Useful Information from Axial Peak Magnetization in Projected NMR Experiments

UTOPIA NMR: activating unexploited magnetization using interleaved low-gamma detection

A growing number of nuclear magnetic resonance (NMR) spectroscopic studies are impaired by the limited information content provided by the standard set of experiments conventionally recorded. This is particularly true for studies of challenging biological systems including large, unstructured, membrane-embedded and/or paramagnetic proteins. Here we introduce the concept of unified time-optimized interleaved acquisition NMR (UTOPIA-NMR) for the unified acquisition of standard high-γ (e.g. (1)H) and low-γ (e.g. (13)C) detected experiments using a single receiver. Our aim is to activate the high level of polarization and information content distributed on low-γ nuclei without disturbing conventional magnetization transfer pathways. We show that using UTOPIA-NMR we are able to recover nearly all of the normally non-used magnetization without disturbing the standard experiments. In other words, additional spectra, that can significantly increase the NMR insights, are obtained for free. While we anticipate a broad range of possible applications we demonstrate for the soluble protein Bcl-xL (ca. 21 kDa) and for OmpX in nanodiscs (ca. 160 kDa) that UTOPIA-NMR is particularly useful for challenging protein systems including perdeuterated (membrane) proteins.

Efficient sequential assignments in proteins with reduced dimensionality 3D HN(CA)NH

We present reduced dimensionality (RD) 3D HN(CA)NH for efficient sequential assignment in proteins. The experiment correlates the (15)N and (1)H chemical shift of a residue ('i') with those of its immediate N-terminal (i - 1) and C-terminal (i + 1) neighbors and provides four-dimensional chemical shift correlations rapidly with high resolution. An assignment strategy is presented which combines the correlations observed in this experiment with amino acid type information obtained from 3D CBCA(CO)NH. By classifying the 20 amino acid types into seven distinct categories based on (13)C(β) chemical shifts, it is observed that a stretch of five sequentially connected residues is sufficient to map uniquely on to the polypeptide for sequence specific resonance assignments. This method is exemplified by application to three different systems: maltose binding protein (42 kDa), intrinsically disordered domain of insulin-like growth factor binding protein-2 and Ubiquitin. Fast data acquisition is demonstrated using longitudinal (1)H relaxation optimization. Overall, 3D HN(CA)NH is a powerful tool for high throughput resonance assignment, in particular for unfolded or intrinsically disordered polypeptides.

Lessons from structural genomics

A decade of structural genomics, the large-scale determination of protein structures, has generated a wealth of data and many important lessons for structural biology and for future large-scale projects. These lessons include a confirmation that it is possible to construct large-scale facilities that can determine the structures of a hundred or more proteins per year, that these structures can be of high quality, and that these structures can have an important impact. Technology development has played a critical role in structural genomics, the difficulties at each step of determining a structure of a particular protein can be quantified, and validation of technologies is nearly as important as the technologies themselves. Finally, rapid deposition of data in public databases has increased the impact and usefulness of the data and international cooperation has advanced the field and improved data sharing.

J-GFT NMR for precise measurement of mutually correlated nuclear spin-spin couplings

G-matrix Fourier transform (GFT) NMR spectroscopy is presented for accurate and precise measurement of chemical shifts and nuclear spin-spin couplings correlated according to spin system. The new approach, named "J-GFT NMR", is based on a largely extended GFT NMR formalism and promises to have a broad impact on projection NMR spectroscopy. Specifically, constant-time J-GFT (6,2)D (HA-CA-CO)-N-HN was implemented for simultaneous measurement of five mutually correlated NMR parameters, that is, 15N backbone chemical shifts and the four one-bond spin-spin couplings 13Calpha-1Halpha, 13Calpha-13C', 15N-13C', and 15N-1HNu. The experiment was applied for measuring residual dipolar couplings (RDCs) in an 8 kDa protein Z-domain aligned with Pf1 phages. Comparison with RDC values extracted from conventional NMR experiments reveals that RDCs are measured with high precision and accuracy, which is attributable to the facts that (i) the use of constant time evolution ensures that signals do not broaden whenever multiple RDCs are jointly measured in a single dimension and (ii) RDCs are multiply encoded in the multiplets arising from the joint sampling. This corresponds to measuring the couplings multiple times in a statistically independent manner. A key feature of J-GFT NMR, i.e., the correlation of couplings according to spin systems without reference to sequential resonance assignments, promises to be particularly valuable for rapid identification of backbone conformation and classification of protein fold families on the basis of statistical analysis of dipolar couplings.

