Author(s): 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]
Date: 2021
Persistent ID: http://hdl.handle.net/11449/206868
Origin: Oasisbr
Made available in DSpace on 2021-06-25T10:45:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-11-25
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.
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 Diego
Faculty of Pharmaceutical Sciences of Ribeirão Preto Department of Physics and Chemistry University of São Paulo
Max Planck Institute of Molecular Plant Physiology
Biomedical Sciences Institute University of São Paulo
Department 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)
