Construct optimization for protein NMR structure analysis using amide hydrogen/deuterium exchange mass spectrometry

Disordered or unstructured regions of proteins, while often very important biologically, can pose significant challenges for resonance assignment and three‐dimensional structure determination of the ordered regions of proteins by NMR methods. In this article, we demonstrate the application of ¹H/²H exchange mass spectrometry (DXMS) for the rapid identification of disordered segments of proteins and design of protein constructs that are more suitable for structural analysis by NMR. In this benchmark study, DXMS is applied to five NMR protein targets chosen from the Northeast Structural Genomics project. These data were then used to design optimized constructs for three partially disordered proteins. Truncated proteins obtained by deletion of disordered N‐ and C‐terminal tails were evaluated using ¹H‐¹⁵N HSQC and ¹H‐¹⁵N heteronuclear NOE NMR experiments to assess their structural integrity. These constructs provide significantly improved NMR spectra, with minimal structural perturbations to the ordered regions of the protein structure. As a representative example, we compare the solution structures of the full length and DXMS‐based truncated construct for a 77‐residue partially disordered DUF896 family protein YnzC from Bacillus subtilis, where deletion of the disordered residues (ca. 40% of the protein) does not affect the native structure. In addition, we demonstrate that throughput of the DXMS process can be increased by analyzing mixtures of up to four proteins without reducing the sequence coverage for each protein. Our results demonstrate that DXMS can serve as a central component of a process for optimizing protein constructs for NMR structure determination. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Application of NMR in structural proteomics: screening for proteins amenable to structural analysis

In the time of structural proteomics when protein structures are targeted on a genome-wide scale, the detection of "well-behaved" proteins that would yield good quality NMR spectra or X-ray images is the key to high-throughput structure determination. Already, simple one-dimensional proton NMR spectra provide enough information for assessing the folding properties of proteins. Heteronuclear two-dimensional spectra are routinely used for screenings that reveal structural, as well as binding, properties of proteins. NMR can thus provide important information for optimizing conditions for protein constructs that are amenable to structural studies.     

Strategies for structural proteomics of prokaryotes: Quantifying the advantages of studying orthologous proteins and of using both NMR and X-ray crystallography approaches

Only about half of non-membrane-bound proteins encoded by either bacterial or archaeal genomes are soluble when expressed in Escherichia coli (Yee et al., Proc Natl Acad Sci USA 2002;99:1825-1830; Christendat et al., Prog Biophys Mol Biol 200;73:339-345). This property limits genome-scale functional and structural proteomics studies, which depend on having a recombinant, soluble version of each protein. An emerging strategy to increase the probability of deriving a soluble derivative of a protein is to study different sequence homologues of the same protein, including representatives from thermophilic organisms, based on the assumption that the stability of these proteins will facilitate structural analysis. To estimate the relative merits of this strategy, we compared the recombinant expression, solubility, and suitability for structural analysis by NMR and/or X-ray crystallography for 68 pairs of homologous proteins from E. coli and Thermotoga maritima. A sample suitable for structural studies was obtained for 62 of the 68 pairs of homologs under standardized growth and purification procedures. Fourteen (eight E. coli and six T. maritima proteins) samples generated NMR spectra of a quality suitable for structure determination and 30 (14 E. coli and 16 T. maritima proteins) samples formed crystals. Only three (one E. coli and two T. maritima proteins) samples both crystallized and had excellent NMR properties. The conclusions from this work are: (1) The inclusion of even a single ortholog of a target protein increases the number of samples for structural studies almost twofold; (2) there was no clear advantage to the use of thermophilic proteins to generate samples for structural studies; and (3) for the small proteins analyzed here, the use of both NMR and crystallography approaches almost doubled the number of samples for structural studies.     