Principles and applications of GFT projection NMR spectroscopy

The two defining features of G-matrix Fourier transform (GFT) projection NMR spectroscopy are (i) repeated joint sampling of several indirect chemical shift evolution periods of a multidimensional NMR experiment so that transfer amplitudes are generated which are proportional to all possible permutations of cosine and sine modulations of the individual shifts, and (ii) linear combination of the subspectra resulting from such repeated joint sampling in the time or frequency domain which yields edited subspectra containing signals encoding phase-sensitively detected linear combinations of the jointly sampled shifts. This review sketches the underlying principles of GFT NMR and outlines its relation to further developments such as the reconstruction of multidimensional NMR spectra.

G-matrix Fourier transform NOESY-based protocol for high-quality protein structure determination

A protocol for high-quality structure determination based on G-matrix Fourier transform (GFT) NMR is presented. Five through-bond chemical shift correlation experiments providing 4D and 5D spectral information at high digital resolution are performed for resonance assignment. These are combined with a newly implemented (4,3)D GFT NOESY experiment which encodes information of 4D 15N/15N-, 13C(alipahtic)/15N-, and 13C(aliphatic)/13C(aliphatic)-resolved [1H,1H]-NOESY in two subspectra, each containing one component of chemical shift doublets arising from 4D --> 3D projection at omega1:Omega(1H) +/- Omega(X) [X = 15N,13C(aliphatic)]. The peaks located at the centers of the doublets are obtained from simultaneous 3D 15N/13C(aliphatic)/13C(aromatic)-resolved [1H,1H]-NOESY, wherein NOEs detected on aromatic protons are also obtained. The protocol was applied for determining a high-quality structure of the 14 kDa Northeast Structural Genomics consortium target protein, YqfB (PDB ID ). Through-bond correlation and NOESY spectra were acquired, respectively, in 16.9 and 39 h (30 h for shift doublets, 9 h for central peaks) on a 600 MHz spectrometer equipped with a cryogenic probe. The rapidly collected highly resolved 4D NOESY information allows one to assign the majority of NOEs directly from chemical shifts, which yields accurate initial structures "within" approximately 2 angstroms of the final structure. Information theoretical "QUEEN" analysis of initial distance limit constraint networks revealed that, in contrast to structure-based protocols, such NOE assignment is not biased toward identifying additional constraints that tend to be redundant with respect to the available constraint network. The protocol enables rapid NMR data collection for robust high-quality structure determination of proteins up to approximately 20-25 kDa in high-throughput.

Probing Structure and Functional Dynamics of (Large) Proteins with Aromatic Rings: L-GFT-TROSY (4,3)D HCCH NMR Spectroscopy

NMR assignment of aromatic rings in proteins is a prerequisite for obtaining high-quality solution structures of proteins and for studying the dynamics and folding of their molecular cores. Here we present sensitive PFG-PEP L-GFT-(TROSY) (4,3)D HCCH NMR for identification of aromatic spin systems based on four-dimensional (4D) spectral information which can be rapidly obtained with high digital resolution. The G-matrix Fourier Transform (GFT) experiment relies on newly introduced longitudinal relaxation (L-)optimization for aromatic protons and is optimally suited for both sensitivity and sampling limited data collection, making it particularly attractive for NMR-based structural genomics. Applications are presented for 21 and 13 kDa proteins HR41 and MaR11, targets of the Northeast Structural Genomics Consortium for which data collection is, respectively, sensitivity and sampling limited. Complete assignment of aromatic rings enabled high-quality NMR structure determination, and nearly complete analysis of aromatic proton line widths allowed one to assess the flipping of most rings in HR41. Specifically, the ring of Tyr90 flips very slowly on the seconds time scale, thereby proving the absence of fast larger-amplitude motional modes which could allow the ring to flip. This indicates remarkable rigidity of the substructure in which the ring is embedded. Tyr90 is conserved among ubiquitin-conjugating enzymes E2, to which HR41 belongs, and is located in spatial proximity to the interface between E2 and ubiquitin protein ligase E3. Hence, the conformational rigidity and/or the slow motional mode probed by the ring might be of functional importance.

