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Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling
INTRODUCTION: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden me...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394458/ https://www.ncbi.nlm.nih.gov/pubmed/30830464 http://dx.doi.org/10.1007/s11306-019-1487-4 |
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author | Freire, Rafael Teixeira Bero, Joanne Beaufay, Claire Selegato, Denise Medeiros Coqueiro, Aline Choi, Young Hae Quetin-Leclercq, Joëlle |
author_facet | Freire, Rafael Teixeira Bero, Joanne Beaufay, Claire Selegato, Denise Medeiros Coqueiro, Aline Choi, Young Hae Quetin-Leclercq, Joëlle |
author_sort | Freire, Rafael Teixeira |
collection | PubMed |
description | INTRODUCTION: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products. OBJECTIVE: Create a multivariate model to identify antiplasmodial metabolites from (1)H NMR data of two African medicinal plants, Keetia leucantha and K. venosa. METHODS: The extracts of twigs and leaves of Keetia species were measured by (1)H NMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation. RESULTS: Unsupervised (1)H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS–DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples. CONCLUSION: NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11306-019-1487-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6394458 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-63944582019-03-15 Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling Freire, Rafael Teixeira Bero, Joanne Beaufay, Claire Selegato, Denise Medeiros Coqueiro, Aline Choi, Young Hae Quetin-Leclercq, Joëlle Metabolomics Original Article INTRODUCTION: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products. OBJECTIVE: Create a multivariate model to identify antiplasmodial metabolites from (1)H NMR data of two African medicinal plants, Keetia leucantha and K. venosa. METHODS: The extracts of twigs and leaves of Keetia species were measured by (1)H NMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation. RESULTS: Unsupervised (1)H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS–DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples. CONCLUSION: NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11306-019-1487-4) contains supplementary material, which is available to authorized users. Springer US 2019-02-21 2019 /pmc/articles/PMC6394458/ /pubmed/30830464 http://dx.doi.org/10.1007/s11306-019-1487-4 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Freire, Rafael Teixeira Bero, Joanne Beaufay, Claire Selegato, Denise Medeiros Coqueiro, Aline Choi, Young Hae Quetin-Leclercq, Joëlle Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title | Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title_full | Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title_fullStr | Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title_full_unstemmed | Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title_short | Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling |
title_sort | identification of antiplasmodial triterpenes from keetia species using nmr-based metabolic profiling |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394458/ https://www.ncbi.nlm.nih.gov/pubmed/30830464 http://dx.doi.org/10.1007/s11306-019-1487-4 |
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