Multiple helical conformations of the helix‐turn‐helix region revealed by NOE‐restrained MD simulations of tryptophan aporepressor,TrpR

The nature of flexibility in the helix‐turn‐helix region of E. coli trp aporepressor has been unexplained for many years. The original ensemble of nuclear magnetic resonance (NMR structures showed apparent disorder, but chemical shift and relaxation measurements indicated a helical region. Nuclear Overhauser effect (NOE) data for a temperature‐sensitive mutant showed more helical character in its helix‐turn‐helix region, but nevertheless also led to an apparently disordered ensemble. However, conventional NMR structure determination methods require all structures in the ensemble to be consistent with every NOE simultaneously. This work uses an alternative approach in which some structures of the ensemble are allowed to violate some NOEs to permit modeling of multiple conformational states that are in dynamic equilibrium. Newly measured NOE data for wild‐type aporepressor are used as time‐averaged distance restraints in molecular dynamics simulations to generate an ensemble of helical conformations that is more consistent with the observed NMR data than the apparent disorder in the previously reported NMR structures. The results indicate the presence of alternating helical conformations that provide a better explanation for the flexibility of the helix‐turn‐helix region of trp aporepressor. Structures representing these conformations have been deposited with PDB ID: 5TM0. Proteins 2017; 85:731–740. © 2016 Wiley Periodicals, Inc.     

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 ϕ torsional-angle restraints, the resulting set of 20 NMR model structures exhibits regular α-helical structure. However, the set slightly violates some measured NOE bounds and does not reproduce all 15 measured ³J(H_N-H_Cα)-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 ³J-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 ³J-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.     

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.     

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.     

A refined model for the solution structure of oxidized putidaredoxin

A refined model for the solution structure of oxidized putidaredoxin (Pdxo), a Cys4Fe2S2 ferredoxin, has been determined. A previous structure (Pochapsky et al. (1994) Biochemistry 33, 6424-6432; PDB entry ) was calculated using the results of homonuclear two-dimensional NMR experiments. New data has made it possible to calculate a refinement of the original Pdxo solution structure. First, essentially complete assignments for diamagnetic 15N and 13C resonances of Pdxo have been made using multidimensional NMR methods, and 15N- and 13C-resolved NOESY experiments have permitted the identification of many new NOE restraints for structural calculations. Stereospecific assignments for leucine and valine CH3 resonances were made using biosynthetically directed fractional 13C labeling, improving the precision of NOE restraints involving these residues. Backbone dihedral angle restraints have been obtained using a combination of two-dimensional J-modulated 15N,1H HSQC and 3D (HN)CO(CO)NH experiments. Second, the solution structure of a diamagnetic form of Pdx, that of the C85S variant of gallium putidaredoxin, in which a nonligand Cys is replaced by Ser, has been determined (Pochapsky et al. (1998) J. Biomol. NMR 12, 407-415), providing information concerning structural features not observable in the native ferredoxin due to paramagnetism. Third, a crystal structure of a closely related ferredoxin, bovine adrenodoxin, has been published (Müller et al. (1998) Structure 6, 269-280). This structure has been used to model the metal binding site structure in Pdx. A family of fourteen structures is presented that exhibits an rmsd of 0.51 A for backbone heavy atoms and 0.83 A for all heavy atoms. Exclusion of the modeled metal binding loop region reduces overall the rmsd to 0.30 A for backbone atoms and 0.71 A for all heavy atoms.     

TOUCHSTONEX: protein structure prediction with sparse NMR data

TOUCHSTONEX, a new method for folding proteins that uses a small number of long-range contact restraints derived from NMR experimental NOE (nuclear Overhauser enhancement) data, is described. The method employs a new lattice-based, reduced model of proteins that explicitly represents C(alpha), C(beta), and the sidechain centers of mass. The force field consists of knowledge-based terms to produce protein-like behavior, including various short-range interactions, hydrogen bonding, and one-body, pairwise, and multibody long-range interactions. Contact restraints were incorporated into the force field as an NOE-specific pairwise potential. We evaluated the algorithm using a set of 125 proteins of various secondary structure types and lengths up to 174 residues. Using N/8 simulated, long-range sidechain contact restraints, where N is the number of residues, 108 proteins were folded to a C(alpha)-root-mean-square deviation (RMSD) from native below 6.5 A. The average RMSD of the lowest RMSD structures for all 125 proteins (folded and unfolded) was 4.4 A. The algorithm was also applied to limited experimental NOE data generated for three proteins. Using very few experimental sidechain contact restraints, and a small number of sidechain-main chain and main chain-main chain contact restraints, we folded all three proteins to low-to-medium resolution structures. The algorithm can be applied to the NMR structure determination process or other experimental methods that can provide tertiary restraint information, especially in the early stage of structure determination, when only limited data are available.     