Resonance Assignment of Proteins with High Shift Degeneracy Based on 5D Spectral Information Encoded in G2FT NMR Experiments

A suite of novel (5,3)D G2FT triple resonance NMR experiments encoding highly resolved 5D spectral information is presented for sequential resonance assignment of proteins exhibiting high chemical shift degeneracy. Efficient resonance assignment is achieved by separate joint sampling of (i) chemical shifts which solely serve to provide increased resolution and (ii) shifts which also provide sequential connectivities. In these G2FT experiments, two G-matrix transformations are employed. Peaks are resolved along a first GFT dimension at both Omega(15N) + Omega(13C') and Omega(15N) - Omega(13C'), or at Omega(15N) + Omega(13Calpha) and Omega(15N) - Omega(13Calpha), to break backbone 15N,1HN chemical shift degeneracy. Sequential connectivities are established along a second GFT dimension by measuring intraresidue and sequential correlations at 2Omega(13Calpha), Omega(13Calpha + 13Cbeta), and Omega(13Calpha - 13Cbeta), or at Omega(13Calpha + 1Halpha) and Omega(13Calpha - 1Halpha), to resolve 13Calpha/beta,1Halpha chemical shift degeneracy. It is demonstrated that longitudinal proton relaxation optimization of out-and-back implementations suitable for deuterated proteins and nonlinear data sampling combined with maximum entropy reconstruction further accelerate G2FT NMR data acquisition speed. As a result, the spectral information can be obtained within hours, so that (5,3)D G2FT experiments are viable options for high-throughput structure determination in structural genomics. Applications are presented for 17 kDa alpha-helical protein YqbG and 13.5 kDa protein rps24e, targets of the Northeast Structural Genomics consortium, as well as for 9 kDa protein Z-domain. The high resolving power of the G2FT NMR experiments makes them attractive choices to study alpha-helical globular/membrane or (partially) unfolded proteins, thus promising to pave the way for NMR-based structural genomics of membrane proteins.

Rapid NMR data collection

Rapid data collection is an area of intense research in biomolecular NMR spectroscopy, in particular for high-throughput structure determination in structural genomics. NMR data acquisition and processing protocols for rapidly obtaining high-dimensional spectral information aim at avoiding sampling limited data collection and are reviewed here with emphasis on G-matrix Fourier transform NMR spectroscopy.

An integrated platform for automated analysis of protein NMR structures

Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.

A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra

We present an algorithm and program called Pattern Picker that performs editing of raw peak lists derived from multidimensional NMR experiments with characteristic peak patterns. Pattern Picker detects groups of correlated peaks within peak lists from reduced dimensionality triple resonance (RD-TR) NMR spectra, with high fidelity and high yield. With typical quality RD-TR NMR data sets, Pattern Picker performs almost as well as human analysis, and is very robust in discriminating real peak sets from noise and other artifacts in unedited peak lists. The program uses a depth-first search algorithm with short-circuiting to efficiently explore a search tree representing every possible combination of peaks forming a group. The Pattern Picker program is particularly valuable for creating an automated peak picking/editing process. The Pattern Picker algorithm can be applied to a broad range of experiments with distinct peak patterns including RD, G-matrix Fourier transformation (GFT) NMR spectra, and experiments to measure scalar and residual dipolar coupling, thus promoting the use of experiments that are typically harder for a human to analyze. Since the complexity of peak patterns becomes a benefit rather than a drawback, Pattern Picker opens new opportunities in NMR experiment design.

G-matrix Fourier transform NMR spectroscopy for complete protein resonance assignment

A G-matrix Fourier transform (GFT) NMR spectroscopy-based strategy for resonance assignment of proteins is described. Each of the GFT NMR experiments presented here rapidly affords four-, five-, or six-dimensional spectral information in combination with precise measurements of chemical shifts. The resulting high information content enables one to obtain nearly complete assignments by using only four NMR experiments. For the backbone amide proton detected "out-and-back" experiments, data collection was further accelerated up to approximately 2.5-fold by use of longitudinal (1)H relaxation optimization. The GFT NMR experiments were acquired for three proteins with molecular masses ranging from 8.6 to 17 kDa, demonstrating that the proposed strategy is of key interest for automated resonance assignment in structural genomics.

DEPT spectral editing in HCCONH-type experiments. Application to fast protein backbone and side chain assignment

2D DEPT-H(alpha,beta)C(alpha,beta)(CO)NH and 2D CT-DEPT-HC(CO)NH-TOCSY experiments are presented which allow fast resonance assignment of aliphatic protein side chains. In these 2D reduced-dimensionality experiments, two or three nuclei are frequency labeled in the indirect dimension. DEPT spectral editing reduces the number of correlation peaks detected in each 2D spectrum, and helps in amino-acid-type determination during sequential backbone resonance assignment. Applications are shown for a small 68-residue, and a highly deuterated 167-residue protein. The new experiments complement the set of 2D HNX correlation experiments, previously proposed for fast protein resonance assignment [J. Biomol. NMR, 27 (2003) 57].

