Mechanisms of breast cancer treatment using Gentiana robusta: evidence from comprehensive bioinformatics investigation - Bo Xiong; Xinxin Zhang; Dongzhi Sangji; Lianghong Ni; Mingjie Fan; Beibei Fan (Scientific Reports)
Abstract This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation. Building upon prior research on QJ’s chemical constituents, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the DAVID database. Network interactions and core genes were identified using Cytoscape 3.9.1. Key target genes, including Interleukin-6 (IL-6), tumour suppressor gene P53 (TP53), and epidermal growth factor receptor (EGFR), were selected for molecular docking with QJ’s active components, 2′-O-β-D-glucopyranosyl-gentiopicroside and macrophylloside D, employing Schrodinger Maestro 13.5. Molecular dynamics (MD) simulations were performed using the Desmond program. A total of 270 intersection targets of active ingredients and diseases were identified, with three core targets determined through network topology screening. Enrichment analysis highlighted the involvement of QJ in breast cancer treatment, primarily through the hsa05200 cancer signaling pathway and the hsa04066 HIF-1 signaling pathway. Molecular docking and dynamics simulations demonstrated the close interaction of 2′-O-β-D-glucopyranosyl-gentiopicroside (QJ17) and macrophylloside D (QJ25) with IL6, TP53, and EGFR, and other target genes, showcasing a stabilizing effect. In conclusion, this study unveils the effective components and potential mechanisms of 2′-O-β-D-glucopyranosyl-gentiopicroside and macrophylloside D in breast cancer prevention and treatment. The identified components act on target genes such as IL6, TP53, and EGFR, regulating crucial pathways including the cancer signaling and Hypoxia-inducible factor 1 (HIF-1) signaling pathways. These findings provide valuable insights into the therapeutic potential of QJ in breast cancer management. However, further experimental research are needed to validate the computational findings of QJ.