Identifying the Multitarget Pharmacological Mechanism of Action of Genistein on Lung Cancer by Integrating Network Pharmacology and Molecular Dynamic Simulation.
Raju DasJoo Han WooPublished in: Molecules (Basel, Switzerland) (2024)
Food supplements have become beneficial as adjuvant therapies for many chronic disorders, including cancer. Genistein, a natural isoflavone enriched in soybeans, has gained potential interest as an anticancer agent for various cancers, primarily by modulating apoptosis, the cell cycle, and angiogenesis and inhibiting metastasis. However, in lung cancer, the exact impact and mechanism of action of genistein still require clarification. To provide more insight into the mechanism of action of genistein, network pharmacology was employed to identify the key targets and their roles in lung cancer pathogenesis. Based on the degree score, the hub genes AKT1, CASP3, EGFR, STAT3, ESR1, SRC, PTGS2, MMP9, PRAG, and AR were significantly correlated with genistein treatment. AKT1, EGFR, and STAT3 were enriched in the non-small cell lung cancer (NSCLC) pathway according to Kyoto Encyclopedia of Genes and Genomes analysis, indicating a significant connection to lung cancer development. Moreover, the binding affinity of genistein to NSCLC target proteins was further verified by molecular docking and molecular dynamics simulations. Genistein exhibited potential binding to AKT1, which is involved in apoptosis, cell migration, and metastasis, thus holding promise for modulating AKT1 function. Therefore, this study aimed to investigate the mechanism of action of genistein and its therapeutic potential for the treatment of NSCLC.
Keyphrases
- signaling pathway
- small cell lung cancer
- cell proliferation
- molecular dynamics simulations
- molecular docking
- cell cycle
- cell migration
- oxidative stress
- tyrosine kinase
- advanced non small cell lung cancer
- epidermal growth factor receptor
- pi k akt
- genome wide
- cell cycle arrest
- cell death
- squamous cell carcinoma
- machine learning
- network analysis
- bioinformatics analysis
- papillary thyroid
- artificial intelligence
- brain metastases
- mass spectrometry
- deep learning
- molecular dynamics
- childhood cancer
- combination therapy
- drug induced
- squamous cell
- smoking cessation
- climate change