Towards miniaturization of a structural genomics pipeline using micro-expression and microcoil NMR

In structural genomics centers, nuclear magnetic resonance (NMR) screening is in increasing use as a tool to identify folded proteins that are promising targets for three-dimensional structure determination by X-ray crystallography or NMR spectroscopy. The use of 1D ¹H NMR spectra or 2D [¹H,¹⁵N]-correlation spectroscopy (COSY) typically requires milligram quantities of unlabeled or isotope-labeled protein, respectively. Here, we outline ways towards miniaturization of a structural genomics pipeline with NMR screening for folded globular proteins, using a high-density micro-fermentation device and a microcoil NMR probe. The proteins are micro-expressed in unlabeled or isotope-labeled media, purified, and then subjected to 1D ¹H NMR and/or 2D [¹H,¹⁵N]-COSY screening. To demonstrate that the miniaturization is functioning effectively, we processed nine mouse homologue protein targets and compared the results with those from the “macro-scale” Joint Center of Structural Genomics (JCSG) high-throughput pipeline. The results from the two pipelines were comparable, illustrating that the data were not compromised in the miniaturized approach.     

Relationship between local structural entropy and protein thermostability

We developed a technique to compute structural entropy directly from protein sequences. We explored the possibility of using structural entropy to identify residues involved in thermal stabilization of various protein families. Examples include methanococcal adenylate kinase, Ribonuclease HI and holocytochrome c(551). Our results show that the positions of the largest structural entropy differences between wild type and mutant usually coincide with the residues relevant to thermostability. We also observed a good linear relationship between the average structural entropy and the melting temperatures for adenylate kinase and its chimeric constructs. To validate this linear relationship, we compiled a large dataset comprised of 1153 sequences and found that most protein families still display similar linear relationships. Our results suggest that the multitude of interactions involved in thermal stabilization may be generalized into the tendency of proteins to maintain local structural conservation. The linear relationship between structural entropy and protein thermostability should be useful in the study of protein thermal stabilization.     

Comparison of cell-based and cell-free protocols for producing target proteins from the Arabidopsis thaliana genome for structural studies

We describe a comparative study of protein production from 96 Arabidopsis thaliana open reading frames (ORFs) by cell-based and cell-free protocols. Each target was carried through four pipeline protocols used by the Center for Eukaryotic Structural Genomics (CESG), one for the production of unlabeled protein to be used in crystallization trials and three for the production of 15N-labeled proteins to be analyzed by 1H-15N NMR correlation spectroscopy. Two of the protocols involved Escherichia coli cell-based and two involved wheat germ cell-free technology. The progress of each target through each of the protocols was followed with all failures and successes noted. Failures were of the following types: ORF not cloned, protein not expressed, low protein yield, no cleavage of fusion protein, insoluble protein, protein not purified, NMR sample too dilute. Those targets that reached the goal of analysis by 1H-15N NMR correlation spectroscopy were scored as HSQC+ (protein folded and suitable for NMR structural analysis), HSQC+/- (protein partially disordered or not in a single stable conformational state), HSQC- (protein unfolded, misfolded, or aggregated and thus unsuitable for NMR structural analysis). Targets were also scored as X- for failing to crystallize and X+ for successful crystallization. The results constitute a rich database for understanding differences between targets and protocols. In general, the wheat germ cell-free platform offers the advantage of greater genome coverage for NMR-based structural proteomics whereas the E. coli platform when successful yields more protein, as currently needed for crystallization trials for X-ray structure determination.     

NMR spectroscopy as a tool for the rapid assessment of the conformation of GST-fusion proteins

Glutathione-S-transferase (GST)-fusion proteins are used extensively for structural, biochemical, and functional analyses. Although the conformation of the target protein is of critical importance, confirmation of the folded state of the target is often not undertaken or is cumbersome because of the requirement to first remove the GST tag. Here, we demonstrate that it is possible to record conventional (15)N-HSQC NMR spectra of small GST-fusion proteins and that the observed signals arise almost exclusively from the target protein. This approach constitutes a rapid and straightforward means of assessing the conformation of a GST-fusion protein without having to cleave the GST and should prove valuable, both to biochemists seeking to check the conformation of their proteins prior to functional studies and to structural biologists screening protein constructs for suitability as targets for structural studies.     

