The sophistication of the force fields, algorithms and hardware used for molecular dynamics (MD) simulations of proteins is continuously increasing. No matter how advanced the methodology, however, it is essential to evaluate the appropriateness of the structures sampled in a simulation by comparison with quantitative experimental data. Solution nuclear magnetic resonance (NMR) data are particularly useful for checking the quality of protein simulations, as they provide both structural and dynamic information on a variety of temporal and spatial scales. Here, various features and implications of using NMR data to validate and bias MD simulations are outlined, including an overview of the different types of NMR data that report directly on structural properties and of relevant simulation techniques. The focus throughout is on how to properly account for conformational averaging, particularly within the context of the assumptions inherent in the relationships that link NMR data to structural properties.

Molecular dynamics re-refinement of two different small RNA loop structures using the original NMR data suggest a common structure

Restrained molecular dynamics simulations are a robust, though perhaps underused, tool for the end-stage refinement of biomolecular structures. We demonstrate their utility-using modern simulation protocols, optimized force fields, and inclusion of explicit solvent and mobile counterions-by re-investigating the solution structures of two RNA hairpins that had previously been refined using conventional techniques. The structures, both domain 5 group II intron ribozymes from yeast ai5γ and Pylaiella littoralis, share a nearly identical primary sequence yet the published 3D structures appear quite different. Relatively long restrained MD simulations using the original NMR restraint data identified the presence of a small set of violated distance restraints in one structure and a possibly incorrect trapped bulge nucleotide conformation in the other structure. The removal of problematic distance restraints and the addition of a heating step yielded representative ensembles with very similar 3D structures and much lower pairwise RMSD values. Analysis of ion density during the restrained simulations helped to explain chemical shift perturbation data published previously. These results suggest that restrained MD simulations, with proper caution, can be used to "update" older structures or aid in the refinement of new structures that lack sufficient experimental data to produce a high quality result. Notable cautions include the need for sufficient sampling, awareness of potential force field bias (such as small angle deviations with the current AMBER force fields), and a proper balance between the various restraint weights.

Accurate protein structure modeling using sparse NMR data and homologous structure information

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Solid-state NMR ensemble dynamics as a mediator between experiment and simulation

Solid-state NMR (SSNMR) is a powerful technique to describe the orientations of membrane proteins and peptides in their native membrane bilayer environments. The deuterium ((2)H) quadrupolar splitting (DQS), one of the SSNMR observables, has been used to characterize the orientations of various single-pass transmembrane (TM) helices using a semistatic rigid-body model such as the geometric analysis of labeled alanine (GALA) method. However, dynamic information of these TM helices, which could be related to important biological function, can be missing or misinterpreted with the semistatic model. We have investigated the orientation of WALP23 in an implicit membrane of dimyristoylglycerophosphocholine by determining an ensemble of structures using multiple conformer models with a DQS restraint potential. When a single conformer is used, the resulting helix orientation (tilt angle (τ) of 5.6 ± 3.2° and rotation angle (ρ) of 141.8 ± 40.6°) is similar to that determined by the GALA method. However, as the number of conformers is increased, the tilt angles of WALP23 ensemble structures become larger (26.9 ± 6.7°), which agrees well with previous molecular dynamics simulation results. In addition, the ensemble structure distribution shows excellent agreement with the two-dimensional free energy surface as a function of WALP23's τ and ρ. These results demonstrate that SSNMR ensemble dynamics provides a means to extract orientational and dynamic information of TM helices from their SSNMR observables and to explain the discrepancy between molecular dynamics simulation and GALA-based interpretation of DQS data.

Transmembrane helix orientation and dynamics: insights from ensemble dynamics with solid-state NMR observables

As the major component of membrane proteins, transmembrane helices embedded in anisotropic bilayer environments adopt preferential orientations that are characteristic or related to their functional states. Recent developments in solid-state nuclear magnetic resonance (SSNMR) spectroscopy have made it possible to measure NMR observables that can be used to determine such orientations in a native bilayer environment. A quasistatic single conformer model is frequently used to interpret the SSNMR observables, but important motional information can be missing or misinterpreted in the model. In this work, we have investigated the orientation of the single-pass transmembrane domain of viral protein "u" (VpuTM) from HIV-1 by determining an ensemble of structures using multiple conformer models based on the SSNMR ensemble dynamics technique. The resulting structure ensemble shows significantly larger orientational fluctuations while the ensemble-averaged orientation is compatible with the orientation based on the quasistatic model. This observation is further corroborated by comparison with the VpuTM orientation from comparative molecular dynamics simulations in explicit bilayer membranes. SSNMR ensemble dynamics not only reveals the importance of transmembrane helix dynamics in interpretation of SSNMR observables, but also provides a means to simultaneously extract both transmembrane helix orientation and dynamics information from the SSNMR measurements.

