Computer-Aided 13C NMR Chemical Profiling of Crude Natural Extracts without Fractionation.
Ali BakiriJane HubertRomain ReynaudSylvie LanthonyDominique HarakatJean-Hugues RenaultJean-Marc NuzillardPublished in: Journal of natural products (2017)
A computer-aided, 13C NMR-based dereplication method is presented for the chemical profiling of natural extracts without any fractionation. An algorithm was developed in order to compare the 13C NMR chemical shifts obtained from a single routine spectrum with a set of predicted NMR data stored in a natural metabolite database. The algorithm evaluates the quality of the matching between experimental and predicted data by calculating a score function and returns the list of metabolites that are most likely to be present in the studied extract. The proof of principle of the method is demonstrated on a crude alkaloid extract obtained from the leaves of Peumus boldus, resulting in the identification of eight alkaloids, including isocorydine, rogersine, boldine, reticuline, coclaurine, laurotetanine, N-methylcoclaurine, and norisocorydine, as well as three monoterpenes, namely, p-cymene, eucalyptol, and α-terpinene. The results were compared to those obtained with other methods, either involving a fractionation step before the chemical profiling process or using mass spectrometry detection in the infusion mode or coupled to gas chromatography.
Keyphrases
- mass spectrometry
- high resolution
- solid state
- gas chromatography
- magnetic resonance
- single cell
- machine learning
- tandem mass spectrometry
- oxidative stress
- deep learning
- electronic health record
- big data
- liquid chromatography
- low dose
- high resolution mass spectrometry
- high performance liquid chromatography
- ms ms
- emergency department
- anti inflammatory
- gas chromatography mass spectrometry
- quality improvement
- solid phase extraction
- label free
- simultaneous determination