Predicted role for the archease protein family based on structural and sequence analysis of TM1083 and MTH1598, two proteins structurally characterized through structural genomics efforts

Recently, the structures of two proteins belonging to the archease family, TM1083 from Thermotoga maritima and MTH1598 from Methanobacterium thermoautotrophicum, have been solved independently by two Protein Structure Initiative structural genomics pilot centers using X-ray crystallography and NMR, respectively. The archease protein family is a good example of one of the paradoxes of structural genomics: Approximately one third of protein structures produced by structural genomics centers have no known function and are still annotated as "hypothetical proteins" in the Protein Data Bank. In the case of archeases, despite the existence of two protein structures and abundant sequence information, there is still no function assigned to this protein family. Here, our group predicts, based on structural similarity, sequence conservation, and gene context analyses, that members of this protein family might function as chaperones or modulators of proteins involved in DNA/RNA processing. The conservation of genomic context for this protein family is constant from Archaea and Bacteria to humans, and suggests that unannotated open reading frames contiguous to them could be novel RNA/DNA binding proteins.     

Will my protein crystallize? A sequence‐based predictor

We propose a machine-learning approach to sequence-based prediction of protein crystallizability in which we exploit subtle differences between proteins whose structures were solved by X-ray analysis [or by both X-ray and nuclear magnetic resonance (NMR) spectroscopy] and those proteins whose structures were solved by NMR spectroscopy alone. Because the NMR technique is usually applied on relatively small proteins, sequence length distributions of the X-ray and NMR datasets were adjusted to avoid predictions biased by protein size. As feature space for classification, we used frequencies of mono-, di-, and tripeptides represented by the original 20-letter amino acid alphabet as well as by several reduced alphabets in which amino acids were grouped by their physicochemical and structural properties. The classification algorithm was constructed as a two-layered structure in which the output of primary support vector machine classifiers operating on peptide frequencies was combined by a second-level Naive Bayes classifier. Due to the application of metamethods for cost sensitivity, our method is able to handle real datasets with unbalanced class representation. An overall prediction accuracy of 67% [65% on the positive (crystallizable) and 69% on the negative (noncrystallizable) class] was achieved in a 10-fold cross-validation experiment, indicating that the proposed algorithm may be a valuable tool for more efficient target selection in structural genomics. A Web server for protein crystallizability prediction called SECRET is available at http://webclu.bio.wzw.tum.de:8080/secret.     

Comparison of X‐ray and NMR structures: Is there a systematic difference in residue contacts between X‐ray‐ and NMR‐resolved protein structures?

We have compared structures of 78 proteins determined by both NMR and X-ray methods. It is shown that X-ray and NMR structures of the same protein have more differences than various X-ray structures obtained for the protein, and even more than various NMR structures of the protein. X-ray and NMR structures of 18 of these 78 proteins have obvious large-scale structural differences that seem to reflect a difference of crystal and solution structures. The other 60 pairs of structures have only small-scale differences comparable with differences between various X-ray or various NMR structures of a protein; we have analyzed these structures more attentively. One of the main differences between NMR and X-ray structures concerns the number of contacts per residue: (1) NMR structures presented in PDB have more contacts than X-ray structures at distances below 3.0 A and 4.5-6.5 A, and fewer contacts at distances of 3.0-4.5 A and 6.5-8.0 A; (2) this difference in the number of contacts is greater for internal residues than for external ones, and it is larger for beta-containing proteins than for all-alpha proteins. Another significant difference is that the main-chain hydrogen bonds identified in X-ray and NMR structures often differ. Their correlation is 69% only. However, analogous difference is found for refined and rerefined NMR structures, allowing us to suggest that the observed difference in interresidue contacts of X-ray and NMR structures of the same proteins is due mainly to a difference in mathematical treatment of experimental results.     

A solubility-enhancement tag (SET) for NMR studies of poorly behaving proteins

Protein-fusion constructs have been used with great success for enhancing expression of soluble recombinant protein and as tags for affinity purification. Unfortunately the most popular tags, such as GST and MBP, are large, which hinders direct NMR studies of the fusion proteins. Cleavage of the fusion proteins often re-introduces problems with solubility and stability. Here we describe the use of N-terminally fused protein G (B1 domain) as a non-cleavable solubility-enhancement tag (SET) for structure determination of a dimeric protein complex. The SET enhances the solubility and stability of the fusion product dramatically while not interacting directly with the protein of interest. This approach can be used for structural characterization of poorly behaving protein systems, and would be especially useful for structural genomics studies.     

