Non-Uniform Sampling for Quantitative NOESY.

Non-uniform sampling (NUS) enables faster acquisition of NMR spectra. Concerns about spectral fidelity, particularly in high-dynamic-range experiments like NOESY, have limited its quantitative applications. In this study, we assessed whether optimised Poisson-gap sampling schemes can generate high-fidelity spectra suitable for quantitation and evaluated the effectiveness of NUS ranking tools, NUSscore and nus-tool, in identifying optimal sampling schemes. A total of 25,000 Poisson-gap sampling schemes were generated and ranked using NUSscore, with a subset of 11 of these spanning the score distribution, alongside 15 random-shuffle and the highest and lowest scoring Poisson-gap schemes determined using the signal apex-to-artefact ratio were used for comparison, all with 50% sampling coverage. Additionally, hybrid sampling schemes incorporating a long initial uniformly sampled section, termed US-NUS hybrid schemes, were evaluated. Spectral fidelity was evaluated on interproton distance accuracy, including the proportion of retained interproton distances and their deviation from uniformly sampled reference spectra. NUSscore showed a strong correlation with spectral fidelity. The peak-to-sidelobe ratio implemented in nus-tool showed no correlation, with the relative sensitivity metric showing a weak correlation. Signal-to-artefact apex ratio was also not predictive for identifying sampling schedules with maintained interproton distances. All Poisson-gap sampling schemes however outperformed random-shuffle. The US-NUS hybrids demonstrated improved interproton distance conservation than traditional Poisson-gap sampling schemes with a low seed dependence, making them a promising sampling schedule for quantitative NOESY analysis.