GFT NMR, a new approach to rapidly obtain precise high-dimensional NMR spectral information

Widely used higher-dimensional Fourier transform (FT) NMR spectroscopy suffers from two major drawbacks: (i) The minimal measurement time of an N-dimensional FT NMR experiment, which is constrained by the need to sample N - 1 indirect dimensions, may exceed by far the measurement time required to achieve sufficient signal-to-noise ratios. (ii) The low resolution in the indirect dimensions severely limits the precision of the indirect chemical shift measurements. To relax on constraints arising from these drawbacks, we present here an acquisition scheme which is based on the phase-sensitive joint sampling of the indirect dimensions spanning a subspace of a conventional NMR experiment. This allows one to very rapidly obtain high-dimensional NMR spectral information. Because the phase-sensitive joint sampling yields subspectra containing "chemical shift multiplets", alternative data processing is required for editing the components of the multiplets. The subspectra are linearly combined using a so-called "G-matrix" and subsequently Fourier-transformed. The chemical shifts are multiply encoded in the resonance lines constituting the shift multiplets. This corresponds to performing statistically independent multiple measurements, and the chemical shifts can thus be obtained with high precision. To indicate that a combined G-matrix and FT is employed, we named the new approach "GFT NMR spectroscopy". GFT NMR opens new avenues to establish high-throughput protein structure determination, to investigate systems with a higher degree of chemical shift degeneracy, and to study dynamic phenomena such as slow folding of biological macromolecules in greater detail.

Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment

A suite of reduced-dimensionality (13)C,(15)N,(1)H-triple-resonance NMR experiments is presented for rapid and complete protein resonance assignment. Even when using short measurement times, these experiments allow one to retain the high spectral resolution required for efficient automated analysis. "Sampling limited" and "sensitivity limited" data collection regimes are defined, respectively, depending on whether the sampling of the indirect dimensions or the sensitivity of a multidimensional NMR experiments per se determines the minimally required measurement time. We show that reduced-dimensionality NMR spectroscopy is a powerful approach to avoid the "sampling limited regime"--i.e., a standard set of ten experiments proposed here allows one to effectively adapt minimal measurement times to sensitivity requirements. This is of particular interest in view of the greatly increased sensitivity of NMR spectrometers equipped with cryogenic probes. As a step toward fully automated analysis, the program AUTOASSIGN has been extended to provide sequential backbone and (13)C(beta) resonance assignments from these reduced-dimensionality NMR data.

Efficient measurement of (3)J(N,Cgamma) and (3)J(C',Cgamma) coupling constants of aromatic residues in (13)C, (15)N-labeled proteins

An NMR pulse sequence is proposed for the simultaneous determination of side chain chi1 torsion-angle related (3)J(N,Cgamma) and (3)J(C', Cgamma) couplings in aromatic amino acid spin systems. The method is of the quantitative J correlation type and takes advantage of attenuated (15)N and (1)H transverse relaxation by means of the TROSY principle. Unlike previously developed schemes for the measurement of either of the two coupling types, spectra contain internal reference peaks that are usually recorded in separate experiments. Therefore, the desired information is extracted from a single rather than four data sets. The new method is demonstrated with uniformly (13)C/(15)N labeled Desulfovibrio vulgaris flavodoxin, which contains 14 aromatic out of 147 total amino acid residues.

NMR scalar couplings across Watson-Crick base pair hydrogen bonds in DNA observed by transverse relaxation-optimized spectroscopy

This paper describes the NMR observation of 15N---15N and 1H---15N scalar couplings across the hydrogen bonds in Watson-Crick base pairs in a DNA duplex, hJNN and hJHN. These couplings represent new parameters of interest for both structural studies of DNA and theoretical investigations into the nature of the hydrogen bonds. Two dimensional [15N,1H]-transverse relaxation-optimized spectroscopy (TROSY) with a 15N-labeled 14-mer DNA duplex was used to measure hJNN, which is in the range 6-7 Hz, and the two-dimensional hJNN-correlation-[15N,1H]-TROSY experiment was used to correlate the chemical shifts of pairs of hydrogen bond-related 15N spins and to observe, for the first time, hJHN scalar couplings, with values in the range 2-3.6 Hz. TROSY-based studies of scalar couplings across hydrogen bonds should be applicable for large molecular sizes, including protein-bound nucleic acids.