The dynamic duo: Combining NMR and small angle scattering in structural biology

Structural biology provides essential information for elucidating molecular mechanisms that underlie biological function. Advances in hardware, sample preparation, experimental methods, and computational approaches now enable structural analysis of protein complexes with increasing complexity that more closely represent biologically entities in the cellular environment. Integrated multidisciplinary approaches are required to overcome limitations of individual methods and take advantage of complementary aspects provided by different structural biology techniques. Although X‐ray crystallography remains the method of choice for structural analysis of large complexes, crystallization of flexible systems is often difficult and does typically not provide insights into conformational dynamics present in solution. Nuclear magnetic resonance spectroscopy (NMR) is well‐suited to study dynamics at picosecond to second time scales, and to map binding interfaces even of large systems at residue resolution but suffers from poor sensitivity with increasing molecular weight. Small angle scattering (SAS) methods provide low resolution information in solution and can characterize dynamics and conformational equilibria complementary to crystallography and NMR. The combination of NMR, crystallography, and SAS is, thus, very useful for analysis of the structure and conformational dynamics of (large) protein complexes in solution. In high molecular weight systems, where NMR data are often sparse, SAS provides additional structural information and can differentiate between NMR‐derived models. Scattering data can also validate the solution conformation of a crystal structure and indicate the presence of conformational equilibria. Here, we review current state‐of‐the‐art approaches for combining NMR, crystallography, and SAS data to characterize protein complexes in solution.     

Ion mobility–mass spectrometry for structural proteomics

Ion mobility coupled to mass spectrometry has been an important tool in the fields of chemical physics and analytical chemistry for decades, but its potential for interrogating the structure of proteins and multiprotein complexes has only recently begun to be realized. Today, ion mobility–mass spectrometry is often applied to the structural elucidation of protein assemblies that have failed high-throughput crystallization or NMR spectroscopy screens. Here, we highlight the technology, approaches and data that have led to this dramatic shift in use, including emerging trends such as the integration of ion mobility–mass spectrometry data with more classical (e.g., ‘bottom-up’) proteomics approaches for the rapid structural characterization of protein networks.     

Refolding out of guanidine hydrochloride is an effective approach for high-throughput structural studies of small proteins

Low in vivo solubility of recombinant proteins expressed in Escherichia coli can seriously hinder the purification of structural samples for large-scale proteomic NMR and X-ray crystallography studies. Previous results from our laboratory have shown that up to one half of all bacterial and archaeal proteins are insoluble when overexpressed in E. coli. Although a number of strategies may be used to increase in vivo protein solubility, there are no generally applicable methods, and the expression of each insoluble recombinant protein must be individually optimized. For this reason, we have tested a generic denaturation/refolding protein purification procedure to assess the number of structural samples that could be generated by using this methodology. Our results show that a denaturation/refolding protocol is appropriate for many small proteins (相似文献   

MUSTANG: a multiple structural alignment algorithm

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.     

The New York Consortium on Membrane Protein Structure (NYCOMPS): a high-throughput platform for structural genomics of integral membrane proteins

The New York Consortium on Membrane Protein Structure (NYCOMPS) was formed to accelerate the acquisition of structural information on membrane proteins by applying a structural genomics approach. NYCOMPS comprises a bioinformatics group, a centralized facility operating a high-throughput cloning and screening pipeline, a set of associated wet labs that perform high-level protein production and structure determination by x-ray crystallography and NMR, and a set of investigators focused on methods development. In the first three years of operation, the NYCOMPS pipeline has so far produced and screened 7,250 expression constructs for 8,045 target proteins. Approximately 600 of these verified targets were scaled up to levels required for structural studies, so far yielding 24 membrane protein crystals. Here we describe the overall structure of NYCOMPS and provide details on the high-throughput pipeline.     

