A refinement protocol to determine structure,topology, and depth of insertion of membrane proteins using hybrid solution and solid-state NMR restraints

To fully describe the fold space and ultimately the biological function of membrane proteins, it is necessary to determine the specific interactions of the protein with the membrane. This property of membrane proteins that we refer to as structural topology cannot be resolved using X-ray crystallography or solution NMR alone. In this article, we incorporate into XPLOR-NIH a hybrid objective function for membrane protein structure determination that utilizes solution and solid-state NMR restraints, simultaneously defining structure, topology, and depth of insertion. Distance and angular restraints obtained from solution NMR of membrane proteins solubilized in detergent micelles are combined with backbone orientational restraints (chemical shift anisotropy and dipolar couplings) derived from solid-state NMR in aligned lipid bilayers. In addition, a supplementary knowledge-based potential, E _z (insertion depth potential), is used to ensure the correct positioning of secondary structural elements with respect to a virtual membrane. The hybrid objective function is minimized using a simulated annealing protocol implemented into XPLOR-NIH software for general use. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Solution NMR structure of the 30S ribosomal protein S28E from Pyrococcus horikoshii

We report NMR assignments and solution structure of the 71-residue 30S ribosomal protein S28E from the archaean Pyrococcus horikoshii, target JR19 of the Northeast Structural Genomics Consortium. The structure, determined rapidly with the aid of automated backbone resonance assignment (AutoAssign) and automated structure determination (AutoStructure) software, is characterized by a four-stranded beta-sheet with a classic Greek-key topology and an oligonucleotide/oligosaccharide beta-barrel (OB) fold. The electrostatic surface of S28E exhibits positive and negative patches on opposite sides, the former constituting a putative binding site for RNA. The 13 C-terminal residues of the protein contain a consensus sequence motif constituting the signature of the S28E protein family. Surprisingly, this C-terminal segment is unstructured in solution.     

Automated structure determination from NMR spectra

Automated methods for protein structure determination by NMR have increasingly gained acceptance and are now widely used for the automated assignment of distance restraints and the calculation of three-dimensional structures. This review gives an overview of the techniques for automated protein structure analysis by NMR, including both NOE-based approaches and methods relying on other experimental data such as residual dipolar couplings and chemical shifts, and presents the FLYA algorithm for the fully automated NMR structure determination of proteins that is suitable to substitute all manual spectra analysis and thus overcomes a major efficiency limitation of the NMR method for protein structure determination.     

KUJIRA,a package of integrated modules for systematic and interactive analysis of NMR data directed to high-throughput NMR structure studies

The recent expansion of structural genomics has increased the demands for quick and accurate protein structure determination by NMR spectroscopy. The conventional strategy without an automated protocol can no longer satisfy the needs of high-throughput application to a large number of proteins, with each data set including many NMR spectra, chemical shifts, NOE assignments, and calculated structures. We have developed the new software KUJIRA, a package of integrated modules for the systematic and interactive analysis of NMR data, which is designed to reduce the tediousness of organizing and manipulating a large number of NMR data sets. In combination with CYANA, the program for automated NOE assignment and structure determination, we have established a robust and highly optimized strategy for comprehensive protein structure analysis. An application of KUJIRA in accordance with our new strategy was carried out by a non-expert in NMR structure analysis, demonstrating that the accurate assignment of the chemical shifts and a high-quality structure of a small protein can be completed in a few weeks. The high completeness of the chemical shift assignment and the NOE assignment achieved by the systematic analysis using KUJIRA and CYANA led, in practice, to increased reliability of the determined structure.     

A novel strategy for NMR resonance assignment and protein structure determination

The quality of protein structures determined by nuclear magnetic resonance (NMR) spectroscopy is contingent on the number and quality of experimentally-derived resonance assignments, distance and angular restraints. Two key features of protein NMR data have posed challenges for the routine and automated structure determination of small to medium sized proteins; (1) spectral resolution – especially of crowded nuclear Overhauser effect spectroscopy (NOESY) spectra, and (2) the reliance on a continuous network of weak scalar couplings as part of most common assignment protocols. In order to facilitate NMR structure determination, we developed a semi-automated strategy that utilizes non-uniform sampling (NUS) and multidimensional decomposition (MDD) for optimal data collection and processing of selected, high resolution multidimensional NMR experiments, combined it with an ABACUS protocol for sequential and side chain resonance assignments, and streamlined this procedure to execute structure and refinement calculations in CYANA and CNS, respectively. Two graphical user interfaces (GUIs) were developed to facilitate efficient analysis and compilation of the data and to guide automated structure determination. This integrated method was implemented and refined on over 30 high quality structures of proteins ranging from 5.5 to 16.5 kDa in size.     

