Automatic differential analysis of NMR experiments in complex samples

Abstract

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. KEYWORDSautomatic processing, mixture analysis, recursive feature elimination, spectral fingerprint Magn Reson Chem. 2018;56:469-479.wileyonlinelibrary.com/journal/mrc

Phytochemical analysis and anti-microbial activities of Artemisia spp. and rapid isolation methods of artemisinin

“…A highly downfield shifted methyne carbon signal at 105.4 ppm and a quaternary carbon signal at 93.7 ppm indicated the compound is highly oxygenated. The 13 C-, DEPT, 1 H -NMR spectral data of the compound was identified by comparison of its 1 H, 13 C NMR spectral data with those reported for artemisinin (Cafferata et al 2009 ; Margueritte et al 2018 ). There were different methods of extraction and purification for artemisinin.…”

Simultaneous determination of artemisinin and its analogs and flavonoids in Artemisia annua crude extracts with the use of NMR spectroscopy

“…Among the spectroscopic methods commonly used in the analysis of natural products, NMR spectroscopy is a dominant technique due to the wide range of experimental approaches that are available, the high level of structural information that is provided, and the non‐destruction of the sample . Significant effort has been given to the development of NMR methodologies that can be applied successfully to the analysis of various constituents of complex mixtures or crude plant extracts without any previous separation or isolation of the individual components . To the best of our knowledge, however, only one attempt has been made to analyze by 13 C and 1 H NMR the major components (artemisinin, camphor, and dihydroartemisinic acid) of a raw A .…”

Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

“…5.2.2 Plasmodesma: automatised pharmacophoric deconvolution. To face the avalanche of data that derives from the manual comparison of metabolomics studies or natural extracts screening, Delsuc et al developed a computer program, nicknamed Plasmodesma 93 allowing the autonomous, unsupervised processing of a large corpus of 1D and 2D NMR spectra acquired in different conditions. The capabilities of this tool were extended to be able to extract the spectral ngerprint of a molecule of interest from a set of NMR experiments through a simple linear regression, leading to pharmacophoric deconvolution.…”