An ensemble dynamics approach to decipher solid-state NMR observables of membrane proteins

Solid-state NMR (SSNMR) is an invaluable tool for determining orientations of membrane proteins and peptides in lipid bilayers. Such orientational descriptions provide essential information about membrane protein functions. However, when a semi-static single conformer model is used to interpret various SSNMR observables, important dynamics information can be missing, and, sometimes, even orientational information can be misinterpreted. In addition, over the last decade, molecular dynamics (MD) simulation and semi-static SSNMR interpretation have shown certain levels of discrepancies in terms of transmembrane helix orientation and dynamics. Dynamic fitting models have recently been proposed to resolve these discrepancies by taking into account transmembrane helix whole body motions using additional parameters. As an alternative approach, we have developed SSNMR ensemble dynamics (SSNMR-ED) using multiple conformer models, which generates an ensemble of structures that satisfies the experimental observables without any fitting parameters. In this review, various computational methods for determining transmembrane helix orientations are discussed, and the distributions of VpuTM (from HIV-1) and WALP23 (a synthetic peptide) orientations from SSNMR-ED simulations are compared with those from MD simulations and semi-static/dynamic fitting models. Such comparisons illustrate that SSNMR-ED can be used as a general means to extract both membrane protein structure and dynamics from the SSNMR measurements. This article is part of a Special Issue entitled: Membrane protein structure and function.

Methods of NMR structure refinement: molecular dynamics simulations improve the agreement with measured NMR data of a C-terminal peptide of GCN4-p1

The C-terminal trigger sequence is essential in the coiled-coil formation of GCN4-p1; its conformational properties are thus of importance for understanding this process at the atomic level. A solution NMR model structure of a peptide, GCN4p16-31, encompassing the GCN4-p1 trigger sequence was proposed a few years ago. Derived using a standard single-structure refinement protocol based on 172 nuclear Overhauser effect (NOE) distance restraints, 14 hydrogen-bond and 11 phi torsional-angle restraints, the resulting set of 20 NMR model structures exhibits regular alpha-helical structure. However, the set slightly violates some measured NOE bounds and does not reproduce all 15 measured (3)J(H(N)-H(Calpha))-coupling constants, indicating that different conformers of GCN4p16-31 might be present in solution. With the aim to resolve structures compatible with all NOE upper distance bounds and (3)J-coupling constants, we executed several structure refinement protocols employing unrestrained and restrained molecular dynamics (MD) simulations with two force fields. We find that only configurational ensembles obtained by applying simultaneously time-averaged NOE distance and (3)J-coupling constant restraining with either force field reproduce all the experimental data. Additionally, analyses of the simulated ensembles show that the conformational variability of GCN4p16-31 in solution admitted by the available set of 187 measured NMR data is larger than represented by the set of the NMR model structures. The conformations of GCN4p16-31 in solution differ in the orientation not only of the side-chains but also of the backbone. The inconsistencies between the NMR model structures and the measured NMR data are due to the neglect of averaging effects and the inclusion of hydrogen-bond and torsional-angle restraints that have little basis in the primary, i.e. measured NMR data.

Structure of the complex of [Ru(tpm)(dppz)py](2+) with a B-DNA oligonucleotide - a single-substituent binding switch for a metallo-intercalator

We report the synthesis of three new complexes related to the achiral [Ru(tpm)(dppz)py](2+) cation (tpm=tripyridazole methane, dppz=dipyrido[3,2-a:2',3'-c]phenazine, py=pyridine) that contain an additional single functional group on the monodentate ancillary pyridyl ligand. Computational calculations indicate that the coordinated pyridyl rings are in a fixed orientation parallel to the dppz axis, and that the electrostatic properties of the complexes are very similar. DNA binding studies on the new complexes reveal that the nature and positioning of the functional group has a profound effect on the binding mode and affinity of these complexes. To explore the molecular and structural basis of these effects, circular dichroism and NMR studies on [Ru(tpm)(dppz)py]Cl(2) with the octanucleotides d(AGAGCTCT)(2) and d(CGAGCTCG)(2), were carried out. These studies demonstrate that the dppz ligand intercalates into the G(2)-A(3) step, with {Ru(tpm)py} in the minor groove. They also reveal that the complex intercalates into the binding site in two possible orientations with the pyridyl ligand of the major conformer making close contact with terminal base pairs. We conclude that substitution at the 2- or 3-position of the pyridine ring has little effect on binding, but that substitution at the 4-position drastically disrupts intercalative binding, particularly with a 4-amino substituent, because of steric and electronic interactions with the DNA. These results indicate that complexes derived from these systems have the potential to function as sequence-specific light-switch systems.

