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[en] A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.
[en] Characterization of the chemical components of complex mixtures in solution is important in many areas of biochemistry and chemical biology, including metabolomics. The use of 2D NMR total correlation spectroscopy (TOCSY) experiments has proven very useful for the identification of known metabolites as well as for the characterization of metabolites that are unknown by taking advantage of the good resolution and high sensitivity of this homonuclear experiment. Due to the complexity of the resulting spectra, automation is critical to facilitate and speed-up their analysis and enable high-throughput applications. To better meet these emerging needs, an automated spin-system identification algorithm of TOCSY spectra is introduced that represents the cross-peaks and their connectivities as a mathematical graph, for which all subgraphs are determined that are maximal cliques. Each maximal clique can be assigned to an individual spin system thereby providing a robust deconvolution of the original spectrum for the easy extraction of critical spin system information. The approach is demonstrated for a complex metabolite mixture consisting of 20 compounds and for E. coli cell lysate.
[en] The use of small rotors capable of very fast magic-angle spinning (MAS) in conjunction with proton dilution by perdeuteration and partial reprotonation at exchangeable sites has enabled the acquisition of resolved, proton detected, solid-state NMR spectra on samples of biological macromolecules. The ability to detect the high-gamma protons, instead of carbons or nitrogens, increases sensitivity. In order to achieve sufficient resolution of the amide proton signals, rotors must be spun at the maximum rate possible given their size and the proton back-exchange percentage tuned. Here we investigate the optimal proton back-exchange ratio for triply labeled SH3 at 40 kHz MAS. We find that spectra acquired on 60 % back-exchanged samples in 1.9 mm rotors have similar resolution at 40 kHz MAS as spectra of 100 % back-exchanged samples in 1.3 mm rotors spinning at 60 kHz MAS, and for (H)NH 2D and (H)CNH 3D spectra, show 10–20 % higher sensitivity. For 100 % back-exchanged samples, the sensitivity in 1.9 mm rotors is superior by a factor of 1.9 in (H)NH and 1.8 in (H)CNH spectra but at lower resolution. For (H)C(C)NH experiments with a carbon–carbon mixing period, this sensitivity gain is lost due to shorter relaxation times and less efficient transfer steps. We present a detailed study on the sensitivity of these types of experiments for both types of rotors, which should enable experimentalists to make an informed decision about which type of rotor is best for specific applications
[en] NMR spectra of large RNAs are difficult to assign because of extensive spectral overlap and unfavorable relaxation properties. Here we present a new approach to facilitate assignment of RNA spectra using a suite of four 2D-filtered/edited NOESY experiments in combination with base-type-specific isotopically labeled RNA. The filtering method was developed for use in 3D filtered NOESY experiments (Zwahlen et al., 1997), but the 2D versions are both more sensitive and easier to interpret for larger RNAs than their 3D counterparts. These experiments are also useful for identifying intermolecular NOEs in RNA-protein complexes. Applications to NOE assignment of larger RNAs and an RNA-protein complex are presented
[en] Here we describe a new algorithm for automatically determining the mainchain sequential assignment of NMR spectra for proteins. Using only the customary triple resonance experiments, assignments can be quickly found for not only small proteins having rather complete data, but also for large proteins, even when only half the residues can be assigned. The result of the calculation is not the single best assignment according to some criterion, but rather a large number of satisfactory assignments that are summarized in such a way as to help the user identify portions of the sequence that are assigned with confidence, vs. other portions where the assignment has some correlated alternatives. Thus very imperfect initial data can be used to suggest future experiments.
[en] In order to reduce the acquisition time of multidimensional NMR spectra of biological macromolecules, projected spectra (or in other words, spectra sampled in polar coordinates) can be used. Their standard processing involves a regular FFT of the projections followed by a reconstruction, i.e. a non-linear process. In this communication, we show that a 2D discrete Fourier transform can be implemented in polar coordinates to obtain directly a frequency domain spectrum. Aliasing due to local violations of the Nyquist sampling theorem gives rise to base line ridges but the peak line-shapes are not distorted as in most reconstruction methods. The sampling scheme is not linear and the data points in the time domain should thus be weighted accordingly in the polar FT; however, artifacts can be reduced by additional data weighting of the undersampled regions. This processing does not require any parameter tuning and is straightforward to use. The algorithm written for polar sampling can be adapted to any sampling scheme and will permit to investigate better compromises in terms of experimental time and lack of artifacts