Efficient identification of amino acid types for fast protein backbone assignments

A simplified recipe for assigning amide NMR signals using combinatorial 14N amino acid inverse-labeling

Assignment of backbone amide proton resonances is one of the most time-consuming stages of any protein NMR study when the protein samples behave non-ideally. A robust and convenient NMR procedure for analyzing spectra of marginal-to-low quality is helpful for high-throughput structure determination. The 14N selective- and inverse-labeling method is a candidate solution. Here, we present a simplified protocol for assigning protein backbone amide NMR signals. When 14N inversely labeled residues are present in a protein, their backbone NH cross peaks vanish from the protein's 1H-(15)N HSQC spectrum, and thus, their chemical shifts can be readily identified by a process of elimination. Some metabolically related amino acids, for example, Ile, Leu, and Val, cannot be individually incorporated but can be inversely labeled together. We optimized and simplified the protocol and M9-based medium formula for the 14N selective- and inverse-labeling method without any additives. Our approach should be cost-effective, because the method could be additively applied stepwise, even when the proteins of interest were found to be non-ideal.

Backbone resonance assignment and order tensor estimation using residual dipolar couplings

An NMR investigation of proteins with known X-ray structures is of interest in a number of endeavors. Performing these studies through nuclear magnetic resonance (NMR) requires the costly step of resonance assignment. The prevalent assignment strategy does not make use of existing structural information and requires uniform isotope labeling. Here we present a rapid and cost-effective method of assigning NMR data to an existing structure-either an X-ray or computationally modeled structure. The presented method, Exhaustively Permuted Assignment of RDCs (EPAR), utilizes unassigned residual dipolar coupling (RDC) data that can easily be obtained by NMR spectroscopy. The algorithm uses only the backbone N-H RDCs from multiple alignment media along with the amino acid type of the RDCs. It is inspired by previous work from Zweckstetter and provides several extensions. We present results on 13 synthetic and experimental datasets from 8 different structures, including two homodimers. Using just two alignment media, EPAR achieves an average assignment accuracy greater than 80%. With three media, the average accuracy is higher than 94%. The algorithm also outputs a prediction of the assignment accuracy, which has a correlation of 0.77 to the true accuracy. This prediction score can be used to establish the needed confidence in assignment accuracy.

Kinetic, dynamic, ligand binding properties, and structural models of a dual-substrate specific nudix hydrolase from Schizosaccharomyces pombe

Schizosaccharomyces pombe Aps1 is a nudix hydrolase that catalyzes the hydrolysis of both diadenosine 5',5'''-P(1),P(n)-oligophosphates and diphosphoinositol polyphosphates in vitro. Nudix hydrolases act upon a wide variety of substrates, despite having a common 23 amino acid catalytic motif; hence, the residues responsible for substrate specificity are considered to reside outside the common catalytic nudix motif. The specific residues involved in binding each substrate of S. pombe Aps1 are unknown. In this study, we have conducted mutational and kinetic studies in combination with structural homology modeling and NMR spectroscopic analyses to identify potential residues involved in binding each class of substrates. This study demonstrates several major findings with regard to Aps1. First, the determination of the kinetic parameters of K(m) and k(cat) indicated that the initial 31 residues of Aps1 are not involved in substrate binding or catalysis with respect to Ap(6)A. Second, NMR spectroscopic analyses revealed the secondary structure and three dynamic backbone regions, one of which corresponds to a large insert in Aps1 as compared to other putative fungal orthologues. Third, two structural models of Aps1Delta2-19, based on the crystal structures of human DIPP1 and T. thermophilus Ndx1, were generated using homology modeling. The structural models were in excellent agreement with the NMR-derived secondary structure of Aps1Delta2-19. Fourth, NMR chemical shift mapping in conjunction with structural homology models indicated several residues outside the catalytic nudix motif that are involved in specific binding of diphosphoinositol polyphosphate or diadenosine oligophosphate ligands.

Protein nuclear magnetic resonance under physiological conditions

Almost everything we know about protein biophysics comes from studies on purified proteins in dilute solution. Most proteins, however, operate inside cells where the concentration of macromolecules can be >300 mg/mL. Although reductionism-based approaches have served protein science well for more than a century, biochemists now have the tools to study proteins under these more physiologically relevant conditions. We review a part of this burgeoning postreductionist landscape by focusing on high-resolution protein nuclear magnetic resonance (NMR) spectroscopy, the only method that provides atomic-level information over an entire protein under the crowded conditions found in cells.

