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(es)

Mannochio-Russo, Helena ^{[1, 2]} ; Bueno, Paula Carolina P. ^{[3, 4]} ; Bauermeister, Anelize ^{[1, 5]} ; de Almeida, Rafael Felipe ^[6] ; Dorrestein, Pieter C. ^[1] ; Cavalheiro, Alberto Jose ^[2] ; Bolzani, Vanderlan S. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Calif San Diego, Collaborat Mass Spectrometry Innovat Ctr, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 - USA

^[2] Sao Paulo State Univ UNESP, NuBBE, Dept Biochem & Organ Chem, Inst Chem, BR-14800901 Araraquara, SP - Brazil

^[3] Max Planck Inst Mol Plant Physiol, D-14476 Potsdam - Germany

^[4] Univ Sao Paulo, Fac Pharmaceut Sci Ribeirao Preto, Dept Phys & Chem, BR-14049900 Ribeirao Preto, SP - Brazil

^[5] Univ Sao Paulo, Biomed Sci Inst, BR-05508900 Sao Paulo, SP - Brazil

^[6] Feira de Santana State Univ UEFS, Dept Biol Sci, Lamol Lab, BR-44036900 Feira De Santana, BA - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Journal of Natural Products; v. 83, n. 11, p. 3239-3249, NOV 25 2020.
• Citações Web of Science: 2

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. (AU)

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