Refinement of NMR structures using implicit solvent and advanced sampling techniques

NMR biomolecular structure calculations exploit simulated annealing methods for conformational sampling and require a relatively high level of redundancy in the experimental restraints to determine quality three-dimensional structures. Recent advances in generalized Born (GB) implicit solvent models should make it possible to combine information from both experimental measurements and accurate empirical force fields to improve the quality of NMR-derived structures. In this paper, we study the influence of implicit solvent on the refinement of protein NMR structures and identify an optimal protocol of utilizing these improved force fields. To do so, we carry out structure refinement experiments for model proteins with published NMR structures using full NMR restraints and subsets of them. We also investigate the application of advanced sampling techniques to NMR structure refinement. Similar to the observations of Xia et al. (J.Biomol. NMR 2002, 22, 317-331), we find that the impact of implicit solvent is rather small when there is a sufficient number of experimental restraints (such as in the final stage of NMR structure determination), whether implicit solvent is used throughout the calculation or only in the final refinement step. The application of advanced sampling techniques also seems to have minimal impact in this case. However, when the experimental data are limited, we demonstrate that refinement with implicit solvent can substantially improve the quality of the structures. In particular, when combined with an advanced sampling technique, the replica exchange (REX) method, near-native structures can be rapidly moved toward the native basin. The REX method provides both enhanced sampling and automatic selection of the most native-like (lowest energy) structures. An optimal protocol based on our studies first generates an ensemble of initial structures that maximally satisfy the available experimental data with conventional NMR software using a simplified force field and then refines these structures with implicit solvent using the REX method. We systematically examine the reliability and efficacy of this protocol using four proteins of various sizes ranging from the 56-residue B1 domain of Streptococcal protein G to the 370-residue Maltose-binding protein. Significant improvement in the structures was observed in all cases when refinement was based on low-redundancy restraint data. The proposed protocol is anticipated to be particularly useful in early stages of NMR structure determination where a reliable estimate of the native fold from limited data can significantly expedite the overall process. This refinement procedure is also expected to be useful when redundant experimental data are not readily available, such as for large multidomain biomolecules and in solid-state NMR structure determination.     

Completely automated, highly error-tolerant macromolecular structure determination from multidimensional nuclear overhauser enhancement spectra and chemical shift assignments

The major rate-limiting step in high-throughput NMR protein structure determination involves the calculation of a reliable initial fold, the elimination of incorrect nuclear Overhauser enhancement (NOE) assignments, and the resolution of NOE assignment ambiguities. We present a robust approach to automatically calculate structures with a backbone coordinate accuracy of 1.0-1.5 A from datasets in which as much as 80% of the long-range NOE information (i.e., between residues separated by more than five positions in the sequence) is incorrect. The current algorithm differs from previously published methods in that it has been expressly designed to ensure that the results from successive cycles are not biased by the global fold of structures generated in preceding cycles. Consequently, the method is highly error tolerant and is not easily funnelled down an incorrect path in either three-dimensional structure or NOE assignment space. The algorithm incorporates three main features: a linear energy function representation of the NOE restraints to allow maximization of the number of simultaneously satisfied restraints during the course of simulated annealing; a method for handling the presence of multiple possible assignments for each NOE cross-peak which avoids local minima by treating each possible assignment as if it were an independent restraint; and a probabilistic method to permit both inactivation and reactivation of all NOE restraints on the fly during the course of simulated annealing. NOE restraints are never removed permanently, thereby significantly reducing the likelihood of becoming trapped in a false minimum of NOE assignment space. The effectiveness of the algorithm is demonstrated using completely automatically peak-picked experimental NOE data from two proteins: interleukin-4 (136 residues) and cyanovirin-N (101 residues). The limits of the method are explored using simulated data on the 56-residue B1 domain of Streptococcal protein G.     

De novo determination of protein backbone structure from residual dipolar couplings using Rosetta

As genome-sequencing projects rapidly increase the database of protein sequences, the gap between known sequences and known structures continues to grow exponentially, increasing the demand to accelerate structure determination methods. Residual dipolar couplings (RDCs) are an attractive source of experimental restraints for NMR structure determination, particularly rapid, high-throughput methods, because they yield both local and long-range orientational information and can be easily measured and assigned once the backbone resonances of a protein have been assigned. While very extensive RDC data sets have been used to determine the structure of ubiquitin, it is unclear to what extent such methods will generalize to larger proteins with less complete data sets. Here we incorporate experimental RDC restraints into Rosetta, an ab initio structure prediction method, and demonstrate that the combined algorithm provides a general method for de novo determination of a variety of protein folds from RDC data. Backbone structures for multiple proteins up to approximately 125 residues in length and spanning a range of topological complexities are rapidly and reproducibly generated using data sets that are insufficient in isolation to uniquely determine the protein fold de novo, although ambiguities and errors are observed for proteins with symmetry about an axis of the alignment tensor. The models generated are not high-resolution structures completely defined by experimental data but are sufficiently accurate to accelerate traditional high-resolution NMR structure determination and provide structure-based functional insights.     