A polynomial-time algorithm for de novo protein backbone structure determination from nuclear magnetic resonance data.

We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo high-resolution biomacromolecular structure determination using experimentally recorded data from either NMR spectroscopy or X-ray crystallography. Previous algorithmic formulations of this problem focused on using local distance restraints from NMR (e.g., nuclear Overhauser effect [NOE] restraints) to determine protein structure. This approach has been shown to be NP-hard, essentially due to the local nature of the constraints. In practice, approaches such as molecular dynamics and simulated annealing, which lack both combinatorial precision and guarantees on running time and solution quality, are used routinely for structure determination. We show that residual dipolar coupling (RDC) data, which gives global restraints on the orientation of internuclear bond vectors, can be used in conjunction with very sparse NOE data to obtain a polynomial-time algorithm for structure determination. Furthermore, an implementation of our algorithm has been applied to six different real biological NMR data sets recorded for three proteins. Our algorithm is combinatorially precise, polynomialtime, and uses much less NMR data to produce results that are as good or better than previous approaches in terms of accuracy of the computed structure as well as running time.     

Metropolis Monte Carlo calculations of DNA structure using internal coordinates and NMR distance restraints: An alternative method for generating a high-resolution solution structure

Summary A new method, a restrained Monte Carlo (rMC) calculation, is demonstrated for generating high-resolution structures of DNA oligonucleotides in solution from interproton distance restraints and bounds derived from complete relaxation matrix analysis of two-dimensional nuclear Overhauser effect (NOE) spectral peak intensities. As in the case of restrained molecular dynamics (rMD) refinement of structures, the experimental distance restraints and bounds are incorporated as a pseudo-energy term (or penalty function) into the mathematical expression for the molecular energy. However, the use of generalized helical parameters, rather than Cartesian coordinates, to define DNA conformation increases efficiency by decreasing by an order of magnitude the number of parameters needed to describe a conformation and by simplifying the potential energy profile. The Metropolis Monte Carlo method is employed to simulate an annealing process. The rMC method was applied to experimental 2D NOE data from the octamer duplex d(GTA-TAATG)·d(CATTATAC). Using starting structures from different locations in conformational space (e.g. A-DNA and B-DNA), the rMC calculations readily converged, with a root-mean-square deviation (RMSD) of <0.3 Å between structures generated using different protocols and starting structures. Theoretical 2D NOE peak intensities were calculated for the rMC-generated structures using the complete relaxation matrix program CORMA, enabling a comparison with experimental intensities via residual indices. Simulation of the vicinal proton coupling constants was carried out for the structures generated, enabling a comparison with the experimental deoxyribose ring coupling constants, which were not utilized in the structure determination in the case of the rMC simulations. Agreement with experimental 2D NOE and scalar coupling data was good in all cases. The rMC structures are quite similar to that refined by a traditional restrained MD approach (RMSD<0.5 Å) despite the different force fields used and despite the fact that MD refinement was conducted with additional restraints imposed on the endocyclic torsion angles of deoxyriboses. The computational time required for the rMC and rMD calculations is about the same. A comparison of structural parameters is made and some limitations of both methods are discussed with regard to the average nature of the experimental restraints used in the refinement.Abbreviations MC Monte Carlo - rMC restrained Monte Carlo - MD molecular dynamics - rMD restrained molecular dynamics - DG distance geometry - EM energy minimization - 2D NOE two-dimensional nuclear Overhauser effect - DQF-COSY double-quantum-filtered correlation spectroscopy - RMSD root-mean-square deviation To whom correspondence should be addressed.     

GENFOLD: a genetic algorithm for folding protein structures using NMR restraints.

We report the development and validation of the program GENFOLD, a genetic algorithm that calculates protein structures using restraints obtained from NMR, such as distances derived from nuclear Overhauser effects, and dihedral angles derived from coupling constants. The program has been tested on three proteins: the POU domain (a small three-helix DNA-binding protein), bovine pancreatic trypsin inhibitor (BPTI), and the starch-binding domain from Aspergillus niger glucoamylase I, a 108-residue beta-sheet protein. Structures were calculated for each protein using published NMR restraints. In addition, structures were calculated for BPTI using artificial restraints generated from a high-resolution crystal structure. In all cases the fittest calculated structures were close to the target structure, and could be refined to structures indistinguishable from the target structures by means of a low-temperature simulated annealing refinement. The effectiveness of the program is similar to that of distance geometry and simulated annealing methods, and it is capable of using a very wide range of restraints as input. It can thus be readily extended to the calculation of structures of large proteins, for which few NOE restraints may be available.     

