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.


Journal

Journal of natural products
ISSN: 1520-6025
Titre abrégé: J Nat Prod
Pays: United States
ID NLM: 7906882

Informations de publication

Date de publication:
25 11 2020
Historique:
pubmed: 17 11 2020
medline: 28 10 2021
entrez: 16 11 2020
Statut: ppublish

Résumé

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

Identifiants

pubmed: 33196207
doi: 10.1021/acs.jnatprod.0c00495
doi:

Substances chimiques

Biological Products 0
Plant Extracts 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3239-3249

Auteurs

Helena Mannochio-Russo (H)

NuBBE, Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University (UNESP), 14800-901, Araraquara, SP Brazil.
Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States.

Paula Carolina P Bueno (PCP)

Faculty of Pharmaceutical Sciences of Ribeirão Preto, Department of Physics and Chemistry, University of São Paulo, 14049-900, Ribeirão Preto, SP Brazil.
Max Planck Institute of Molecular Plant Physiology, 14476, Potsdam-Golm, Germany.

Anelize Bauermeister (A)

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States.
Biomedical Sciences Institute, University of São Paulo, 05508-900 São Paulo, SP Brazil.

Rafael Felipe de Almeida (RF)

Department of Biological Sciences, Lamol Lab, Feira de Santana State University (UEFS), Feira de Santana, BA 44036-900, Brazil.

Pieter C Dorrestein (PC)

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States.

Alberto José Cavalheiro (AJ)

NuBBE, Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University (UNESP), 14800-901, Araraquara, SP Brazil.

Vanderlan S Bolzani (VS)

NuBBE, Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University (UNESP), 14800-901, Araraquara, SP Brazil.

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