Determination of the free energy landscape of alpha-synuclein using spin label nuclear magnetic resonance measurements

Natively unfolded proteins present a challenge for structure determination because they populate highly heterogeneous ensembles of conformations. A useful source of structural information about these states is provided by paramagnetic relaxation enhancement measurements by nuclear magnetic resonance spectroscopy, from which long-range interatomic distances can be estimated. Here we describe a method for using such distances as restraints in molecular dynamics simulations to obtain a mapping of the free energy landscapes of natively unfolded proteins. We demonstrate the method in the case of alpha-synuclein and validate the results by a comparison with electron transfer measurements. Our findings indicate that our procedure provides an accurate estimate of the relative statistical weights of the different conformations populated by alpha-synuclein in its natively unfolded state.

A method to explore protein side chain conformational variability using experimental data

Experimentally measured values of molecular properties or observables of biomolecules such as proteins are generally averages over time and space, which do not contain sufficient information to determine the underlying conformational distribution of the molecules in solution. The relationship between experimentally measured NMR (3)J-coupling values and the corresponding dihedral angle values is a particularly complicated case due to its nonlinear, multiple-valued nature. Molecular dynamics (MD) simulations at constant temperature can generate Boltzmann ensembles of molecular structures that are free from a priori assumptions about the nature of the underlying conformational distribution. They suffer, however, from limited sampling with respect to time and conformational space. Moreover, the quality of the obtained structures is dependent on the choice of force field and solvation model. A recently proposed method that uses time-averaging with local-elevation (LE) biasing of the conformational search provides an elegant means of overcoming these three problems. Using a set of side chain (3)J-coupling values for the FK506 binding protein (FKBP), we first investigate the uncertainty in the angle values predicted theoretically. We then propose a simple MD-based technique to detect inconsistencies within an experimental data set and identify degrees of freedom for which conformational averaging takes place or for which force field parameters may be deficient. Finally, we show that LE MD is the best method for producing ensembles of structures that, on average, fit the experimental data.

Conformational averaging in structural biology: issues, challenges and computational solutions

Most experimental methods in structural biology provide time- and ensemble-averaged signals and, consequently, molecular structures based on such signals often exhibit only idealized, average features. Second, most experimental signals are only indirectly related to real, molecular geometries, and solving a structure typically involves a complicated procedure, which may not always result in a unique solution. To what extent do such conformationally-averaged, non-linear experimental signals and structural models derived from them accurately represent the underlying microscopic reality? Are there some structural motifs that are actually artificially more likely to be "seen" in an experiment simply due to the averaging artifact? Finally, what are the practical consequences of ignoring the averaging effects when it comes to functional and mechanistic implications that we try to glean from experimentally-based structural models? In this review, we critically address the work that has been aimed at studying such questions. We summarize the details of experimental methods typically used in structural biology (most notably nuclear magnetic resonance, X-ray crystallography and different types of spectroscopy), discuss their individual susceptibility to conformational (motional) averaging, and review several theoretical approaches, most importantly molecular dynamics simulations that are increasingly being used to aid experimentalists in interpreting structural biology experiments.

Structure of the inhibitor W7 bound to the regulatory domain of cardiac troponin C

The calmodulin antagonist W7 binds to troponin C in the presence of Ca(2+) and inhibits striated muscle contraction. This study integrates multiple data into the structure of the regulatory domain of human cardiac troponin C (cNTnC) bound to Ca(2+) and W7. The protein-W7 interface is defined through a three-dimensional {(1)H,(13)C}-edited-{(1)H,(12)C}-detected NOESY NMR experiment, and other aspects of the structure are modeled as perturbations to previously known coordinates and restraints. The structure determination protocol optimizes the protein-W7 contacts prior to the introduction of protein-W7 steric interactions or conformational changes in the protein. The structure determination protocol gives families of conformers that all have an optimal docking as assessed by satisfaction of the target function. The structure supports the previously proposed troponin I blocking mechanism for the activity of W7 in striated muscle and suggests a role for the flexible tail of W7 in stabilization of the bound state. This clarifies the structure-activity relationships of W7 and implicates an electrostatically mediated component of activity in common analogues of W7, including the antipsychotic trifluoroperazine and the cardiotonic levosimendan.

