2. Academic Validation
  3. Exploration of the anti-inflammatory mechanism of Lanqin oral solution based on the network pharmacology analysis optimized by Q-markers selection

Exploration of the anti-inflammatory mechanism of Lanqin oral solution based on the network pharmacology analysis optimized by Q-markers selection

  • Comput Biol Med. 2023 Jan 23;154:106607. doi: 10.1016/j.compbiomed.2023.106607.
Hui Ma 1,  Weiliang Fu 1,  Hengyuan Yu 1,  Youdong Xu 2,  Lulu Xiao 1,  Yiwei Zhang 1,  Yongjiang Wu 1,  Xuesong Liu 1,  Yong Chen 3,  Tengfei Xu 4
Affiliations

Affiliations

  • 1 College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
  • 2 National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, 102206, China.
  • 3 College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China. Electronic address: [email protected].
  • 4 College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China. Electronic address: [email protected].
PMID: 36731363 DOI: 10.1016/j.compbiomed.2023.106607
Abstract

Network pharmacology is widely used to predict the mechanism of traditional Chinese medicines (TCM), but the framework in traditional network pharmacology analysis ignores the relationship between the concentration of components and drug efficacy. Lanqin oral solution (LOS) is a TCM formulation that widely used in the clinical treatment of pharyngitis, but its pharmacodynamic mechanism is still unknown. The present study was designed to elaborate the anti-inflammatory mechanism of LOS based on the quality markers (Q-markers). The efficacy of LOS was correlated with the fingerprint common peaks by chemometrics to select key peaks, and the Q-markers were further confirmed by mass spectrometry. Network pharmacology analysis was performed based on the chosen Q-markers to elaborate the potential pharmacodynamic mechanisms. Four efficacy-related chromatographic peaks were screened by the novel competitive adaptive reweighted sampling (CARS) spectrum-effect relationship analysis and series of other chemometrics methods. Four peaks were further characterized as the Q-markers in the LOS by mass spectrometry, i.e., geniposide, berberine, palmatine and baicalin. The ingredient-target network demonstrated that the LOS showed more impact on the NF-κB signaling pathway to elicit anti-inflammatory ability. Overall, the present study has introduced CARS into the spectrum-effect relationship analysis for the first time, which complemented the commonly applied chemometric methods. The network established based on the screened Q-markers was highly interpretable and successfully achieved the prediction of the anti-inflammatory mechanism of LOS. The proposed workflow provides a systematic method for exploring the mechanism of TCM based on identifying efficacy indicators. More importantly, it offers a reference for clarifying the mechanisms for other TCM formulations.

Keywords

Anti-inflammatory; Competitive adaptive reweighted sampling; Lanqin oral solution; Network pharmacology; Q-marker; Spectrum-effect relationship.

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