Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data

Abstract

Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.

Discovery of stimulator binding to a conserved pocket in the heme domain of soluble guanylyl cyclase

“…To prepare the sample, the isotopically labeled Sw H-NOX was treated with 10 mM dithionite in an extensively degassed buffer containing 50 mM Tris-HCl (pH 8.0), 50 mM NaCl, and then saturated with CO in a sealed tube. Dithionite was removed by buffer-exchange to an extensively degassed, then CO-saturated buffer containing 50 mM sodium/potassium phosphate (pH 7.5), 50 Protein backbone resonance assignmentAll backbone and side-chain resonance experiments were acquired using 40-50% nonuniformly sampling (38,39) , (40). Sequencespecific backbone resonance assignments were determined using the following triple resonance experiments: 3D-HNCA (44), 3D-HN(CO)CA, 3D-HNCACB (44), 3D-CBCA(CO)NH, 3D-HNCO, and 3D-(HCA)CO(CA)NH.…”

Monitoring 15N Chemical Shifts During Protein Folding by Pressure-Jump NMR

“…(A, B) Small region of the HSQC spectrum, recorded with the scheme of Figure 1 for τ = 10 ms and κ = 2 ms, modulated by (A) cos(ω N κ) and (B) sin(ω N κ). Extension of the 50-ms t 1 time domain to 75 ms by the NUS reconstruction program SMILE 34 was used to slightly increase both resolution and sensitivity. Negative intensity is shown in brown.…”

An engineered transforming growth factor β (TGF-β) monomer that functions as a dominant negative to block TGF-β signaling

“…The T 2 relaxation times were obtained by fitting relative peak intensities as a function of the T 2 delay time to a two-parameter decaying exponential. Data were processed using NMRPipe (54), with the SMILE algorithm used for prediction of the missing points in the 13 C and 15 N dimensions of the non-uniform sampling data sets (55). Data analysis was performed using NMRFAM-SPARKY (56).…”