Similarity measures for protein ensembles

Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations. However, instead of examining individual conformations it is in many cases more relevant to analyse ensembles of conformations that have been obtained either through experiments or from methods such as molecular dynamics simulations. We here present three approaches that can be used to compare conformational ensembles in the same way as the root mean square deviation is used to compare individual pairs of structures. The methods are based on the estimation of the probability distributions underlying the ensembles and subsequent comparison of these distributions. We first validate the methods using a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single-molecule refinement.

Geometry-based sampling of conformational transitions in proteins

The fast and accurate prediction of protein flexibility is one of the major challenges in protein science. Enzyme activity, signal transduction, and ligand binding are dynamic processes involving essential conformational changes ranging from small side chain fluctuations to reorientations of entire domains. In the present work, we describe a reimplementation of the CONCOORD approach, termed tCONCOORD, which allows a computationally efficient sampling of conformational transitions of a protein based on geometrical considerations. Moreover, it allows for the extraction of the essential degrees of freedom, which, in general, are the biologically relevant ones. The method rests on a reliable estimate of the stability of interactions observed in a starting structure, in particular those interactions that change during a conformational transition. Applications to adenylate kinase, calmodulin, aldose reductase, T4-lysozyme, staphylococcal nuclease, and ubiquitin show that experimentally known conformational transitions are faithfully predicted.

A large data set comparison of protein structures determined by crystallography and NMR: statistical test for structural differences and the effect of crystal packing

The existence of a large number of proteins for which both nuclear magnetic resonance (NMR) and X-ray crystallographic coordinates have been deposited into the Protein Data Bank (PDB) makes the statistical comparison of the corresponding crystal and NMR structural models over a large data set possible, and facilitates the study of the effect of the crystal environment and other factors on structure. We present an approach for detecting statistically significant structural differences between crystal and NMR structural models which is based on structural superposition and the analysis of the distributions of atomic positions relative to a mean structure. We apply this to a set of 148 protein structure pairs (crystal vs NMR), and analyze the results in terms of methodological and physical sources of structural difference. For every one of the 148 structure pairs, the backbone root-mean-square distance (RMSD) over core atoms of the crystal structure to the mean NMR structure is larger than the average RMSD of the members of the NMR ensemble to the mean, with 76% of the structure pairs having an RMSD of the crystal structure to the mean more than a factor of two larger than the average RMSD of the NMR ensemble. On average, the backbone RMSD over core atoms of crystal structure to the mean NMR is approximately 1 A. If non-core atoms are included, this increases to 1.4 A due to the presence of variability in loops and similar regions of the protein. The observed structural differences are only weakly correlated with the age and quality of the structural model and differences in conditions under which the models were determined. We examine steric clashes when a putative crystalline lattice is constructed using a representative NMR structure, and find that repulsive crystal packing plays a minor role in the observed differences between crystal and NMR structures. The observed structural differences likely have a combination of physical and methodological causes. Stabilizing attractive interactions arising from intermolecular crystal contacts which shift the equilibrium of the crystal structure relative to the NMR structure is a likely physical source which can account for some of the observed differences. Methodological sources of apparent structural difference include insufficient sampling or other issues which could give rise to errors in the estimates of the precision and/or accuracy.

The helix-turn-helix motif as an ultrafast independently folding domain: the pathway of folding of Engrailed homeodomain

Helices 2 and 3 of Engrailed homeodomain (EnHD) form a helix-turn-helix (HTH) motif. This common motif is believed not to fold independently, which is the characteristic feature of a motif rather than a domain. But we found that the EnHD HTH motif is monomeric and folded in solution, having essentially the same structure as in full-length protein. It had a sigmoidal thermal denaturation transition. Both native backbone and local tertiary interactions were formed concurrently at 4 x 10(5) s(-1) at 25 degrees C, monitored by IR and fluorescence T-jump kinetics, respectively, the same rate constant as for the fast phase in the folding of EnHD. The HTH motif, thus, is an ultrafast-folding, natural protein domain. Its independent stability and appropriate folding kinetics account for the stepwise folding of EnHD, satisfy fully the criteria for an on-pathway intermediate, and explain the changes in mechanism of folding across the homeodomain family. Experiments on mutated and engineered fragments of the parent protein with different probes allowed the assignment of the observed kinetic phases to specific events to show that EnHD is not an example of one-state downhill folding.