Characterizing conserved structural contacts by pair-wise relative contacts and relative packing groups

To adequately deal with the inherent complexity of interactions between protein side-chains, we develop and describe here a novel method for characterizing protein packing within a fold family. Instead of approaching side-chain interactions absolutely from one residue to another, we instead consider the relative interactions of contacting residue pairs. The basic element, the pair-wise relative contact, is constructed from a sequence alignment and contact analysis of a set of structures and consists of a cluster of similarly oriented, interacting, side-chain pairs. To demonstrate this construct's usefulness in analyzing protein structure, we used the pair-wise relative contacts to analyze two sets of protein structures as defined by SCOP: the diverse globin-like superfamily (126 structures) and the more uniform heme binding globin family (a 94 structure subset of the globin-like superfamily). The superfamily structure set produced 1266 unique pair-wise relative contacts, whereas the family structure subset gave 1001 unique pair-wise relative contacts. For both sets, we show that these constructs can be used to accurately and automatically differentiate between fold classes. Furthermore, these pair-wise relative contacts correlate well with sequence identity and thus provide a direct relationship between changes in sequence and changes in structure. To capture the complexity of protein packing, these pair-wise relative contacts can be superimposed around a single residue to create a multi-body construct called a relative packing group. Construction of convex hulls around the individual packing groups provides a measure of the variation in packing around a residue and defines an approximate volume of space occupied by the groups interacting with a residue. We find that these relative packing groups are useful in understanding the structural quality of sequence or structure alignments. Moreover, they provide context to calculate a value for structural randomness, which is important in properly assessing the quality of a structural alignment. The results of this study provide the framework for future analysis for correlating sequence changes to specific structure changes.     

A part of ice nucleation protein exhibits the ice-binding ability

We generated a recombinant 96-residue polypeptide corresponding to a sequence Tyr176-Gly273 of ice nucleation protein from Pseudomonas syringae (denoted INP96). INP96 exhibited an ability to shape an ice crystal, whose morphology is highly similar to the hexagonal-bipyramid generally identified for antifreeze protein. INP96 also showed a non-linear, concentration-dependent retardation of ice growth. Additionally, circular dichroism and NMR measurements suggested a local structural construction in INP96, which undergoes irreversible thermal denaturation. These data imply that a part of INP constructs a unique structure so as to interact with the ice crystal surfaces.     

Strategies for the structural analysis of multi-protein complexes: lessons from the 3D-Repertoire project

Structural studies of multi-protein complexes, whether by X-ray diffraction, scattering, NMR spectroscopy or electron microscopy, require stringent quality control of the component samples. The inability to produce 'keystone' subunits in a soluble and correctly folded form is a serious impediment to the reconstitution of the complexes. Co-expression of the components offers a valuable alternative to the expression of single proteins as a route to obtain sufficient amounts of the sample of interest. Even in cases where milligram-scale quantities of purified complex of interest become available, there is still no guarantee that good quality crystals can be obtained. At this step, protein engineering of one or more components of the complex is frequently required to improve solubility, yield or the ability to crystallize the sample. Subsequent characterization of these constructs may be performed by solution techniques such as Small Angle X-ray Scattering and Nuclear Magnetic Resonance to identify 'well behaved' complexes. Herein, we recount our experiences gained at protein production and complex assembly during the European 3D Repertoire project (3DR). The goal of this consortium was to obtain structural information on multi-protein complexes from yeast by combining crystallography, electron microscopy, NMR and in silico modeling methods. We present here representative set case studies of complexes that were produced and analyzed within the 3DR project. Our experience provides useful insight into strategies that are more generally applicable for structural analysis of protein complexes.     

Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality

Membrane proteins are challenging to study and restraints for structure determination are typically sparse or of low resolution because the membrane environment that surrounds them leads to a variety of experimental challenges. When membrane protein structures are determined by different techniques in different environments, a natural question is “which structure is most biologically relevant?” Towards answering this question, we compiled a dataset of membrane proteins with known structures determined by both solution NMR and X‐ray crystallography. By investigating differences between the structures, we found that RMSDs between crystal and NMR structures are below 5 Å in the membrane region, NMR ensembles have a higher convergence in the membrane region, crystal structures typically have a straighter transmembrane region, have higher stereo‐chemical correctness, and are more tightly packed. After quantifying these differences, we used high‐resolution refinement of the NMR structures to mitigate them, which paves the way for identifying and improving the structural quality of membrane proteins.