A variable target intensity-restrained global optimization (VARTIGO) procedure for determining three-dimensional structures of polypeptides from NOESY data: Application to gramicidin-S

Summary A global optimization method for intensity-restrained structure refinement, based on variable target function (VTF) analysis, is illustrated using experimental data on a model peptide, gramicidin-S (GS) dissolved in DMSO. The method (referred to as VARTIGO for variable target intensity-restrained global optimization) involves minimization of a target function in which the range of NOE contacts is gradually increased in successive cycles of optimization in dihedral angle space. Several different starting conformations (including all-trans) have been tested to establish the validity of the method. Not all optimizations were successful, but these were readily identifiable from their large NOE R-factors. We also show that it is possible to simultaneously optimize the rotational correlation time along with the dihedral angles. The structural features of GS thus obtained from the successful optimizations are in excellent agreement with the available experimental data. A comparison is made with structures generated from an intensity-restrained single target function (STF) analysis. The results on GS suggest that VARTIGO refinement is capable of yielding better quality structures. Our work also underscores the need for a simultaneous analysis of different NOE R-factors in judging the quality of optimized structures. The NOESY data on GS in DMSO appear to provide evidence for the presence of two orientations for the ornithine side chain, in fast exchange. The NOESY spectra for this case were analyzed using a relaxation rate matrix which is a weighted average of the relaxation rate matrices for the individual conformations.     

Solution structure of neuronal bungarotoxin determined by two-dimensional NMR spectroscopy: calculation of tertiary structure using systematic homologous model building, dynamical simulated annealing, and restrained molecular dynamics.

Neuronal bungarotoxin has previously been shown, using two-dimensional 1H NMR spectroscopy, to have a triple-stranded antiparallel beta-sheet structure which dimerizes in solution [Oswald, R.E., Sutcliffe, M.J., Bamberger, M., Loring, R.H., Braswell, E., & Dobson, C.M. (1991) Biochemistry 30, 4901-4909]. In this paper, structural calculations are described which use the 582 experimentally measured NOE restraints in conjunction with 27 phi-angle restraints from J-value measurements. The positions of the N-terminal region and C-terminal region were poorly defined in the calculated structures with respect to the remainder of the structure. The region of the structure containing the triple-stranded beta-sheet was, however, well defined and similar to that found in the structure of homologous alpha-bungarotoxin (45% amino acid identity). The experimental restraints did not result in a well-defined dimer interface region because of the small number of NOEs which could be identified in this region. An approach was therefore adopted which produced model structures based to varying degrees on the alpha-bungarotoxin structure. Fourteen different structures were generated in this manner and subsequently used as starting points for refinement using dynamical simulated annealing followed by restrained molecular dynamics. This approach, which combines NMR data and homologous model building, has enabled a family of structures to be proposed for the dimeric molecule. In particular, Phe49 has been identified as possibly playing an important role in dimer formation, this residue in one chain interacting with the corresponding residue in the adjacent chain.     

Do NOE distances contain enough information to assess the relative populations of multi-conformer structures?

Summary The feasibility of determining the relative populations of multi-conformer structures from NOE-derived distances alone is assessed. Without cross-validation of the NOE restraints, any population ratio can be refined to a similar quality of the fit. Complete cross-validation provides a less biased measure of fit and allows the estimation of the correct population ratio when used in conjunction with very tight distance restraints. With the qualitative distance restraints most commonly used in NMR structure determination, cross-validation is unsuccessful in providing the correct answer. Other experimental sources are therefore needed to determine relative populations of multi-conformer structures.To whom correspondence should be addressed.     

Improved reliability,accuracy and quality in automated NMR structure calculation with ARIA

In biological NMR, assignment of NOE cross-peaks and calculation of atomic conformations are critical steps in the determination of reliable high-resolution structures. ARIA is an automated approach that performs NOE assignment and structure calculation in a concomitant manner in an iterative procedure. The log-harmonic shape for distance restraint potential and the Bayesian weighting of distance restraints, recently introduced in ARIA, were shown to significantly improve the quality and the accuracy of determined structures. In this paper, we propose two modifications of the ARIA protocol: (1) the softening of the force field together with adapted hydrogen radii, which is meaningful in the context of the log-harmonic potential with Bayesian weighting, (2) a procedure that automatically adjusts the violation tolerance used in the selection of active restraints, based on the fitting of the structure to the input data sets. The new ARIA protocols were fine-tuned on a set of eight protein targets from the CASD–NMR initiative. As a result, the convergence problems previously observed for some targets was resolved and the obtained structures exhibited better quality. In addition, the new ARIA protocols were applied for the structure calculation of ten new CASD–NMR targets in a blind fashion, i.e. without knowing the actual solution. Even though optimisation of parameters and pre-filtering of unrefined NOE peak lists were necessary for half of the targets, ARIA consistently and reliably determined very precise and highly accurate structures for all cases. In the context of integrative structural biology, an increasing number of experimental methods are used that produce distance data for the determination of 3D structures of macromolecules, stressing the importance of methods that successfully make use of ambiguous and noisy distance data.     

