Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1021/acs.jnatprod.0c00495 http://hdl.handle.net/11449/206868 |
Resumo: | Proper chromatographic methods may reduce the challenges inherent in analyzing natural product extracts, especially when utilizing hyphenated detection techniques involving mass spectrometry. As there are many variations one can introduce during chromatographic method development, this can become a daunting and time-consuming task. To reduce the number of runs and time needed, the use of instrumental automatization and commercial software to apply Quality by Design and statistical analysis automatically can be a valuable approach to investigate complex matrices. To evaluate this strategy in the natural products workflow, a mixture of nine species from the family Malpighiaceae was investigated. By this approach, the entire data collection and method development procedure (comprising screening, optimization, and robustness simulation) was accomplished in only 4 days, resulting in very low limits of detection and quantification. The analysis of the individual extracts also proved the efficiency of the use of a mixture of extracts for this workflow. Molecular networking and library searches were used to annotate a total of 61 compounds, including O-glycosylated flavonoids, C-glycosylated flavonoids, quinic/shikimic acid derivatives, sterols, and other phenols, which were efficiently separated by the method developed. These results support the potential of statistical tools for chromatographic method optimization as an efficient approach to reduce time and maximize resources, such as solvents, to get proper chromatographic conditions. |
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Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family MalpighiaceaeProper chromatographic methods may reduce the challenges inherent in analyzing natural product extracts, especially when utilizing hyphenated detection techniques involving mass spectrometry. As there are many variations one can introduce during chromatographic method development, this can become a daunting and time-consuming task. To reduce the number of runs and time needed, the use of instrumental automatization and commercial software to apply Quality by Design and statistical analysis automatically can be a valuable approach to investigate complex matrices. To evaluate this strategy in the natural products workflow, a mixture of nine species from the family Malpighiaceae was investigated. By this approach, the entire data collection and method development procedure (comprising screening, optimization, and robustness simulation) was accomplished in only 4 days, resulting in very low limits of detection and quantification. The analysis of the individual extracts also proved the efficiency of the use of a mixture of extracts for this workflow. Molecular networking and library searches were used to annotate a total of 61 compounds, including O-glycosylated flavonoids, C-glycosylated flavonoids, quinic/shikimic acid derivatives, sterols, and other phenols, which were efficiently separated by the method developed. These results support the potential of statistical tools for chromatographic method optimization as an efficient approach to reduce time and maximize resources, such as solvents, to get proper chromatographic conditions.NuBBE Department of Biochemistry and Organic Chemistry Institute of Chemistry São Paulo State University (UNESP)Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San DiegoFaculty of Pharmaceutical Sciences of Ribeirão Preto Department of Physics and Chemistry University of São PauloMax Planck Institute of Molecular Plant PhysiologyBiomedical Sciences Institute University of São PauloDepartment of Biological Sciences Lamol Lab Feira de Santana State University (UEFS)NuBBE Department of Biochemistry and Organic Chemistry Institute of Chemistry São Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)San DiegoUniversidade de São Paulo (USP)Max Planck Institute of Molecular Plant PhysiologyFeira de Santana State University (UEFS)Mannochio-Russo, Helena [UNESP]Bueno, Paula Carolina P.Bauermeister, AnelizeDe Almeida, Rafael FelipeDorrestein, Pieter C.Cavalheiro, Alberto José [UNESP]Bolzani, Vanderlan S. [UNESP]2021-06-25T10:45:11Z2021-06-25T10:45:11Z2020-11-25info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3239-3249http://dx.doi.org/10.1021/acs.jnatprod.0c00495Journal of Natural Products, v. 83, n. 11, p. 3239-3249, 2020.1520-60250163-3864http://hdl.handle.net/11449/20686810.1021/acs.jnatprod.0c004952-s2.0-85096543083Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Natural Productsinfo:eu-repo/semantics/openAccess2021-10-23T15:33:32Zoai:repositorio.unesp.br:11449/206868Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T15:33:32Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
title |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
spellingShingle |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae Mannochio-Russo, Helena [UNESP] |
title_short |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
title_full |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
title_fullStr |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
title_full_unstemmed |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
title_sort |
Can Statistical Evaluation Tools for Chromatographic Method Development Assist in the Natural Products Workflow? A Case Study on Selected Species of the Plant Family Malpighiaceae |
author |
Mannochio-Russo, Helena [UNESP] |
author_facet |
Mannochio-Russo, Helena [UNESP] Bueno, Paula Carolina P. Bauermeister, Anelize De Almeida, Rafael Felipe Dorrestein, Pieter C. Cavalheiro, Alberto José [UNESP] Bolzani, Vanderlan S. [UNESP] |
author_role |
author |
author2 |
Bueno, Paula Carolina P. Bauermeister, Anelize De Almeida, Rafael Felipe Dorrestein, Pieter C. Cavalheiro, Alberto José [UNESP] Bolzani, Vanderlan S. [UNESP] |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) San Diego Universidade de São Paulo (USP) Max Planck Institute of Molecular Plant Physiology Feira de Santana State University (UEFS) |
dc.contributor.author.fl_str_mv |
Mannochio-Russo, Helena [UNESP] Bueno, Paula Carolina P. Bauermeister, Anelize De Almeida, Rafael Felipe Dorrestein, Pieter C. Cavalheiro, Alberto José [UNESP] Bolzani, Vanderlan S. [UNESP] |
description |
Proper chromatographic methods may reduce the challenges inherent in analyzing natural product extracts, especially when utilizing hyphenated detection techniques involving mass spectrometry. As there are many variations one can introduce during chromatographic method development, this can become a daunting and time-consuming task. To reduce the number of runs and time needed, the use of instrumental automatization and commercial software to apply Quality by Design and statistical analysis automatically can be a valuable approach to investigate complex matrices. To evaluate this strategy in the natural products workflow, a mixture of nine species from the family Malpighiaceae was investigated. By this approach, the entire data collection and method development procedure (comprising screening, optimization, and robustness simulation) was accomplished in only 4 days, resulting in very low limits of detection and quantification. The analysis of the individual extracts also proved the efficiency of the use of a mixture of extracts for this workflow. Molecular networking and library searches were used to annotate a total of 61 compounds, including O-glycosylated flavonoids, C-glycosylated flavonoids, quinic/shikimic acid derivatives, sterols, and other phenols, which were efficiently separated by the method developed. These results support the potential of statistical tools for chromatographic method optimization as an efficient approach to reduce time and maximize resources, such as solvents, to get proper chromatographic conditions. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-11-25 2021-06-25T10:45:11Z 2021-06-25T10:45:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1021/acs.jnatprod.0c00495 Journal of Natural Products, v. 83, n. 11, p. 3239-3249, 2020. 1520-6025 0163-3864 http://hdl.handle.net/11449/206868 10.1021/acs.jnatprod.0c00495 2-s2.0-85096543083 |
url |
http://dx.doi.org/10.1021/acs.jnatprod.0c00495 http://hdl.handle.net/11449/206868 |
identifier_str_mv |
Journal of Natural Products, v. 83, n. 11, p. 3239-3249, 2020. 1520-6025 0163-3864 10.1021/acs.jnatprod.0c00495 2-s2.0-85096543083 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Natural Products |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
3239-3249 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1799965452656443392 |