1H, 13C, and 15N resonance assignments of human phosphohistidine phosphatase 1 (PHPT1)

Phosphohistidine phosphatase 1 (PHPT1) is the first protein histidine phosphatase identified in vertebrates. The NMR assignments of human PHPT1 are essential for solution structure determination and NMR study of the protein interactions of PHPT1 with its potential substrates.     

Rapid,robotic, small‐scale protein production for NMR screening and structure determination

Three‐dimensional protein structure determination is a costly process due in part to the low success rate within groups of potential targets. Conventional validation methods eliminate the vast majority of proteins from further consideration through a time‐consuming succession of screens for expression, solubility, purification, and folding. False negatives at each stage incur unwarranted reductions in the overall success rate. We developed a semi‐automated protocol for isotopically‐labeled protein production using the Maxwell‐16, a commercially available bench top robot, that allows for single‐step target screening by 2D NMR. In the span of a week, one person can express, purify, and screen 48 different ¹⁵N‐labeled proteins, accelerating the validation process by more than 10‐fold. The yield from a single channel of the Maxwell‐16 is sufficient for acquisition of a high‐quality 2D ¹H‐¹⁵N‐HSQC spectrum using a 3‐mm sample cell and 5‐mm cryogenic NMR probe. Maxwell‐16 screening of a control group of proteins reproduced previous validation results from conventional small‐scale expression screening and large‐scale production approaches currently employed by our structural genomics pipeline. Analysis of 18 new protein constructs identified two potential structure targets that included the second PDZ domain of human Par‐3. To further demonstrate the broad utility of this production strategy, we solved the PDZ2 NMR structure using [U‐¹⁵N,¹³C] protein prepared using the Maxwell‐16. This novel semi‐automated protein production protocol reduces the time and cost associated with NMR structure determination by eliminating unnecessary screening and scale‐up steps.     

Structure-based protein NMR assignments using native structural ensembles

An important step in NMR protein structure determination is the assignment of resonances and NOEs to corresponding nuclei. Structure-based assignment (SBA) uses a model structure ("template") for the target protein to expedite this process. Nuclear vector replacement (NVR) is an SBA framework that combines multiple sources of NMR data (chemical shifts, RDCs, sparse NOEs, amide exchange rates, TOCSY) and has high accuracy when the template is close to the target protein's structure (less than 2 A backbone RMSD). However, a close template may not always be available. We extend the circle of convergence of NVR for distant templates by using an ensemble of structures. This ensemble corresponds to the low-frequency perturbations of the given template and is obtained using normal mode analysis (NMA). Our algorithm assigns resonances and sparse NOEs using each of the structures in the ensemble separately, and aggregates the results using a voting scheme based on maximum bipartite matching. Experimental results on human ubiquitin, using four distant template structures show an increase in the assignment accuracy. Our algorithm also improves the robustness of NVR with respect to structural noise. We provide a confidence measure for each assignment using the percentage of the structures that agree on that assignment. We use this measure to assign a subset of the peaks with even higher accuracy. We further validate our algorithm on data for two additional proteins with NVR. We then show the general applicability of our approach by applying our NMA ensemble-based voting scheme to another SBA tool, MARS. For three test proteins with corresponding templates, including the 370-residue maltose binding protein, we increase the number of reliable assignments made by MARS. Finally, we show that our voting scheme is sound and optimal, by proving that it is a maximum likelihood estimator of the correct assignments.     

