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Planta Med 2021; 87(12/13): 1061-1068
DOI: 10.1055/a-1470-0446
Natural Product Chemistry and Analytical Studies
Original Papers

13C NMR Dereplication Using MixONat Software: A Practical Guide to Decipher Natural Products Mixtures[ # ]

Antoine Bruguière
1   Univ Angers, SONAS, SFR QUASAV, Faculty of Health Sciences, Dpt Pharmacy, Angers, France
,
Séverine Derbré
1   Univ Angers, SONAS, SFR QUASAV, Faculty of Health Sciences, Dpt Pharmacy, Angers, France
,
Dimitri Bréard
1   Univ Angers, SONAS, SFR QUASAV, Faculty of Health Sciences, Dpt Pharmacy, Angers, France
,
Félix Tomi
2   Université de Corse-CNRS, UMR 6134 SPE, Equipe Chimie et Biomasse, Ajaccio, France
,
Jean-Marc Nuzillard
3   Université de Reims Champagne Ardenne, CNRS, ICMR UMR 7312, Reims, France
,
Pascal Richomme
1   Univ Angers, SONAS, SFR QUASAV, Faculty of Health Sciences, Dpt Pharmacy, Angers, France
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Abstract

The growing use of herbal medicines worldwide requires ensuring their quality, safety, and efficiency to consumers and patients. Quality controls of vegetal extracts are usually undertaken according to pharmacopeial monographs. Analyses may range from simple chemical experiments to more sophisticated but more accurate methods. Nowadays, metabolomic analyses allow a fast characterization of complex mixtures. In the field, besides mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR) has gained importance in the direct identification of natural products in complex herbal extracts. For a decade, automated dereplication processes based on 13C-NMR have been emerging to efficiently identify known major compounds in mixtures. Though less sensitive than MS, 13C-NMR has the advantage of being appropriate to discriminate stereoisomers. Since NMR spectrometers nowadays provide useful datasets in a reasonable time frame, we have recently made available MixONat, a software that processes 13C as well as distortionless enhancement by polarization transfer (DEPT)-135 and -90 data, allowing carbon multiplicity (i.e., CH3, CH2, CH, and C) filtering as a critical step. MixONat requires experimental or predicted chemical shifts (δ C) databases and displays interactive results that can be refined based on the userʼs phytochemical knowledge. The present article provides step-by-step instructions to use MixONat starting from database creation with freely available and/or marketed δ C datasets. Then, for training purposes, the reader is led through a 30 – 60 min procedure consisting of the 13C-NMR based dereplication of a peppermint essential oil.

Key words

database - essential oils - Lamiaceae - Mentha piperita - MixONat - 13C-NMR-based dereplication

# Dedicated to Professor Arnold Vlietinck on the occasion of his 80th birthday.


Supporting Information

    Additional figures including GC-MS chromatogram, NMR spectra, screenshots of MixONat tabs, and obtained results as well as practical processes are available in Supporting Information. A table comparing predicted and experimental δ C for each major monoterpene of peppermint EO is also included.

  • Supporting Information

    Example datasets:

    For training purposes, all NMR spectra (fid and .mnova; Peppermint EO_Carbon-1 – 1.jdf, Peppermint EO_DEPT90deg-1 – 1.jdf, Peppermint EO_DEPT135deg-1 – 1.jdf, Mint EO.mnova), peak lists (.csv; Peppermint EO 13C.csv, Peppermint EO DEPT 90.csv, Peppermint EO DEPT 135.csv, Peppermint EO Minor 13C.csv, Peppermint EO Minor DEPT 90.csv, Peppermint EO Minor DEPT 135.csv) files, and DBs (.sdf; c_type_Lamiaceae DB2.SDF, c_type_Lamiaceae DB3.SDF, c_type_Lamiaceae DB4.SDF, c_type_Mentha DB1.SDF) used in the present paper are accessible in Supporting Information.

  • Data Files


Publication History

Received: 29 January 2021

Accepted after revision: 25 March 2021

Article published online:
06 May 2021

© 2021. Thieme. All rights reserved.

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