Graphical interpretation of Boolean operators for protein NMR assignments

We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies "AND"-, "OR"- and "NOT"-like operations on planes pulled out of the classical three-dimensional spectra to obtain its functionality. The method's strength lies in the continuous graphical presentation of the spectra, allowing both a semi-automatic peaklist construction and sequential assignment. We demonstrate here its general use for the case of a folded protein with a well-dispersed spectrum, but equally for a natively unfolded protein where spectral resolution is minimal.

NMR analysis of KChIP4a reveals structural basis for control of surface expression of Kv4 channel complexes

Potassium channel-interacting proteins (KChIPs) are EF-hand calcium-binding proteins of the recoverin/neuronal calcium sensor 1 family that co-assemble with the pore-forming Kv4 alpha-subunits and thus control surface trafficking of the voltage-gated potassium channels mediating the neuronal I(A) and cardiac I(to) currents. Different from the other KChIPs, KChIP4a largely reduces surface expression of the Kv4 channel complexes. Using solution NMR we show that the unique N terminus of KChIP4a forms a 6-turn alpha-helix that is connected to the highly conserved core of the KChIP protein via a solvent-exposed linker. As identified by chemical shift changes, N-terminal alpha-helix and core domain of KChIP4a interact with each other through the same hydrophobic surface pocket that is involved in intermolecular interaction between the N-terminal helix of Kv4alpha and KChIP in Kv4-KChIP complexes. Electrophysiological recordings and biochemical interaction assays of complexes formed by wild-type and mutant Kv4alpha and KChIP4a proteins suggest that competition of these two helical domains for the surface groove is responsible for the reduced trafficking of Kv4-KChIP4a complexes to the plasma membrane. Surface expression of Kv4 complexes may thus be controlled by an auto-inhibitory domain in the KChIP subunit.

The guanylate kinase domain of the MAGUK PSD-95 binds dynamically to a conserved motif in MAP1a

The postsynaptic density protein PSD-95 and related membrane-associated guanylate kinases are scaffolding proteins, whose modular interaction motifs organize protein complexes at cell junctions. The signature guanylate kinase domain (GK) contains elements of the protein's GMP-binding site but does not bind nucleotide. Instead, the GK domain has evolved from an enzyme to a protein-protein interaction motif. Here, we show that this canonical GMP-binding region interacts with microtubule-associated protein-1a (MAP1a) and we present a structural model. We determine the consensus GK-binding sequence in MAP1a and demonstrate that PSD-95 can use a similar interaction mode to bind diverse protein partners. Furthermore, we show that PSD-95 GK has adopted the conformational flexibility of the ancestral enzyme to bind its varied ligands, which suggests a mechanism of regulation.

Selective labeling of a membrane peptide with 15N-amino acids using cells grown in rich medium

Nuclear magnetic resonance spectra of membrane proteins containing multiple transmembrane helices have proven difficult to resolve due to the redundancy of aliphatic and Ser/Thr residues in transmembrane domains and the low chemical shift dispersity exhibited by residues in alpha-helical structures. Although (13)C- and (15)N-labeling are useful tools in the biophysical analysis of proteins, selective labeling of individual amino acids has been used to help elucidate more complete structures and to probe ligand-protein interactions. In general, selective labeling has been performed in Escherichia coli expression systems using minimal media supplemented with a single labeled amino acid and nineteen other unlabeled amino acids and/or by using auxotrophs for specific amino acids. Growth in minimal media often results in low yields of cells or expression products. We demonstrate a method in which one labeled amino acid is added to a rich medium. These conditions resulted in high expression (> or =100 mg/L) of a test fusion protein and milligram quantities of the selectively labeled membrane peptide after cyanogen bromide cleavage to release the peptide from the fusion protein. High levels of (15)N incorporation and acceptable levels of cross-labeling into other amino acid residues of the peptide were achieved. Growth in rich media is a simple and convenient alternative to growth in supplemented minimal media and is readily applicable to the expression of proteins selectively labeled with specific amino acids.

