Deciphering Key Protein Targets, Hub Gene Networks, Signaling Pathways and in silico Docking Studies of Artemisinin in Human Lung Carcinoma

Indian Journal of Pharmaceutical Education and Research

  • Xin Sheng1Department of Pulmonary and Critical Care Medicine-Section 1, The Second Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital, Chengdu Sichuan, CHINA.
  • Dandan Sheng2Department of Tuberculosis, Yantai Qishan Hospital, Yantai Shandong, CHINA.
  • Ruiqing Xing3Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an Shaanxi, CHINA.

Volume 60 Issue 1 Pages 393-409

DOI: 10.5530/ijper.20261248

Abstract

Background: Artemisinin has been reported to exert potent anticancer effects in diverse cancers, but its mode of anticancer action is not fully understood. Objectives: This study involved network pharmacology, bioinformatics, in silico molecular docking and dynamics along with experimental validation to demonstrate the anticancer activity as well as detailed mode of action of artemisinin in lung cancer. Materials and Methods: SwissADME and Protox-II analyzed physicochemical properties and toxicity of artemisinin, while SuperPred and SwissTargetPrediction predicted the biological targets. Lung cancer targets identified from Genecards overlapped with targets of artemisinin using Venny 2.0.2. The intersecting gene targets were submitted to STRING for PPI network development and hub gene identification was done using Cytoscape CytoHubba plugin. ShinyGo platform enabled Gene Ontology and KEGG pathway analysis, whereas UALCAN database revealed DNA methylation, gene expression and survival analysis of hub genes. The correlation between hub gene expression and immune cell infiltration into the tumor microenvironment was studied using the TIMER database. Molecular docking was done using CB-Dock2 and MD simulation with CABS-flex. In vitro experimental assays using MTT, fluorescence microscopy (AO/ EB staining) and western blotting evaluated the effects of artemisinin on cell viability, apoptosis and hub-gene expression. Results: The constructed PPI network comprised 137 nodes and 858 edges, identifying 10 hub genes, including EGFR, HSP90AA1 and PTGS2. Functional analysis revealed significant enrichment in processes like Protein kinase activity and pathways such as PD-L1 expression and PI3K-Akt signalling. UALCAN analyses indicated elevated DNA methylation of EGFR and HSP90AA1, while HSP90AA1 and HSP90AB1 were upregulated in mRNA expression. Immune infiltration analysis showed a positive correlation between hub gene expression and tumor infiltration especially NFKB1 and EGFR. Molecular docking confirmed strong binding affinities of artemisinin to hub genes and molecular dynamics simulations supported stable interactions. Artemisinin demonstrated dose-dependent cytotoxicity in A549 cells, inducing apoptosis and downregulating key hub proteins EGFR, PTGS2 and HSP90AA1 validating the bioinformatics results. Conclusion: Our findings highlight the potential of artemisinin as a therapeutic agent in lung cancer, highlighting its targets and associated pathways for further investigation.

Keywords

  • Apoptosis
  • Artemisinin
  • Gene-ontology
  • Immune infiltration
  • Lung cancer
  • Natural
  • products
  • Network pharmacology
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