Making Accelerated NMR More Robust for Pharmaceutical Sciences
Author:
Lucille Cullen (Graduate Student)Co-Authors:
Alan Marchiori, David RovnyakFaculty Mentor(s):
David RovnyakFunding Source:
Graduate Summer Research Fellowship, Dr. Glenn A. Moser '69 Chemistry Master's Research FundAbstract
Pharmaceutical companies often face roadblocks in structure elucidation of both natural products and identification of impurities. Nuclear magnetic resonance spectroscopy (NMR) can overcome these problems in the drug discovery pipeline in a way mass spectrometry cannot by identifying absolute configuration. New technologies to accelerate structure elucidation include emerging advanced data sampling techniques like nonuniform sampling (NUS), which is powerful, but prone to artefacts. Sampling noise and aliasing artefacts are a barrier to using sparser NUS in complex 2D-NMR experiments. We find that weak aliasing artefacts are a growing concern in sparser 1D-NUS and can sometimes be misattributed to incomplete deconvolution of the broader point-spread function. As sparsity increases in NUS, we find that detrimental repeat sequences can occur early in the sampling schedule, correlating with aliasing artefacts in resulting spectra. By developing a convolutional screening approach to evaluate sampling schedules, these repeat sequences can be detected and characterized. Selecting schedules to avoid repeat sequences and using short periods of initial uniform sampling are effective at reducing these initial repeat sequences and enabling routine 25-33% 1D-NUS of challenging 2D-NMR experiments.