Using Network Pharmacology and Molecular Docking to Explore the Mechanism of Shan Ci Gu (Cremastra appendiculata) Against Non-Small Cell Lung Cancer

Abstract

Background: In recent years, the incidence and mortality rates of non-small cell lung cancer (NSCLC) have increased significantly. Shan Ci Gu is commonly used as an anticancer drug in traditional Chinese medicine; however, its specific mechanism against NSCLC has not yet been elucidated. Here, the mechanism was clarified through network pharmacology and molecular docking.Methods: The Traditional Chinese Medicine Systems Pharmacology database was searched for the active ingredients of Shan Ci Gu, and the relevant targets in the Swiss Target Prediction database were obtained according to the structure of the active ingredients. GeneCards were searched for NSCLC-related disease targets. We obtained the cross-target using VENNY to obtain the core targets. The core targets were imported into the Search Tool for the Retrieval of Interacting Genes/Proteins database, and Cytoscape software was used to operate a mesh chart. R software was used to analyze the Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The core targets and active compounds were molecularly docked through Auto-Dock Vina software to predict the detailed molecular mechanism of Shan Ci Gu for NSCLC treatment. We did a simple survival analysis with hub gene to assess the prognosis of NSCLC patients.Results: Three compounds were screened to obtain 143 target genes and 1,226 targets related to NSCLC, of which 56 genes were related to NSCLC treatment. Shan Ci Gu treatment for NSCLC involved many BPs and acted on main targets including epidermal growth factor receptor (EGFR), ESR1, and SRC through signaling pathways including the endocrine resistance, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathways. Shan Ci Gu might be beneficial for treating NSCLC by inhibiting cell proliferation and migration. Molecular docking revealed that the active compounds β-sitosterol, stigmasterol, and 2-methoxy-9,10-dihydrophenanthrene-4,5-diol had good affinity with the core target genes (EGFR, SRC, and ESR1). Core targets included EGFR, SRC, ESR1, ERBB2, MTOR, MCL1, matrix metalloproteinase 2 (MMP2), MMP9, KDR, and JAK2. Key KEGG pathways included endocrine resistance, EGFR tyrosine kinase inhibitor resistance, ErbB signaling, PI3K-Akt signaling, and Rap1 signaling pathways. These core targets and pathways have an inhibitory effect on the proliferation of NSCLC cells.Conclusion: Shan Ci Gu can treat NSCLC through a multi-target, multi-pathway molecular mechanism and effectively improve NSCLC prognosis. This study could serve as a reference for further mechanistic research on wider application of Shan Ci Gu for NSCLC treatment.

Prediction of the Mechanism of Sodium Butyrate against Radiation-Induced Lung Injury in Non-Small Cell Lung Cancer Based on Network Pharmacology and Molecular Dynamic Simulations

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Investigative on the Molecular Mechanism of Licorice Flavonoids Anti-Melanoma by Network Pharmacology, 3D/2D-QSAR, Molecular Docking, and Molecular Dynamics Simulation

“…Then, enter the potential targets for melanoma treatment into the STRING database, and set the target as “Homo” to construct a protein–protein interaction (PPI) diagram of potential targets for melanoma treatment ( Supplementary Figure S2 ). Potential target pathway enrichment was generated through the DAVID 6.8 database ( Wang et al, 2021 ). Finally, Cytoscape v3.8.2 software ( https://cytoscape.org/download.html ) was used to construct a “C-T-P" network of 44 compounds, 18 targets, and 10 signaling pathways closely related to melanoma to elucidate the effective mechanism of LCF anti-melanoma.…”

Cytotoxicity and molecular-docking approach of a new rosane-type diterpenoid from the roots of Euphorbia nematocypha

“…Active pockets were built and saved as protein data bank (PDB), partial charge (Q), and atom type (T) (PDBQT) files. Then, each active site was docked with the compound ( Wang Y. et al, 2021 ). According to the results of molecular docking, the conformation with the most stable structure and lowest energy was selected and imported into PyMoL 1.8 ( https://pymol.org ) together with the protein ( Shen et al, 2019 ).…”