AHP-3a, a triple-helix acidic polysaccharide isolated from Alpinia officinarum Hance, was evaluated for its anticancer and antioxidant activities. The physicochemical properties and structure of AHP-3a were investigated through gel permeation chromatography, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy. The weight-average molecular weight of AHP-3a was 484 kDa, with the molar percentages of GalA, Gal, Ara, Xyl, Rha, Glc, GlcA, and Fuc being 35.4%, 21.4%, 16.9%, 11.8%, 8.9%, 3.1%, 2.0%, and 0.5%, respectively. Based on the results of the monosaccharide composition analysis, methylation analysis, and NMR spectroscopy, the main chain of AHP-3a was presumed to consist of (1→4)-α-D-GalpA and (1→2)-α-L-Rhap residues, which is a pectic polysaccharide with homogalacturonan (HG) and rhamnogalacturonan-I (RG-I) structural domains containing side chains. In addition, the results of the antioxidant activity assay revealed that the ability of AHP-3a to scavenge DPPH, ABTS, and OH free radicals increased with an increase in its concentration. Moreover, according to the results from the EdU, wound healing, and Transwell assays, AHP-3a can control the proliferation, migration, and invasion of HepG2 and Huh7 hepatocellular carcinoma cells without causing any damage to healthy cells. Thus, AHP-3a may be a natural antioxidant and anticancer component.

Background: Galangin, a flavonoid compound, is derived from Alpinia officinarum Hance. Previous studies have shown that galangin can inhibit the proliferation of hepatocellular carcinoma (HCC), but its mechanism is still unclear. This study aims to investigate the potential targets and molecular mechanisms of galangin on HCC through network pharmacology, bioinformatics, molecular docking, and experimental in vitro validation. Methods: In this study, network pharmacology was used to investigate the targets and mechanisms of galangin in the treatment of HCC. AutoDockTools software was used to simulate and calculate the binding of galangin to its core targets. GO and KEGG enrichment analyses were conducted in the DAVID database to explore the main biological functions and signaling pathways impacted by galangin intervention. In addition, bioinformatics was applied to examine the correlation between the differential expressions of the anti-HCC core targets of galangin and the survival of patients with HCC. Finally, the findings obtained from network pharmacology and bioinformatics were verified in cell experiments. Results: A total of 67 overlapping target genes of galangin and HCC were identified. Through the analysis of the protein-protein interaction (PPI) network, 10 hub genes with the highest degree of freedom were identified, including SRC, ESR1, MMP9, CDK4, CCNB1, MMP2, CDK2, CDK1, CHK1, and PLK1. These genes were found to be closely related to the degradation of the extracellular matrix, signal transduction, and the cell cycle. GO and KEGG enrichment analyses revealed that galangin exerts an anti-HCC role by affecting various signaling pathways, including the cell cycle, pathways in cancer, and the PI3K-Akt signaling pathway. The results of molecular docking indicated a significant interaction between galangin and CCNB1, CDK4, CDK1, and PLK1. Bioinformatics analysis revealed that CCNB1, CDK4, CDK1, and PLK1 were upregulated in the liver of patients with HCC at both the mRNA and protein levels. Flow cytometry analysis showed that galangin induced G0/G1 phase arrest and cell apoptosis in HepG2 and Huh7 cells. Additionally, galangin suppressed the expression of key proteins and mRNAs involved in the cell cycle pathway. Conclusions: These results suggest that galangin inhibits the growth of HCC cells by arresting the cell cycle at the G0/G1 phase.