Screening the effective components of Lysionotus pauciflorus Maxim. on the treatment of LPS induced acute lung injury mice by integrated UHPLC-Q-TOF-MS/MS and network pharmacology

Abstract

Ethnopharmacological relevanceAcute lung injury (ALI) is an inflammatory reaction produced through various injury-causing factors acting on the lungs in a direct or indirect way, with a high morbidity and mortality rate. A review of clinical experience has revealed that Lysionotus pauciflorus Maxim (LP) has a significant therapeutic effect on ALI. However, the comprehensive effective components of LP are uncertain, and the mechanisms, especially the potential therapeutic target for anti-ALI, are still unknown. Aims of the studyIn vitro and in vivo validation of the pharmacodynamics of LP in the treatment of ALI and exploration of its potential mechanism of action based on network pharmacology, molecular docking and experimental validation. Materials and methodsUltra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was employed to identify the ingredients of LP extracts. The potential bioactive ingredients, key targets and signalling pathways were identified by network pharmacology, based on the results of the mass spectrometry analysis. Subsequently, molecular docking was performed on the screened core components and key targets to calculate their molecular binding energies and binding potentials, and to explore the mutual binding modes of small-molecule ligands and large-molecule proteins. Finally, lipopolysaccharide (LPS)-induced RAW264.7 cell model and ALI mice model were used to validate the therapeutic effects and potential mechanism of LP extract towards ALI. ResultsFrom the mass spectrometry results of LP extracts, a total of 89 chemical components were identified, including 46 phenylethanol glycosides, 26 flavonoids, 9 organic acids and their derivatives and 8 other compounds. And furthermore 39 core active components were screened by network pharmacology. The top 10 core components (4 phenylethanol glycosides, 6 flavonoids) have been screened in the composition -target-disease network, and 37 core targets related to LP efficacy were obtained by fitting PPI network analysis. 10 signalling pathways and their targets associated with LP treatment of ALI were obtained by GO/KEGG analysis, indicating that LP could regulate TLR4 and NF-κB signalling pathways through 4 key targets, namely NFKB1, RELA, TLR4 and TNF. The results of the molecular docking procedure indicated a strong affinity, with the binding energies between each component and the target site being less than −6 kcal/mol. The binding modes included Hydrogen Bonds, Pi-Pi interaction, Hydrophobic Interactions, Salt Bridges, Pi-cation interactions. These observations were subsequently validated in vitro and in vivo experiments. The outcomes of in vitro and in vivo experiments demonstrated that LP was effective in reducing the infiltration of inflammatory bacteria in lung tissues and attenuated the expression of pro-inflammatory cytokines in LPS-stimulated mice bronchoalveolar lavage fluid (BALF) and RAW264.7 cells. Furthermore, LP inhibited the expression and phosphorylation of TLR4 protein and NF-κB protein, thus playing a role in the prevention of ALI. ConclusionsIn this study, mass spectrometry analysis was combined with biomolecular networks to initially elucidate the potential of LP to treat ALI by modulating the TLR4/NF-κB pathway. This offers a definitive experimental basis for the development of new LP drugs.