ABSTRACT
Objective: Based on the idea of Q-marker, UPLC-Q-TOF-MS, GC-MS and network pharmacology techniques were used to establish a potential Q-Marker component library associated with the core efficacy of Zhangbang Aurantii Fructus with honeyed bran, in order to lay the foundation for exploring the establishment of pieces quality standards. Methods: Chromatography separation was achieved on an Acquity UPLC BEH C18 column (100 mm × 2.1 mm, 1.7 μm), and eluted with a gradient of methanol-water containing 0.1% formic acid. Data acquisition was carried out in electrospray ionization (ESI) under the positive ion mode, the scanning range was 50-1 200 m/z. Ingredients in alcohol extract of Aurantii Fructus with honeyed bran were identified according to reference substance, relative molecular weight, mass spectrometric cleavage rule and literature information; The volatile oil and aromatic water was extracted by steam distillation and analyzed by gas chromatography-mass spectrometry (GC-MS). The inlet temperature was 260 ℃, the transmission line temperature was 250 ℃, the carrier gas was helium, the flow rate was 1.0 mL/min, the split ratio was 10:1, the injection volume was 1 μL; The program temperature was 70 ℃ for the starting column, 2 ℃/min to 150 ℃ for 2 min, 6 ℃/min to 240 ℃ for 3 min, and then 25 ℃/min to 300 ℃ for 2 min. Mass spectrometry was identified by NIST08 standard mass spectrometry library to identify chemical constituents; Cytoscape 3.7.1 was used to construct a “pieces-compounds-diseases-targets” network of chemical constituents and functional dyspepsia in Aurantii Fructus with honeyed bran. Results: A total of 55 chemical components were identified by UPLC-Q-TOF-MS, and 63 chemical components were identified by GC-MS. Naringin, neohesperidin, eriodictyol-7-O-glucoside, naringenin, limonin, nobiletin, hesperitin, 5-hydroxy- 6,7,8,4’-tetramethoxyflavone, didymin, D-limonene, cymene, γ-terpinene nomilin, (1R)-(+)-α-pinene, caffeic acid and synephrine can be used as a Q-marker ingredient library for Aurantii Fructus with honeyed bran. Conclusion: UPLC-Q-TOF-MS and GC-MS can quickly and qualitatively analyze the chemical constituents in the pieces. The network pharmacology can predict the potential Q-marker library related to efficacy of regulating vital energy and eliminating flatulence, and provide the basis for the establishment of quality standards for the pieces.