Strategies for dealing with conformational sampling in structural calculations of flexible or kinked transmembrane peptides

Peptides corresponding to transmembrane (TM) segments from membrane proteins provide a potential route for the determination of membrane protein structure. We have determined that 2 functionally critical TM segments from the mammalian Na+/H+ exchanger display well converged structure in regions separated by break points. The flexibility of these break points results in conformational sampling in solution. A brief review of available NMR structures of helical membrane proteins demonstrates that there are a number of published structures showing similar properties. Such flexibility is likely indicative of kinks in the full-length protein. This minireview focuses on methods and protocols for NMR structure calculation and analysis of peptide structures under conditions of conformational sampling. The methods outlined allow the identification and analysis of structured peptides containing break points owing to conformational sampling and the differentiation between oligomerization and ensemble-averaged observation of multiple peptide conformations.

A physical picture of atomic motions within the Dickerson DNA dodecamer in solution derived from joint ensemble refinement against NMR and large-angle X-ray scattering data

The structure and dynamics of the Dickerson DNA dodecamer [5'd(CGCGAATTCGCG)2] in solution have been investigated by joint simulated annealing refinement against NMR and large-angle X-ray scattering data (extending from 0.25 to 3 A-1). The NMR data comprise an extensive set of hetero- and homonuclear residual dipolar coupling and 31P chemical shift anisotropy restraints in two alignment media, supplemented by NOE and 3J coupling data. The NMR and X-ray scattering data cannot be fully ascribed to a single structure representation, indicating the presence of anisotropic motions that impact the experimental observables in different ways. Refinement with ensemble sizes (Ne) of >or=2 to represent the atomic motions reconciles all the experimental data within measurement error. Cross validation against both the dipolar coupling and X-ray scattering data suggests that the optimal ensemble size required to account for the current data is 4. The resulting ensembles permit one to obtain a detailed view of the conformational space sampled by the dodecamer in solution and permit one to analyze fluctuations in helicoidal parameters, sugar puckers, and BI-BII backbone transitions and to obtain quantitative metrics of atomic motion such as generalized order parameters and thermal B factors. The calculated order parameters are in good agreement with experimental order parameters obtained from 13C relaxation measurements. Although DNA behaves as a relatively rigid rod with a persistence length of approximately 150 bp, dynamic conformational heterogeneity at the base pair level is functionally important since it readily permits optimization of intermolecular protein-DNA interactions.

The MUMO (minimal under-restraining minimal over-restraining) method for the determination of native state ensembles of proteins

While reliable procedures for determining the conformations of proteins are available, methods for generating ensembles of structures that also reflect their flexibility are much less well established. Here we present a systematic assessment of the ability of ensemble-averaged molecular dynamics simulations with ensemble-averaged NMR restraints to simultaneously reproduce the average structure of proteins and their associated dynamics. We discuss the effects that under-restraining (overfitting) and over-restraining (underfitting) have on the structures generated in ensemble-averaged molecular simulations. We then introduce the MUMO (minimal under-restraining minimal over-restraining) method, a procedure in which different observables are averaged over a different number of molecules. As both over-restraining and under-restraining are significantly reduced in the MUMO method, it is possible to generate ensembles of conformations that accurately characterize both the structure and the dynamics of native states of proteins. The application of the MUMO method to the protein ubiquitin yields a high-resolution structural ensemble with an RDC Q-factor of 0.19.

Determination of conformationally heterogeneous states of proteins

Although conformationally heterogeneous states of proteins are involved in a range of important biological processes, including protein folding and misfolding, and signal transduction, detailed knowledge of their structure and dynamics is still largely missing. Proteins in many of these states are constantly changing shape, such that they are better described as ensembles of conformations rather than in terms of well-defined structures, as is normally the case for native states. Methods in which molecular simulations are combined with experimental measurements are emerging as a powerful route to the accurate determination of the conformational properties of these states of proteins.

Atomic-level characterization of disordered protein ensembles

The roles of unfolded states of proteins in normal folding and in diseases involving aggregation, as well as the prevalence and regulatory functions of intrinsically disordered proteins, have become increasingly recognized. The structural representation of these disordered states as ensembles of interconverting conformers can therefore provide critical insights. Experimental methods can be used to probe ensemble-averaged structural properties of disordered states and computational approaches generate representative ensembles of conformers using experimental restraints. In particular, NMR and small-angle X-ray scattering provide quantitative data that can readily be incorporated into calculations. These techniques have gleaned structural information about denatured, unfolded and intrinsically disordered proteins. The use of experimental data in different computational approaches, including ensemble molecular dynamics simulations and algorithms that assign populations to pregenerated conformers, has highlighted the presence of both local and long-range structure, and the occurrence of native-like and non-native interactions in unfolded and denatured states. Analysis of the resulting ensembles has suggested important implications of this fluctuating structure for folding, aggregation and binding.