Fiche publication
Date publication
novembre 2017
Journal
Magnetic resonance in chemistry : MRC
Auteurs
Membres identifiés du Cancéropôle Est :
Dr DELSUC Marc-André
Tous les auteurs :
Margueritte L, Markov P, Chiron L, Starck JP, Vonthron-Sénécheau C, Bourjot M, Delsuc MA
Lien Pubmed
Résumé
Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies.
Mots clés
automatic processing, mixture analysis, recursive feature elimination, spectral fingerprint
Référence
Magn Reson Chem. 2017 Nov 20;:
