Mechanisms of Ganweikang Tablets against Chronic Hepatitis B: A Comprehensive Study of Network Analysis, Molecular Docking, and Chemical Profiling

甘维康片治疗慢性乙型肝炎的机制:网络分析、分子对接和化学分析的综合研究

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Abstract

The hepatitis B virus (HBV) is one of the major viral infection problems worldwide in public health. The exclusive proprietary Chinese medicine Ganweikang (GWK) tablet has been marketed for years in the treatment of chronic hepatitis B (CHB). However, the pharmacodynamic material basis and underlying mechanism of GWK are not completely clear. This study is aimed at investigating the pharmacological mechanism of the GWK tablet in the treatment of CHB. The chemical ingredient information was obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and Shanghai Institute of Organic Chemistry of CAS. Ingredients and disease-related targets were defined by a combination of differentially expressed genes from CHB transcriptome data and open-source databases. Target-pathway-target (TPT) network analysis, molecular docking, and chemical composition analysis were adopted to further verify the key targets and corresponding active ingredients of GWK. Eight herbs of GWK were correlated to 330 compounds with positive oral bioavailability, and 199 correlated targets were identified. The TPT network was constructed based on the 146 enriched targets by KEGG pathway analysis, significantly associated with 95 pathways. Twenty-five nonvolatile components and 25 volatile components in GWK were identified in UPLC-QTOF/MS and GC-MS chromatograms. The key active ingredients of GWK include ferulic acid, oleanolic acid, ursolic acid, tormentic acid, 11-deoxyglycyrrhetic acid, dibenzoyl methane, anisaldehyde, wogonin, protocatechuic acid, psoralen, caffeate, dimethylcaffeic acid, vanillin, β-amyrenyl acetate, formonentin, aristololactam IIIa, and 7-methoxy-2-methyl isoflavone, associated with targets CA2, NFKB1, RELA, AKT1, JUN, CA1, CA6, IKBKG, FOS, EP300, CREB1, STAT1, MMP9, CDK2, ABCB1, and ABCG2.

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