Rapid identification of chemical constituents of Liaogu Formula based on UHPLC-Q-TOF-MSE combined with UNIFI platform

Abstract

Chemical components of Liaogu Formula (LGF) were analysed using ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UHPLC-Q-TOF-MSE) combined with the UNIFI platform. The analysis was conducted using an InfinityLab Poroshell 120 EC-C18 chromatography column (4.6 mm×100 mm, 2.7 μm) with a gradient elution system consisting of 0.1% formic acid aqueous solution (A) and 0.1% formic acid acetonitrile (B). Mass spectrometry data were acquired in both positive and negative ion modes using an electrospray ionisation (ESI) ion source. The UNIFI platform, reference spectra, and related literature were used for component identification. Using the UHPLC-Q-TOF-MSE technique, mass spectrometry data of the compound were acquired in both positive and negative ion modes. The precise relative molecular masses and tandem mass spectrometry data were analysed using UNIFI software, and the components were identified and inferred by comparing with reference spectra and related literature. A total of 208 chemical components were identified, including 50 terpenoids, 48 flavonoids, 41 organic acids, 21 lignans, 14 alkaloids, 14 steroids, 7 sugars, and 13 other compounds. The UHPLC-Q-TOF-MSE technique can rapidly identify chemical components in LGF with high accuracy, providing a reliable basis for studying the pharmacological foundation of its material. This integrated approach not only provides a comprehensive chemical profile of LGF but also demonstrates a robust and reproducible strategy for the systematic analysis of formulations, offering a foundation for further pharmacological and quality standardization studies.

Supplementary files

Article information

Article type
Paper
Submitted
08 Dec 2025
Accepted
02 Apr 2026
First published
06 Apr 2026

Anal. Methods, 2026, Accepted Manuscript

Rapid identification of chemical constituents of Liaogu Formula based on UHPLC-Q-TOF-MSE combined with UNIFI platform

X. Li, C. Liu, L. Ng, Q. Yu, Y. Bai and Y. Zhou, Anal. Methods, 2026, Accepted Manuscript , DOI: 10.1039/D5AY02031J

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