Laboratory of Natural Compounds Chemistry and Bioanalytics, Core Facility Center "Arktika", M.V. Lomonosov Northern (Arctic) Federal University, Northern Dvina Emb. 17, 163002 Arkhangelsk, Russia.
Molecules. 2023 Dec 15;28(24):8114. doi: 10.3390/molecules28248114.
Lignans constitute a large group of phenolic plant secondary metabolites possessing high bioactivity. Their accurate determination in plant extracts with a complex chemical composition is challenging and requires advanced separation techniques. In the present study, a new approach to the determination of lignans in coniferous knotwood extracts as the promising industrial-scale source of such compounds based on comprehensive two-dimensional liquid chromatography separation and UV spectrophotometric detection is proposed. First and second-dimension column screening showed that the best results can be obtained using a combination of non-polar and polar hydroxy group embedded octadecyl stationary phases with moderate (~40%) "orthogonality". The optimization of LC × LC separation conditions allowed for the development of a new method for the quantification of the five lignans (secoisolariciresinol, matairesinol, pinoresinol, 7-hydroxymatairesinol, and nortrachelogenin) in knotwood extracts with limits of quantification in the range of 0.27-0.95 mg L and a linear concentration range covering at least two orders of magnitude. Testing the developed method on coniferous (larch, fir, spruce, and pine) knotwood extracts demonstrated the high selectivity of the analysis and the advantages of LC × LC in the separation and accurate quantification of the compounds co-eluting in one-dimensional HPLC.
木脂素是一大类具有高生物活性的酚类植物次生代谢物。它们在化学成分复杂的植物提取物中的准确测定具有挑战性，需要先进的分离技术。本研究提出了一种新的方法，用于测定针叶木节材提取物中的木脂素，作为此类化合物有前途的工业规模来源，该方法基于全面二维液相色谱分离和紫外分光光度检测。第一维和第二维柱筛选表明，使用非极性和极性含羟基十八烷基固定相的组合，并具有适度的（约 40%）“正交性”，可以获得最佳结果。LC×LC 分离条件的优化允许开发一种新的方法，用于定量测定木节材提取物中的五种木脂素（开环异落叶松脂素、落叶松脂素、松脂醇、7-羟基落叶松脂素和新松脂酚），定量限在 0.27-0.95mg/L 范围内，线性浓度范围至少覆盖两个数量级。在针叶木（落叶松、冷杉、云杉和松树）木节材提取物上测试所开发的方法，证明了分析的高选择性和 LC×LC 在化合物共洗脱的一维 HPLC 分离和准确定量方面的优势。