Structure determination of a membrane protein in proteoliposomes

An NMR method for determining the three-dimensional structures of membrane proteins in proteoliposomes is demonstrated by determining the structure of MerFt, the 60-residue helix-loop-helix integral membrane core of the 81-residue mercury transporter MerF. The method merges elements of oriented sample (OS) solid-state NMR and magic angle spinning (MAS) solid-state NMR techniques to measure orientation restraints relative to a single external axis (the bilayer normal) from individual residues in a uniformly (13)C/(15)N labeled protein in unoriented liquid crystalline phospholipid bilayers. The method relies on the fast (>10(5) Hz) rotational diffusion of membrane proteins in bilayers to average the static chemical shift anisotropy and heteronuclear dipole-dipole coupling powder patterns to axially symmetric powder patterns with reduced frequency spans. The frequency associated with the parallel edge of such motionally averaged powder patterns is exactly the same as that measured from the single line resonance in the spectrum of a stationary sample that is macroscopically aligned parallel to the direction of the applied magnetic field. All data are collected on unoriented samples undergoing MAS. Averaging of the homonuclear (13)C/(13)C dipolar couplings, by MAS of the sample, enables the use of uniformly (13)C/(15)N labeled proteins, which provides enhanced sensitivity through direct (13)C detection as well as the use of multidimensional MAS solid-state NMR methods for resolving and assigning resonances. The unique feature of this method is the measurement of orientation restraints that enable the protein structure and orientation to be determined in unoriented proteoliposomes.     

Calculating protein structures directly from anisotropic spin interaction constraints

Protein structure determination by solid-state NMR of aligned samples relies on the fundamental characteristics of the anisotropic nuclear spin interactions present in isotopically labeled proteins. Progress in the implementation of algorithms that calculate protein structures from the orientational constraints in the chemical shift and heteronuclear dipolar coupling interactions is described using both simulated and experimental data.     

CABS‐NMR—De novo tool for rapid global fold determination from chemical shifts,residual dipolar couplings and sparse methyl‐methyl noes

Recent development of nuclear magnetic resonance (NMR) techniques provided new types of structural restraints that can be successfully used in fast and low‐cost global protein fold determination. Here, we present CABS‐NMR, an efficient protein modeling tool, which takes advantage of such structural restraints. The restraints are converted from original NMR data to fit the coarse grained protein representation of the C‐Alpha‐Beta‐Side‐group (CABS) algorithm. CABS is a Monte Carlo search algorithm that uses a knowledge‐based force field. Its versatile structure enables a variety of protein‐modeling protocols, including purely de novo folding, folding guided by restraints derived from template structures or, structure assembly based on experimental data. In particular, CABS‐NMR uses the distance and angular restraints set derived from various NMR experiments. This new modeling technique was successfully tested in structure determination of 10 globular proteins of size up to 216 residues, for which sparse NMR data were available. Additional detailed analysis was performed for a S100A1 protein. Namely, we successfully predicted Nuclear Overhauser Effect signals on the basis of low‐energy structures obtained from chemical shifts by CABS‐NMR. It has been observed that utility of chemical shifts and other types of experimental data (i.e. residual dipolar couplings and methyl‐methyl Nuclear Overhauser Effect signals) in the presented modeling pipeline depends mainly on size of a protein and complexity of its topology. In this work, we have provided tools for either post‐experiment processing of various kinds of NMR data or fast and low‐cost structural analysis in the still challenging field of new fold predictions. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

3D structure determination of the Crh protein from highly ambiguous solid-state NMR restraints

