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.     

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.     

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     

Complete cross-validation and R-factor calculation of a solid-state NMR derived structure

Cross-validation of a solid-state NMR-derived membrane polypeptide structure is demonstrated. An initial structure has been achieved directly from solid-state NMR derived orientational restraints based on a variety of anisotropic nuclear spin interactions. Refining the molecular structure involves setting up a penalty function that incorporates all available solid-state NMR experimental data and an energy function. A validation method is required to choose the optimal weighting factor for the total penalty function to balance the contribution from the experimental restraints and the energy function. Complete cross-validation has been used to avoid over-fitting the orientational restraints. Such cross-validation involves partitioning of the experimental data into a test set and a working set followed by checking the free R-value during the refinement process. This approach is similar to the method used in crystallography and solution NMR. Optimizing the weighting factor on the penalty function by cross-validation will increase the quality of the refined structure from solid-state NMR data. The complete cross-validation and R-factor calculation is demonstrated using experimental solid-state NMR data from gramicidin A, a monovalent cation channel in lipid bilayers.     

Site-directed parallel spin-labeling and paramagnetic relaxation enhancement in structure determination of membrane proteins by solution NMR spectroscopy

A major challenge for the structure determination of integral membrane proteins by solution NMR spectroscopy is the limited number of NOE restraints in these systems stemming from extensive deuteration. Paramagnetic relaxation enhancement (PRE) by means of nitroxide spin-labels can provide valuable long-range distance information but, in practice, has limits in its application to membrane proteins because spin-labels are often incompletely reduced in highly apolar environments. Using the integral membrane protein OmpA as a model system, we introduce a method of parallel spin-labeling with paramagnetic and diamagnetic labels and show that distances in the range 15-24 Angstroms can be readily determined. The protein was labeled at 11 water-exposed and lipid-covered sites, and 320 PRE distance restraints were measured. The addition of these restraints resulted in significant improvement of the calculated backbone structure of OmpA. Structures of reasonable quality can even be calculated with PRE distance restraints only, i.e., in the absence of NOE distance restraints.     

Direct use of unassigned resonances in NMR structure calculations with proxy residues

We present a method that significantly enhances the robustness of (automated) NMR structure determination by allowing the NOE data corresponding to unassigned NMR resonances to be used directly in the calculations. The unassigned resonances are represented by additional atoms or groups of atoms that have no interaction with the regular protein atoms except through distance restraints. These so-called "proxy" residues can be used to generate NOE-based distance restraints in a similar fashion as for the assigned part of the protein. If sufficient NOE information is available, the restraints are expected to place the proxies at positions close to the correct atoms for the unassigned resonance, which can facilitate subsequent assignment. Convergence can be further improved by supplying additional information about the possible identities of the unassigned resonances. We have implemented this approach in the widely used automated assignment and structure calculation protocols ARIA and CANDID. We find that it significantly increases the robustness of structure calculations with regard to missing assignments and yields structures of higher quality. Our approach is still able to find correctly folded structures with up to 30% randomly missing resonance assignments, and even when only backbone and beta resonances are present! This should be of significant value to NMR-based structural proteomics initiatives.     

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.     

Structure determination of protein-protein complexes using NMR chemical shifts: case of an endonuclease colicin-immunity protein complex

Nuclear magnetic resonance (NMR) spectroscopy provides a range of powerful techniques for determining the structures and the dynamics of proteins. The high-resolution determination of the structures of protein-protein complexes, however, is still a challenging problem for this approach, since it can normally provide only a limited amount of structural information at protein-protein interfaces. We present here the determination using NMR chemical shifts of the structure (PDB code 2K5X) of the cytotoxic endonuclease domain from bacterial toxin colicin (E9) in complex with its cognate immunity protein (Im9). In order to achieve this result, we introduce the CamDock method, which combines a flexible docking procedure with a refinement that exploits the structural information provided by chemical shifts. The results that we report thus indicate that chemical shifts can be used as structural restraints for the determination of the conformations of protein complexes that are difficult to obtain by more standard NMR approaches.     

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.     

Explicit treatment of force contribution from alignment tensor using overdetermined linear equations and its application in NMR structure determination

Residual dipolar coupling (RDC) provides valuable information about the orientation of each internuclear vector in a macromolecule with respect to the static magnetic field. However, structure determination utilizing RDC still remains challenging without additional restraints such as NOE. In this context, a novel approach has been developed to efficiently extract structural information from RDC by successive application of singular value decomposition (SVD) method in the course of NMR structure determination. Force contribution from the alignment tensor is rigorously formulated in the context of SVD, and assessments have been made to verify its numerical accuracy. The efficacy of this approach is illustrated by showing that RDC restraints alone can restore a distorted beta-hairpin to native-like structure using the replica-exchange molecular dynamics simulations.     

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.     

Complementary segmental labeling of large RNAs: economic preparation and simplified NMR spectra for measurement of more RDCs

NMR structure determination of large RNAs is often restricted by limited RDC information caused by chemical shift degeneracy. We established a general, time- and cost-effective methodology for the preparation of 13C/15N complementary labeled RNAs from a single plasmid. Applying this method to the 25 kDa BC1-DTE RNA, we were able to resolve severe chemical shift degeneracy, thereby almost doubling the number of RDC restraints in comparison to the conventional 13C,15N uniform-labeled RNA.     

