Singular Value Decomposition for the Automated Analysis of NMR Fraction Libraries
Identifying and quantifying molecular components of biological fluids offers great potential for the diagnosis of disease, detecting environmental contaminants, and process monitoring. The use of simple 1D 1H NMR spectra to accomplish this task offers advantages in terms of broad applicability and quantitative output. However, it also encounters obstacles in extracting individual components from…
Identifying and quantifying molecular components of biological fluids, such as detecting disease, environmental contaminants, and monitoring processes, can greatly benefit from 1D 1H NMR spectra due to their broad applicability and quantitative output. However, complex superimposed spectra and limited database entries pose challenges in extracting individual components and accurately identifying compounds.
This study introduces a new protocol that uses singular value decomposition (SVD) to automatically separate component spectra and match them to database entries containing both chemical shift and scalar coupling information. The protocol was tested using a fungal extract from Neurospora crassa, which was chromatographically fractionated into a two-dimensional spectral fraction library.
The outcomes were compared to a previous analysis that relied on a semi-manual curation of separated spectra and chemical shift matching.
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