In a wide variety of proteins, insolubility presents a challenge to structural biology, as X-ray crystallography and liquid-state NMR are unsuitable. Indeed, no general approach is available as of today for studying the three-dimensional structures of membrane proteins and protein fibrils. We here demonstrate, at the example of the microcrystalline model protein Crh, how high-resolution 3D structures can be derived from magic-angle spinning solid-state NMR distance restraints for fully labeled protein samples. First, we show that proton-mediated rare-spin correlation spectra, as well as carbon-13 spin diffusion experiments, provide enough short, medium, and long-range structural restraints to obtain high-resolution structures of this 2 x 10.4 kDa dimeric protein. Nevertheless, the large number of 13C/15N spins present in this protein, combined with solid-state NMR line widths of about 0.5-1 ppm, induces substantial ambiguities in resonance assignments, preventing 3D structure determination by using distance restraints uniquely assigned on the basis of their chemical shifts. In the second part, we thus demonstrate that an automated iterative assignment algorithm implemented in a dedicated solid-state NMR version of the program ARIA permits to resolve the majority of ambiguities and to calculate a de novo 3D structure from highly ambiguous solid-state NMR data, using a unique fully labeled protein sample. We present, using distance restraints obtained through the iterative assignment process, as well as dihedral angle restraints predicted from chemical shifts, the 3D structure of the fully labeled Crh dimer refined at a root-mean-square deviation of 1.33 A.     

Membrane orientation of the Na,K-ATPase regulatory membrane protein CHIF determined by solid-state NMR

Corticosteroid hormone-induced factor (CHIF) is a major regulatory subunit of the Na,K-ATPase, and a member of an evolutionarily conserved family of membrane proteins that regulate the function of the enzyme complex in a tissue-specific and physiological-state-specific manner. Here we present the structure of CHIF oriented in the membrane, determined by solid-state NMR orientation-dependent restraints. Because CHIF adopts a similar structure in lipid micelles and bilayers, it is possible to assign the solid-state NMR spectrum measured for (15)N-labeled CHIF in oriented bilayers from the structure determined in micelles, to obtain the global orientation of the protein in the membrane.     

Protein structure prediction: combining de novo modeling with sparse experimental data

Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.     

High-field NMR studies of molecular recognition and structure-function relationships in antimicrobial piscidins at the water-lipid bilayer interface

High magnetic field solid-state NMR was performed on amphipathic cationic antimicrobial peptides from fish to characterize their secondary structure and orientation in hydrated phospholipid bilayers. High-resolution distance and orientational restraints on 13C- and 15N-labeled amidated piscidins 1 and 3 provided site-specific information establishing alpha-helicity and an orientation parallel to the membrane surface. Few membrane-bound natural peptides with this topology have been structurally studied at high resolution in the presence of hydrated lipid bilayers. This orientation was foreseen since the partitioning of amphipathic cationic antimicrobial peptides at the water-bilayer interface allows for favorable peptide-lipid interactions, and it may be related to the mechanism of action. The enhanced resolution obtained at 900 MHz evidences a determinant advantage of ultra-high-field NMR for the structural determination of multiple-labeled peptides and proteins.     

Two-Dimensional Solid-State NMR Spectroscopy: New Possibilities for the Investigation of the Structure and Dynamics of Solid Polymers [New Analytical Methods (38)]

NMR spectroscopy is an effective method not only for examining liquid samples but also for characterizing molecular sturcture, order and dynamics in amorphous and ordered solids. Recent developments in the area of solid-state NMR spectroscopy span from model-dependent studies of conventional one-dimensional spectra to the more definitive two-dimensional (2D) spectra which provide more specific information. For example, with 2D-NMR spectroscopy it is possible to determine the orientational distribution functions of molecular segments in drawn polymers and to distinguish different mechanisms of complex molecular motions. Following an introduction to basic NMR spectroscopy, an overview of the current state-of-the-art of 2D methods in solid-state NMR spectroscopy is presented and demonstrated with selected examples.     

Refinement of multidomain protein structures by combination of solution small-angle X-ray scattering and NMR data

Determination of the 3D structures of multidomain proteins by solution NMR methods presents a number of unique challenges related to their larger molecular size and the usual scarcity of constraints at the interdomain interface, often resulting in a decrease in structural accuracy. In this respect, experimental information from small-angle scattering of X-ray radiation in solution (SAXS) presents a suitable complement to the NMR data, as it provides an independent constraint on the overall molecular shape. A computational procedure is described that allows incorporation of such SAXS data into the mainstream high-resolution macromolecular structure refinement. The method is illustrated for a two-domain 177-amino-acid protein, gammaS crystallin, using an experimental SAXS data set fitted at resolutions from approximately 200 A to approximately 30 A. Inclusion of these data during structure refinement decreases the backbone coordinate root-mean-square difference between the derived model and the high-resolution crystal structure of a 54% homologous gammaB crystallin from 1.96 +/- 0.07 A to 1.31 +/- 0.04 A. Combining SAXS data with NMR restraints can be accomplished at a moderate computational expense and is expected to become useful for multidomain proteins, multimeric assemblies, and tight macromolecular complexes.     