FINGAR: A new genetic algorithm-based method for fitting NMR data

Summary A new NMR refinement method, FINGAR (FIt NMR using a Genetic AlgoRithm), has been developed, which allows one to determine a weighted set of structures that best fits measured NMR-derived data. This method shows appreciable advantages over commonly used refinement methods. FINGAR generates an ensemble of conformations whose average reproduces the experimental NMR-derived restraints. In addition, a statistical importance weight is assigned to each of the conformations in the ensemble. As a result, one is not limited to simply presenting an envelope of sampled conformers. Instead, one can subsequently focus on a select few conformers of high weight. This is critical, because many structural analyses depend on using discrete conformations, not simply averages or ensembles. The genetic algorithm used by FINGAR allows one to simultaneously and reliably fit against many restraints, and to generate solutions which include as many conformations with non-zero weights as are necessary to generate the best fit. An added benefit of FINGAR is that because the time-consuming step in this method needs only to be performed once, in the beginning of the first run, numerous FINGAR simulations can be performed rapidly.     

Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13

Computational methods that produce accurate protein structure models from limited experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. The NMR-assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity, and error rate for protein structure prediction. We describe our approach to predict the structure of these proteins leveraging the Rosetta software suite. Protein structure models were predicted de novo using a two-stage protocol. First, low-resolution models were generated with the Rosetta de novo method guided by nonambiguous nuclear Overhauser effect (NOE) contacts and residual dipolar coupling (RDC) restraints. Second, iterative model hybridization and fragment insertion with the Rosetta comparative modeling method was used to refine and regularize models guided by all ambiguous and nonambiguous NOE contacts and RDCs. Nine out of 16 of the Rosetta de novo models had the correct fold (global distance test total score > 45) and in three cases high-resolution models were achieved (root-mean-square deviation < 3.5 å). We also show that a meta-approach applying iterative Rosetta + NMR refinement on server-predicted models which employed non-NMR-contacts and structural templates leads to substantial improvement in model quality. Integrating these data-assisted refinement strategies with innovative non-data-assisted approaches which became possible in CASP13 such as high precision contact prediction will in the near future enable structure determination for large proteins that are outside of the realm of conventional NMR.     

Improving NMR protein structure quality by Rosetta refinement: a molecular replacement study

The structure of human protein HSPC034 has been determined by both solution nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. Refinement of the NMR structure ensemble, using a Rosetta protocol in the absence of NMR restraints, resulted in significant improvements not only in structure quality, but also in molecular replacement (MR) performance with the raw X-ray diffraction data using MOLREP and Phaser. This method has recently been shown to be generally applicable with improved MR performance demonstrated for eight NMR structures refined using Rosetta (Qian et al., Nature 2007;450:259-264). Additionally, NMR structures of HSPC034 calculated by standard methods that include NMR restraints have improvements in the RMSD to the crystal structure and MR performance in the order DYANA, CYANA, XPLOR-NIH, and CNS with explicit water refinement (CNSw). Further Rosetta refinement of the CNSw structures, perhaps due to more thorough conformational sampling and/or a superior force field, was capable of finding alternative low energy protein conformations that were equally consistent with the NMR data according to the Recall, Precision, and F-measure (RPF) scores. On further examination, the additional MR-performance shortfall for NMR refined structures as compared with the X-ray structure were attributed, in part, to crystal-packing effects, real structural differences, and inferior hydrogen bonding in the NMR structures. A good correlation between a decrease in the number of buried unsatisfied hydrogen-bond donors and improved MR performance demonstrates the importance of hydrogen-bond terms in the force field for improving NMR structures. The superior hydrogen-bond network in Rosetta-refined structures demonstrates that correct identification of hydrogen bonds should be a critical goal of NMR structure refinement. Inclusion of nonbivalent hydrogen bonds identified from Rosetta structures as additional restraints in the structure calculation results in NMR structures with improved MR performance.