A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations

Abstract Although understanding their chemical composition is vital for accurately predicting the bioactivity of multicomponent drugs, nutraceuticals, and foods, no analytical approach exists to easily predict the bioactivity of multicomponent systems from complex behaviors of multiple coexisting fa...

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Autores principales:	Yoshinori Fujimura, Chihiro Kawano, Ayaka Maeda-Murayama, Asako Nakamura, Akiko Koike-Miki, Daichi Yukihira, Eisuke Hayakawa, Takanori Ishii, Hirofumi Tachibana, Hiroyuki Wariishi, Daisuke Miura
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1df2176e02e6451f82180dd92065cfd9
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spelling	oai:doaj.org-article:1df2176e02e6451f82180dd92065cfd92021-12-02T16:06:43ZA Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations10.1038/s41598-017-02499-12045-2322https://doaj.org/article/1df2176e02e6451f82180dd92065cfd92017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-02499-1https://doaj.org/toc/2045-2322Abstract Although understanding their chemical composition is vital for accurately predicting the bioactivity of multicomponent drugs, nutraceuticals, and foods, no analytical approach exists to easily predict the bioactivity of multicomponent systems from complex behaviors of multiple coexisting factors. We herein represent a metabolic profiling (MP) strategy for evaluating bioactivity in systems containing various small molecules. Composition profiles of diverse bioactive herbal samples from 21 green tea extract (GTE) panels were obtained by a high-throughput, non-targeted analytical procedure. This employed the matrix-assisted laser desorption ionization–mass spectrometry (MALDI–MS) technique, using 1,5-diaminonaphthalene (1,5-DAN) as the optical matrix for detecting GTE-derived components. Multivariate statistical analyses revealed differences among the GTEs in their antioxidant activity, oxygen radical absorbance capacity (ORAC). A reliable bioactivity-prediction model was constructed to predict the ORAC of diverse GTEs from their compositional balance. This chemometric procedure allowed the evaluation of GTE bioactivity by multicomponent rather than single-component information. The bioactivity could be easily evaluated by calculating the summed abundance of a few selected components that contributed most to constructing the prediction model. 1,5-DAN-MALDI–MS-MP, using diverse bioactive sample panels, represents a promising strategy for screening bioactivity-predictive multicomponent factors and selecting effective bioactivity-predictive chemical combinations for crude multicomponent systems.Yoshinori FujimuraChihiro KawanoAyaka Maeda-MurayamaAsako NakamuraAkiko Koike-MikiDaichi YukihiraEisuke HayakawaTakanori IshiiHirofumi TachibanaHiroyuki WariishiDaisuke MiuraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yoshinori Fujimura Chihiro Kawano Ayaka Maeda-Murayama Asako Nakamura Akiko Koike-Miki Daichi Yukihira Eisuke Hayakawa Takanori Ishii Hirofumi Tachibana Hiroyuki Wariishi Daisuke Miura A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
description	Abstract Although understanding their chemical composition is vital for accurately predicting the bioactivity of multicomponent drugs, nutraceuticals, and foods, no analytical approach exists to easily predict the bioactivity of multicomponent systems from complex behaviors of multiple coexisting factors. We herein represent a metabolic profiling (MP) strategy for evaluating bioactivity in systems containing various small molecules. Composition profiles of diverse bioactive herbal samples from 21 green tea extract (GTE) panels were obtained by a high-throughput, non-targeted analytical procedure. This employed the matrix-assisted laser desorption ionization–mass spectrometry (MALDI–MS) technique, using 1,5-diaminonaphthalene (1,5-DAN) as the optical matrix for detecting GTE-derived components. Multivariate statistical analyses revealed differences among the GTEs in their antioxidant activity, oxygen radical absorbance capacity (ORAC). A reliable bioactivity-prediction model was constructed to predict the ORAC of diverse GTEs from their compositional balance. This chemometric procedure allowed the evaluation of GTE bioactivity by multicomponent rather than single-component information. The bioactivity could be easily evaluated by calculating the summed abundance of a few selected components that contributed most to constructing the prediction model. 1,5-DAN-MALDI–MS-MP, using diverse bioactive sample panels, represents a promising strategy for screening bioactivity-predictive multicomponent factors and selecting effective bioactivity-predictive chemical combinations for crude multicomponent systems.
format	article
author	Yoshinori Fujimura Chihiro Kawano Ayaka Maeda-Murayama Asako Nakamura Akiko Koike-Miki Daichi Yukihira Eisuke Hayakawa Takanori Ishii Hirofumi Tachibana Hiroyuki Wariishi Daisuke Miura
author_facet	Yoshinori Fujimura Chihiro Kawano Ayaka Maeda-Murayama Asako Nakamura Akiko Koike-Miki Daichi Yukihira Eisuke Hayakawa Takanori Ishii Hirofumi Tachibana Hiroyuki Wariishi Daisuke Miura
author_sort	Yoshinori Fujimura
title	A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
title_short	A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
title_full	A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
title_fullStr	A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
title_full_unstemmed	A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations
title_sort	chemometrics-driven strategy for the bioactivity evaluation of complex multicomponent systems and the effective selection of bioactivity-predictive chemical combinations
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/1df2176e02e6451f82180dd92065cfd9
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A Chemometrics-driven Strategy for the Bioactivity Evaluation of Complex Multicomponent Systems and the Effective Selection of Bioactivity-predictive Chemical Combinations

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