Determination of an ensemble of structures representing the denatured state of the bovine acyl-coenzyme a binding protein

The denatured state of a protein contains important information about the determinants of the folding process. By combining site-directed spin-labeling NMR experiments and restrained computer simulations, we have determined ensembles of conformations that represent the denatured state of the bovine acyl-coenzyme A binding protein (ACBP) at three different concentrations of guanidine hydrochloride. As the experimentally determined distance information corresponds to weighted averages over a broad ensemble of structures, we applied the experimental restraints to a system of noninteracting replicas of the protein by using a Monte Carlo sampling scheme. This procedure permits us to sample ensembles of conformations that are compatible with the experimental data and thus to obtain information regarding the distribution of structures in the denatured state. Our results show that the denatured state of ACBP is highly heterogeneous. The high sensitivity of the computational method that we present, however, enabled us to identify long-range interactions between two regions, located near the N- and C-termini, that include both native and non-native elements. The preferential formation of these contacts suggests that the sequence-dependent patterns of helical propensity and hydrophobicity are important determinants of the structure in the denatured state of ACBP.     

Structure calculation from unambiguous long-range amide and methyl 1H-1H distance restraints for a microcrystalline protein with MAS solid-state NMR spectroscopy

Magic-angle spinning (MAS) solid-state NMR becomes an increasingly important tool for the determination of structures of membrane proteins and amyloid fibrils. Extensive deuteration of the protein allows multidimensional experiments with exceptionally high sensitivity and resolution to be obtained. Here we present an experimental strategy to measure highly unambiguous spatial correlations for distances up to 13 ?. Two complementary three-dimensional experiments, or alternatively a four-dimensional experiment, yield highly unambiguous cross-peak assignments, which rely on four encoded chemical shift dimensions. Correlations to residual aliphatic protons are accessible via synchronous evolution of the (15)N and (13)C chemical shifts, which encode valuable amide-methyl distance restraints. On average, we obtain six restraints per residue. Importantly, 50% of all restraints correspond to long-range distances between residues i and j with |i - j| > 5, which are of particular importance in structure calculations. Using ARIA, we calculate a high-resolution structure for the microcrystalline 7.2 kDa α-spectrin SH3 domain with a backbone precision of ～1.1 ?.     

Solution Structure of a Lanthanide-binding DNA Aptamer Determined Using High Quality pseudocontact shift restraints

In this contribution we report the high-resolution NMR structure of a recently identified lanthanide-binding aptamer (LnA). We demonstrate that the rigid lanthanide binding by LnA allows for the measurement of anisotropic paramagnetic NMR restraints which to date remain largely inaccessible for nucleic acids. One type of such restraints - pseudocontact shifts (PCS) induced by four different paramagnetic lanthanides - was extensively used throughout the current structure determination study and the measured PCS turned out to be exceptionally well reproduced by the final aptamer structure. This finding opens the perspective for a broader application of paramagnetic effects in NMR studies of nucleic acids through the transplantation of the binding site found in LnA into other DNA/RNA systems.     

Impact of 15N R2/R1 relaxation restraints on molecular size, shape, and bond vector orientation for NMR protein structure determination with sparse distance restraints

(15)N R(2)/R(1) relaxation data contain information on molecular shape and size as well as on bond vector orientations relative to the diffusion tensor. Since the diffusion tensor can be directly calculated from the molecular coordinates, direct inclusion of (15)N R(2)/R(1) restraints in NMR structure calculations without any a priori assumptions is possible. Here we show that (15)N R(2)/R(1) restraints are particularly valuable when only sparse distance restraints are available. Using three examples of proteins of varying size, namely, GB3 (56 residues), ubiquitin (76 residues), and the N-terminal domain of enzyme I (EIN, 249 residues), we show that incorporation of (15)N R(2)/R(1) restraints results in large and significant increases in coordinate accuracy that can make the difference between being able or unable to determine an approximate global fold. For GB3 and ubiquitin, good coordinate accuracy was obtained using only backbone hydrogen-bond restraints supplemented by (15)N R(2)/R(1) relaxation restraints. For EIN, the global fold could be determined using sparse nuclear Overhauser enhancement (NOE) distance restraints involving only NH and methyl groups in conjunction with (15)N R(2)/R(1) restraints. These results are of practical significance in the study of larger and more complex systems, where the increasing spectral complexity and number of chemical shift degeneracies reduce the number of unambiguous NOE assignments that can be readily obtained, resulting in progressively reduced NOE coverage as the size of the protein increases.     

Characterization of the conformational equilibrium between the two major substates of RNase A using NMR chemical shifts

Following the recognition that NMR chemical shifts can be used for protein structure determination, rapid advances have recently been made in methods for extending this strategy for proteins and protein complexes of increasing size and complexity. A remaining major challenge is to develop approaches to exploit the information contained in the chemical shifts about conformational fluctuations in native states of proteins. In this work we show that it is possible to determine an ensemble of conformations representing the free energy surface of RNase A using chemical shifts as replica-averaged restraints in molecular dynamics simulations. Analysis of this surface indicates that chemical shifts can be used to characterize the conformational equilibrium between the two major substates of this protein.