Automated Protein NMR Structure Determination Using Wavelet De-noised NOESY Spectra

A major time-consuming step of protein NMR structure determination is the generation of reliable NOESY cross peak lists which usually requires a significant amount of manual interaction. Here we present a new algorithm for automated peak picking involving wavelet de-noised NOESY spectra in a process where the identification of peaks is coupled to automated structure determination. The core of this method is the generation of incremental peak lists by applying different wavelet de-noising procedures which yield peak lists of a different noise content. In combination with additional filters which probe the consistency of the peak lists, good convergence of the NOESY-based automated structure determination could be achieved. These algorithms were implemented in the context of the ARIA software for automated NOE assignment and structure determination and were validated for a polysulfide-sulfur transferase protein of known structure. The procedures presented here should be commonly applicable for efficient protein NMR structure determination and automated NMR peak picking. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Solution structure of the c-terminal dimerization domain of SARS coronavirus nucleocapsid protein solved by the SAIL-NMR method

The C-terminal domain (CTD) of the severe acute respiratory syndrome coronavirus (SARS-CoV) nucleocapsid protein (NP) contains a potential RNA-binding region in its N-terminal portion and also serves as a dimerization domain by forming a homodimer with a molecular mass of 28 kDa. So far, the structure determination of the SARS-CoV NP CTD in solution has been impeded by the poor quality of NMR spectra, especially for aromatic resonances. We have recently developed the stereo-array isotope labeling (SAIL) method to overcome the size problem of NMR structure determination by utilizing a protein exclusively composed of stereo- and regio-specifically isotope-labeled amino acids. Here, we employed the SAIL method to determine the high-quality solution structure of the SARS-CoV NP CTD by NMR. The SAIL protein yielded less crowded and better resolved spectra than uniform ¹³C and ¹⁵N labeling, and enabled the homodimeric solution structure of this protein to be determined. The NMR structure is almost identical with the previously solved crystal structure, except for a disordered putative RNA-binding domain at the N-terminus. Studies of the chemical shift perturbations caused by the binding of single-stranded DNA and mutational analyses have identified the disordered region at the N-termini as the prime site for nucleic acid binding. In addition, residues in the β-sheet region also showed significant perturbations. Mapping of the locations of these residues onto the helical model observed in the crystal revealed that these two regions are parts of the interior lining of the positively charged helical groove, supporting the hypothesis that the helical oligomer may form in solution.     

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.     

Hypothetical protein AF2241 from Archaeoglobus fulgidus adopts a cyclophilin-like fold

AF2241 is a hypothetical protein from Archaeoglobus fulgidus and it belongs to the PFam domain of unknown function 369 (DUF369). NMR structural determination reveals that AF2241 adopts a cyclophilin-like fold, with a β-barrel core composed of eight β-strands, one α-helix, and one 3₁₀ helix located at each end of the barrel. The protein displays a high structural similarity to TM1367, another member of DUF369 whose structure has been determined recently by X-ray crystallography. Structural similarity search shows that AF2241 also has a high similarity to human cyclophilin A, however, sequence alignment and electrostatic potential analysis reveal that the residues in the PPIase catalytic site of human cyclophilin A are not conserved in AF2241 or TM1367. Instead, a putative active site of AF2241 maps to a negatively charged pocket composed of 9 conserved residues. Our results suggest that although AF2241 adopts the same fold as the human cyclophilin A, it may have distinct biological function. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A computational method for NMR-constrained protein threading.

Protein threading provides an effective method for fold recognition and backbone structure prediction. But its application is currently limited due to its level of prediction accuracy and scope of applicability. One way to significantly improve its usefulness is through the incorporation of underconstrained (or partial) NMR data. It is well known that the NMR method for protein structure determination applies only to small proteins and that its effectiveness decreases rapidly as the protein mass increases beyond about 30 kD. We present, in this paper, a computational framework for applying underconstrained NMR data (that alone are insufficient for structure determination) as constraints in protein threading and also in all-atom model construction. In this study, we consider both secondary structure assignments from chemical shifts and NOE distance restraints. Our results have shown that both secondary structure assignments and a small number of long-range NOEs can significantly improve the threading quality in both fold recognition and threading-alignment accuracy, and can possibly extend threading's scope of applicability from homologs to analogs. An accurate backbone structure generated by NMR-constrained threading can then provide a great amount of structural information, equivalent to that provided by many NMR data; and hence can help reduce the number of NMR data typically required for an accurate structure determination. This new technique can potentially accelerate current NMR structure determination processes and possibly expand NMR's capability to larger proteins.     

