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Background: Ginseng is one of the top-selling natural products worldwide and has been shown to have significant effects. Nonetheless, there is limited research on American ginseng when compared to Asian ginseng. A small number of studies have demonstrated the therapeutic benefits of American ginseng, which include antioxidant, anti-inflammatory, and immune-stimulating activities. Objective: The objective of our research is to predict the molecular mechanism by which American ginseng combats Type 2 diabetes mellitus (T2DM) using Network Pharmacology and Molecular Docking techniques. By doing so, we aim to reveal one of the comprehensive mechanisms through which American ginseng exerts its therapeutic effects. Methods: We conducted a search for related compounds in American ginseng using the TCMSP database, which we then utilized to classify potential targets for the major ingredients. We obtained targets associated with Type 2 diabetes mellitus (T2DM) from various databases, including PharmGKB, OMIM, TTD, GeneCards, and DrugBank. Using STRING and Cytoscape software, we constructed PPI networks. We subsequently performed GO and KEGG analysis on the targets using the R programming language. Ligand and target structures were acquired from PubChem and PDB databases, respectively. Chem3D and AutoDock software was used to process the structures, while PyMoL was employed for molecular docking analysis. Results: Several investigations have indicated that PTGS2, NFKBIA, PRKCA, IL1B, NCOA2, and LPL targets are significantly associated with American ginseng's effectiveness in treating T2DM. Molecular docking analysis further validated these findings. We discovered three active components with high-affinity, namely papaverine, ginsenoside-rh2, and beta-sitosterol. Conclusion: The outcomes of our predictions could contribute to the development of American ginseng or its active constituents as an alternative therapy for T2DM.

BACKGROUND: Traditional Chinese medicine (TCM) has been widely recognized and accepted worldwide to provide favorable therapeutic effects for cancer patients. As Andrographis paniculata has an anti-tumor effect, it might inhibit lung cancer. OBJECTIVE: The drug targets and related pathways involved in the action of Andrographis paniculata against lung cancer were predicted using network pharmacology, and its mechanism was further explored at the molecular level. METHODS: This work selected the effective components and targets of Andrographis paniculata against the Traditional Chinese Medicine System Pharmacology (TCMSP) database. Targets related to lung cancer were searched for in the GEO database (accession number GSE136043). The volcanic and thermal maps of differential expression genes were produced using the software R. Then, the target genes were analyzed by GO and KEGG analysis using the software R. This also utilized the AutoDock tool to study the molecular docking of the active component structures downloaded from the PubChem database and the key target structures downloaded from the PDB database, and the docking results were visualized using the software PyMol. RESULTS: The results of molecular docking show that wogonin, Mono-O-methylwightin, Deoxycamptothecine, andrographidine F_qt, Quercetin tetramethyl (3’,4’,5,7) ether, 14-deoxyandrographolide, andrographolide-19-β-D-glucoside_qt and 14-deoxy-11-oxo-andrographolide were potential active components, while AKT1, MAPK14, RELA and NCOA1 were key targets. CONCLUSION: This study showed the main candidate components, targets, and pathways involved in the action of Andrographis paniculata against lung cancer.