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构建并应用定量构效关系方法识别黄酮类化合物。

Construction and application of a QSRR approach for identifying flavonoids.

机构信息

College of Pharmacy, Jiamusi University, P.O. Box 154007, China.

College of Pharmacy, Jiamusi University, P.O. Box 154007, China; Shenyang Pharmaceutical University, P.O. Box 117004, China.

出版信息

J Pharm Biomed Anal. 2024 Mar 15;240:115929. doi: 10.1016/j.jpba.2023.115929. Epub 2023 Dec 21.

Abstract

A quantitative structure retention relationship (QSRR) method was developed to identify flavonoid isomers auxiliary using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method based on the linear relationships between the Ln(k') values of flavonoids and their hydrogen bonding energy (X) and dissolution energy (E). Chromatographic separation was achieved with a Hypersil GOLD C18 (100 mm × 2.1 mm, 1.9 µm) column and Agilent SB-C18 (2.1 ×50 mm, 1.8 µm) column on a Dionex Ultimate 3000 RSLC chromatograph. Compounds were eluted isocratically using a mobile phase containing 0.1% formic acid/water solution and methanol at a ratio of 55:45 (v/v). Mass spectrometry was performed in the negative and positive ionization modes on a Thermo Fisher Q Exactive Orbitrap mass spectrometer equipped with an electrospray ionization interface. The established QSRR model was Ln(k') = 5.6163 + 0.0469E - 0.0984X with a determination coefficient (R) of 0.9981, adjusted determination coefficient (adjR) of 0.9976, and corrected root mean square error of 0.0682. The determination coefficient of the leave-one-out (LOO) cross-validation (Q) was 0.9976, and the cross-verification root mean square error was 0.0754. Simulated samples containing 7 flavonoids were used to validate the feasibility of the method. The classical method (UHPLC-MS/MS combined the CD software and the mzCloud, mzVault and Chemspider databases) was used to identify the seven flavonoids in the simulated samples. This classic identification strategy cannot provide accurate identification results, which provided multiple identification results for each compound in the simulated samples. On the basis of the results, the 7 flavonoids were accurately identified by the established QSRR model, and the reference standards were used to validate it. The relative error of retention time(RE(t)) between the model calculation and experimental results was less than 10%. This method effectively complements and improves the classical methods, that UHPLC-MS/MS combined the CD software and the mass spectra databases were used to identify flavonoids identification.

摘要

建立了一种基于黄酮类化合物的线性关系ln(k')与其氢键能(X)和溶解能(E)之间的定量结构保留关系(QSRR)方法,利用超高效液相色谱-串联质谱(UHPLC-MS/MS)法对黄酮类异构体辅助物进行鉴定。在 Dionex Ultimate 3000 RSLC 色谱仪上,使用 Hypersil GOLD C18(100mm×2.1mm,1.9μm)柱和 Agilent SB-C18(2.1×50mm,1.8μm)柱,以 0.1%甲酸/水溶液和甲醇的 55:45(v/v)比例进行等度洗脱来实现化合物的分离。采用配有电喷雾接口的 Thermo Fisher Q Exactive Orbitrap 质谱仪在正负离子模式下进行质谱分析。所建立的 QSRR 模型为 ln(k')=5.6163+0.0469E-0.0984X,决定系数(R)为 0.9981,调整决定系数(adjR)为 0.9976,校正均方根误差为 0.0682。留一法(LOO)交叉验证(Q)的决定系数为 0.9976,交叉验证均方根误差为 0.0754。使用含有 7 种黄酮类化合物的模拟样品验证了该方法的可行性。经典方法(UHPLC-MS/MS 结合 CD 软件和 mzCloud、mzVault 和 Chemspider 数据库)用于鉴定模拟样品中的 7 种黄酮类化合物。这种经典的鉴定策略不能提供准确的鉴定结果,它为模拟样品中的每个化合物提供了多个鉴定结果。在此基础上,利用所建立的 QSRR 模型准确鉴定了 7 种黄酮类化合物,并采用对照品进行了验证。模型计算与实验结果之间的保留时间相对误差(RE(t))小于 10%。该方法有效地补充和改进了经典方法,即 UHPLC-MS/MS 结合 CD 软件和质谱数据库用于鉴定黄酮类化合物。

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