Combination of cell-free expression and NMR spectroscopy as a new approach for structural investigation of membrane proteins

Despite major technical advance in methods used for structural investigations of proteins structure determination of membrane proteins still poses a significant challenge. Recently, the application of cell-free expression systems to membrane proteins has demonstrated that this technique can be used to produce quantities sufficient for structural investigations for many different membrane proteins. In particular for NMR spectroscopy, cell-free expression provides major advantages since it allows for amino acid type selective and even amino acid position specific labeling. In this mini-review we discuss the combination of cell-free membrane protein expression and liquid state NMR spectroscopy.

RIBRA--an error-tolerant algorithm for the NMR backbone assignment problem

We develop an iterative relaxation algorithm called RIBRA for NMR protein backbone assignment. RIBRA applies nearest neighbor and weighted maximum independent set algorithms to solve the problem. To deal with noisy NMR spectral data, RIBRA is executed in an iterative fashion based on the quality of spectral peaks. We first produce spin system pairs using the spectral data without missing peaks, then the data group with one missing peak, and finally, the data group with two missing peaks. We test RIBRA on two real NMR datasets, hbSBD and hbLBD, and perfect BMRB data (with 902 proteins) and four synthetic BMRB data which simulate four kinds of errors. The accuracy of RIBRA on hbSBD and hbLBD are 91.4% and 83.6%, respectively. The average accuracy of RIBRA on perfect BMRB datasets is 98.28%, and 98.28%, 95.61%, 98.16%, and 96.28% on four kinds of synthetic datasets, respectively.

Automated protein NMR structure determination in crude cell-extract

A fully automated, NOE-based NMR structure determination of a uniformly 13C,15N-labeled protein was achieved in crude cell-extract, without purification of the overexpressed protein. Essentially complete sequence-specific assignments were obtained using triple resonance experiments, based on the high intensity of the resonances from the overexpressed protein relative to those of the background. For the collection of NOE distance constraints, efficient discrimination between NOE cross peaks from the target protein and background signals was achieved using the programs ATNOS and CANDID. In the iterative ATNOS/CANDID procedure, the identification of the desired protein NOEs is initially guided by the self-consistency of the protein NOE-network. Although the intensities of the signals in this network vary over a wide range, and are in many instances comparable to or smaller than those of the background, the first cycle of calculations resulted in the correct global polypeptide fold, and the structure was then refined in six subsequent cycles using the intermediate NMR structures for additional guidance. The experience gained with this work demonstrates that the ATNOS/CANDID procedure for automatic protein structure determination is highly robust and reliable in the presence of intense background signals, and might thus also represent a platform for future protein structure determinations in physiological fluids.

GANA--a genetic algorithm for NMR backbone resonance assignment

NMR data from different experiments often contain errors; thus, automated backbone resonance assignment is a very challenging issue. In this paper, we present a method called GANA that uses a genetic algorithm to automatically perform backbone resonance assignment with a high degree of precision and recall. Precision is the number of correctly assigned residues divided by the number of assigned residues, and recall is the number of correctly assigned residues divided by the number of residues with known human curated answers. GANA takes spin systems as input data and uses two data structures, candidate lists and adjacency lists, to assign the spin systems to each amino acid of a target protein. Using GANA, almost all spin systems can be mapped correctly onto a target protein, even if the data are noisy. We use the BioMagResBank (BMRB) dataset (901 proteins) to test the performance of GANA. To evaluate the robustness of GANA, we generate four additional datasets from the BMRB dataset to simulate data errors of false positives, false negatives and linking errors. We also use a combination of these three error types to examine the fault tolerance of our method. The average precision rates of GANA on BMRB and the four simulated test cases are 99.61, 99.55, 99.34, 99.35 and 98.60%, respectively. The average recall rates of GANA on BMRB and the four simulated test cases are 99.26, 99.19, 98.85, 98.87 and 97.78%, respectively. We also test GANA on two real wet-lab datasets, hbSBD and hbLBD. The precision and recall rates of GANA on hbSBD are 95.12 and 92.86%, respectively, and those of hbLBD are 100 and 97.40%, respectively.

