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.
J Nat Prod. 2020 Nov 25;83(11):3239-3249. doi: 10.1021/acs.jnatprod.0c00495. Epub 2020 Nov 16.
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 -glycosylated flavonoids, -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.
适当的色谱方法可以降低分析天然产物提取物所固有的挑战,特别是在利用涉及质谱的键合检测技术时。由于在开发色谱方法时可以引入许多变化,因此这可能成为一项艰巨且耗时的任务。为了减少运行次数和所需的时间,可以使用仪器自动化和商业软件自动应用质量源于设计和统计分析,这是一种研究复杂基质的有价值的方法。为了在天然产物工作流程中评估这种策略,研究了来自大戟科的九种混合物种。通过这种方法,仅用 4 天就完成了整个数据收集和方法开发过程(包括筛选、优化和稳健性模拟),从而实现了非常低的检测限和定量限。对各个提取物的分析也证明了使用混合提取物进行此工作流程的效率。分子网络和库搜索用于注释总共 61 种化合物,包括 -糖苷化黄酮类、-糖苷化黄酮类、奎宁/莽草酸衍生物、甾醇和其他酚类化合物,这些化合物都可以通过开发的方法有效分离。这些结果支持统计工具在色谱方法优化中的潜力,这是一种有效减少时间和最大限度利用资源(如溶剂)以获得适当色谱条件的方法。