The Anti-lung Cancer Mechanism of Qingzao Jiufei Decoction was Studied based on Network Pharmacology, Molecular Docking, and Experimental Verification.

Background: Lung cancer (LC) is one of the most common cancers in the world, with both its incidence and mortality rates ranking at the top position among all types of cancers, posing a serious threat to human health. Qingzao Jiufei Decoction (QD) has been used clinically to treat lung cancer, but its mechanism of action remains unclear.

Objective: This study aims to elucidate the potential pharmacological mechanisms of QD in treating LC through network pharmacology, molecular docking, molecular dynamics simulation (MDS), and animal experiment validation.

Methods: Active components of QD were screened utilizing the TCMSP and HREB databases, and potential targets were predicted using network pharmacology methods. Relevant targets for LC were identified from the Genecards, OMIM, and TTD databases. Intersecting targets between QD and LC were imported into the STRING 12.0 database and Cytoscape 3.10.0 software to create proteinprotein interaction (PPI) network diagrams, and Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted through using the DAVID database to identify core active components and key targets. Molecular docking was employed to assess the binding affinity of core active components with key targets in lung cancer, and MDS was used to evaluate the stability of the target-active component complexes. An in vivo lung cancer model was used to verify the therapeutic effects of QD, and Western blot analysis was used to confirm the pharmacological mechanisms of QD in treating lung cancer.

Results: Network pharmacology analysis has identified 9 core components and 9 key targets. GO and KEGG analyses have revealed a total of 185 signaling pathways, with the PI3K-Akt signaling pathway and MAPK signaling pathway being the two most significantly enriched pathways. Molecular docking results showed that all 9 core components and 9 key targets exhibited significant binding activity (binding energy < -5 kcal/mol). MDS study further simulated and confirmed strong and stable interactions between targets and active components. In an in vivo lung cancer model, QD significantly inhibited tumor growth, while Western blot analysis demonstrated that QD exerted its therapeutic effects on lung cancer by inhibiting the phosphorylation of ERK, JNK, and p38 in the MAPK signaling pathway.

Conclusion: This experimental study found that QD can significantly inhibit the growth of lung cancer through a multifaceted approach involving various components, targets, and pathways, providing a foundation for the development and clinical application of new drugs targeting lung cancer for QD. Furthermore, it offers valuable insights into anti-tumor research with Traditional Chinese Medicine (TCM) and facilitates a more comprehensive interpretation of TCM principles through the lens of modern science.