In-cell NMR spectroscopy

The role of a protein inside a cell is determined by both its location and its conformational state. Although fluorescence techniques are widely used to determine the cellular localization of proteins in vivo, these approaches cannot provide detailed information about a protein's three-dimensional state. This gap, however, can be filled by NMR spectroscopy, which can be used to investigate both the conformation as well as the dynamics of proteins inside living cells. In this chapter we describe technical aspects of these "in-cell NMR" experiments. In particular, we show that in the case of (15)N-labeling schemes the background caused by labeling all cellular components is negligible, while (13)C-based experiments suffer from high background levels and require selective labeling schemes. A correlation between the signal-to-noise ratio of in-cell NMR experiments with the overexpression level of the protein shows that the current detection limit is 150-200 muM (intracellular concentration). We also discuss experiments that demonstrate that the intracellular viscosity is not a limiting factor since the intracellular rotational correlation time is only approximately two times longer than the correlation time in water. Furthermore, we describe applications of the technique and discuss its limitations.

Optimization of an Escherichia coli system for cell-free synthesis of selectively 15N-labelled proteins for rapid analysis by NMR spectroscopy

Cell-free protein synthesis offers rapid access to proteins that are selectively labelled with [15N]amino acids and suitable for analysis by NMR spectroscopy without chromatographic purification. A system based on an Escherichia coli cell extract was optimized with regard to protein yield and minimal usage of 15N-labelled amino acid, and examined for the presence of metabolic by-products which could interfere with the NMR analysis. Yields of up to 1.8 mg of human cyclophilin A per mL of reaction medium were obtained by expression of a synthetic gene. Equivalent yields were obtained using transcription directed by either T7 or tandem phage lambdapR and pL promoters, when the reactions were supplemented with purified phage T7 or E. coli RNA polymerase. Nineteen samples, each selectively labelled with a different 15N-enriched amino acid, were produced and analysed directly by NMR spectroscopy after ultracentrifugation. Cross-peaks from metabolic by-products were evident in the 15N-HSQC spectra of 13 of the samples. All metabolites were found to be small molecules that could be separated readily from the labelled proteins by dialysis. No significant transamination activity was observed except for [15N]Asp, where an enzyme in the cell extract efficiently converted Asp-->Asn. This activity was suppressed by replacing the normally high levels of potassium glutamate in the reaction mixture with ammonium or potassium acetate. In addition, the activity of peptide deformylase appeared to be generally reduced in the cell-free expression system.

Screening methods to determine biophysical properties of proteins in structural genomics

We have developed and tested a simple and efficient protein purification method for biophysical screening of proteins and protein fragments by nuclear magnetic resonance (NMR) and optical methods, such as circular dichroism spectroscopy. The method constitutes an extension of previously described protocols for gene expression and protein solubility screening [M. Hammarström et al., (2002), Protein Science 11, 313]. Using the present purification scheme it is possible to take several target proteins, produced as fusion proteins, from cell pellet to NMR spectrum and obtain a judgment on the suitability for further structural or biophysical studies in less than 1 day. The method is independent of individual protein properties as long as the target protein can be produced in soluble form with a fusion partner. Identical procedures for cell culturing, lysis, affinity chromatography, protease cleavage, and NMR sample preparation then initially require only optimization for different fusion partner and protease combinations. The purification method can be automated, scaled up or down, and extended to a traditional purification scheme. We have tested the method on several small human proteins produced in Escherichia coli and find that the method allows for detection of structured proteins and unfolded or molten globule-like proteins.

NMR analysis of in vitro-synthesized proteins without purification: a high-throughput approach

A cell-free protein expression system was established that provides protein samples of adequate concentration and purity for direct NMR analysis. The Escherichia coli peptidyl-prolyl cis-trans isomerase PpiB was expressed in this system with dual amino acid-selective isotope labeling to identify the NMR signal from the active site-residue Arg87. Addition of the substrate succinyl-Ala-Ala-Pro-Phe-p-nitroanilide selectively shifted its (15)N-HSQC cross peak, confirming binding to the active site. As cell-free protein expression provides high yields of protein per unit mass of labeled amino acid and sample handling is minimal, this strategy presents an exceptionally inexpensive and rapid approach to protein analysis.