核磁共振波谱应用于结构生物学的研究进展

综述了核磁共振波谱在结构生物学研究中的进展。在溶液中测定生物大分子的结构,分子大小的限制正被减少,尽管新结构的测定仍然需要付出比较大的努力。核磁共振是一个有效的手段,可用于研究在许多细胞过程中存在的弱的或者瞬态的蛋白质-蛋白质相互作用。结构的柔性在蛋白质分子功能中起了中心作用。由于最近方法学的发展,使NMR可以表征蛋白质的动力学,从而可以对分子机制有新的认识。核磁共振波谱可以在原子分辨率下表征无序的蛋白质系统,可以研究折叠路径。跨膜蛋白在细胞中起了关键作用,这使它们成为药物的靶标。应用液体和固体核磁共振技术已经成功测定了跨膜蛋白质的结构。     

Heteronuclear three-dimensional NMR spectroscopy of the inflammatory protein C5a

The utility of three-dimensional heteronuclear NMR spectroscopy for the assignment of 1H and 15N resonances of the inflammatory protein C5a (MW 8500), uniformly labeled with 15N, is demonstrated at a protein concentration of 0.7 mM. It is shown that dramatic simplification of the 2D nuclear Overhauser effect spectrum (NOESY) is obtained by editing with respect to the frequency of the 15N heteronucleus in a third dimension. The improved resolution in the 3D experiment largely facilitates the assignment of protein NMR spectra and allows for the determination of distance constraints from otherwise overlapping NOE cross peaks for purposes of 3D structure determination. The results show that 15N heteronuclear 3D NMR can facilitate the structure determination of small proteins and promises to be a useful tool for the study of larger systems that cannot be studied by conventional 2D NMR techniques.     

Utilization of protein intrinsic disorder knowledge in structural proteomics

Intrinsically disordered proteins (IDPs) and proteins with long disordered regions are highly abundant in various proteomes. Despite their lack of well-defined ordered structure, these proteins and regions are frequently involved in crucial biological processes. Although in recent years these proteins have attracted the attention of many researchers, IDPs represent a significant challenge for structural characterization since these proteins can impact many of the processes in the structure determination pipeline. Here we investigate the effects of IDPs on the structure determination process and the utility of disorder prediction in selecting and improving proteins for structural characterization. Examination of the extent of intrinsic disorder in existing crystal structures found that relatively few protein crystal structures contain extensive regions of intrinsic disorder. Although intrinsic disorder is not the only cause of crystallization failures and many structured proteins cannot be crystallized, filtering out highly disordered proteins from structure-determination target lists is still likely to be cost effective. Therefore it is desirable to avoid highly disordered proteins from structure-determination target lists and we show that disorder prediction can be applied effectively to enrich structure determination pipelines with proteins more likely to yield crystal structures. For structural investigation of specific proteins, disorder prediction can be used to improve targets for structure determination. Finally, a framework for considering intrinsic disorder in the structure determination pipeline is proposed.     

Rapid and reliable protein structure determination via chemical shift threading

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often?<?10 min/structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)—with an average TM-score performance of 0.68 (vs. 0.50–0.62 for other methods). Coupled with recent developments in chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca.     

Flexibility observed in high resolution structures of <Emphasis Type="Italic">Streptomyces aureofaciens</Emphasis> ribonucleases determined by diffraction methods

It has been widely accepted to distinguish between static structures determined by diffraction methods and dynamic structures determined by nuclear magnetic resonance (NMR). The dynamics of NMR structures is demonstrated by an ensemble of a number of overlaid structures. This cannot be seen in one structure determined by diffraction methods. However, it is possible to see the flexibility of a protein molecule in a number of structures of the same protein determined by X-ray techniques which is manifested by different conformations of main-chain. Multiple protein structure determination does not provide identical structures as a result of various factors including flexibility. Overlap of structures of a protein determined at atomic resolution with high accuracy shows that the root-mean-square deviations (rmsd) of main-chain atoms exceed several fold the accuracy of the positional parameters of each structure. Overlap of a number of structures of a protein determined by diffraction methods shows a similar distribution as that determined by NMR. These observations are demonstrated using high resolution structures of Streptomyces aureofaciens ribonucleases, their mutants and complexes with ligands.