On the use of orientational restraints and symmetry corrections in alchemical free energy calculations

Alchemical free energy calculations are becoming a useful tool for calculating absolute binding free energies of small molecule ligands to proteins. Here, we find that the presence of multiple metastable ligand orientations can cause convergence problems when distance restraints alone are used. We demonstrate that the use of orientational restraints can greatly accelerate the convergence of these calculations. However, even with this acceleration, we find that sufficient sampling requires substantially longer simulations than are used in many published protocols. To further accelerate convergence, we introduce a new method of configuration space decomposition by orientation which reduces required simulation lengths by at least a factor of 5 in the cases examined. Our method is easily parallelizable, well suited for cases where a ligand cocrystal structure is not available, and can utilize initial orientations generated by docking packages.     

Methyl proton contacts obtained using heteronuclear through-bond transfers in solid-state NMR spectroscopy

A two-dimensional proton-mediated carbon-carbon correlation experiment that relies on through-bond heteronuclear magnetization transfers is demonstrated in the context of solid-state NMR of proteins. This new experiment, dubbed J-CHHC by analogy to the previously developed dipolar CHHC techniques, is shown to provide selective and sensitive correlations in the methyl region of 2D spectra of crystalline organic compounds. The method is then demonstrated on a microcrystalline sample of the dimeric protein Crh (2 x 10.4 kDa). A total of 34 new proton-proton contacts involving side-chain methyl groups were observed in the J-CHHC spectrum, which had not been observed with the conventional experiment. The contacts were then used as additional distance restraints for the 3D structure determination of this microcrystalline protein. Upon addition of these new distance restraints, which are in large part located in the hydrophobic core of the protein, the root-mean-square deviation with respect to the X-ray structure of the backbone atom coordinates of the 10 best conformers of the new ensemble of structures is reduced from 1.8 to 1.1 A.     

Ensemble approach for NMR structure refinement against (1)H paramagnetic relaxation enhancement data arising from a flexible paramagnetic group attached to a macromolecule

Paramagnetic relaxation enhancement (PRE) measurements on (1)H nuclei have the potential to play an important role in NMR structure determination of macromolecules by providing unique long-range (10-35 A) distance information. Recent methodological advances for covalently attaching paramagnetic groups at specific sites on both proteins and nucleic acids have permitted the application of the PRE to various biological macromolecules. However, because artificially introduced paramagnetic groups are exposed to solvent and linked to the macromolecule by several freely rotatable bonds, they are intrinsically flexible. This renders conventional back-calculation of the (1)H-PRE using a single-point representation inaccurate, thereby severely limiting the utility of the (1)H-PRE as a tool for structure refinement. To circumvent these limitations, we have developed a theoretical framework and computational strategy with which to accurately back-calculate (1)H-PREs arising from flexible paramagnetic groups attached to macromolecules. In this scheme, the (1)H-PRE is calculated using a modified Solomon-Bloembergen equation incorporating a "model-free" formalism, based on a multiple-structure representation of the paramagnetic group in simulated annealing calculations. The ensemble approach for (1)H-PRE back-calculation was examined using several SRY/DNA complexes incorporating dT-EDTA-Mn(2+) at three distinct sites in the DNA, permitting a large data set comprising 435 experimental backbone and side-chain (1)H-PREs to be obtained in a straightforward manner from 2D through-bond correlation experiments. Calculations employing complete cross-validation demonstrate that the ensemble representation provides a means to accurately utilize backbone and side-chain (1)H-PRE data arising from a flexible paramagnetic group in structure refinement. The results of (1)H-PRE based refinement, in conjunction with previously obtained NMR restraints, indicate that significant gains in accuracy can be readily obtained. This is particularly significant in the case of macromolecular complexes where intermolecular translational restraints derived from nuclear Overhauser enhancement data may be limited.     

4D solid-state NMR for protein structure determination

Solid-state NMR offers the chance to extend structural studies to proteins that are otherwise difficult to study at atomic resolution, such as protein fibrils, membrane proteins or poorly diffracting crystals. As two-dimensional spatial correlation NMR spectra of proteins suffer from severe resonance overlap, we analyze in this perspective article the potential of higher-dimensional (3D and 4D) proton-detected experiments, which have an increased number of identifiable and assignable distance restraints for solid-state structural studies. We discuss practical considerations for the NMR measurements and the preparation of suitable protein samples and show results of structure calculations from 4D solid-state NMR spectra.