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J Biomol Struct Dyn ; 41(23): 14135-14151, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36943780

RESUMEN

Traditional treatment of cancer has been plagued by a number of obstacles, such as multiple drug resistance, toxicity and financial constraints. In contrast, phytochemicals that modulate a variety of molecular mechanisms are garnering increasing interest in complementary and alternative medicine. Therefore, an approach based on network pharmacology was used in the present study to explore possible regulatory mechanisms of 6-shogaol as a potential treatment for cervical cancer (CC). A number of public databases were screened to collect information on the target genes of 6-shogaol (SuperPred, Targetnet, Swiss target prediction and PharmMapper), while targets pertaining to CC were taken from disease databases (DisGeNet and Genecards) and gene expression omnibus (GEO) provided expression datasets. With STRING and Cytoscape, protein-protein interactions (PPI) were generated and topology analysis along with CytoNCA were used to identify the Hub genes. The Gene Ontology (GO) database Enrichr was used to annotate the target proteins, while, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, signaling pathway enrichment analysis was conducted. Molecular docking and survival analysis for the Hub genes revealed four genes (HSP90AA1, HRAS, ESR1 and EGFR) with lowest binding energy and majority of the Hub genes (EGFR, SRC, CASP-3, HSP90AA1, MTOR, MAPK-1, MDM2 and ESR1) were linked with the overall survival of CC patients. In conclusion, the present study provides the scientific evidence which strongly supports the use of 6-shogoal as an inhibitor of cellular proliferation, growth, migration as well as inducer of apoptosis via targeting the hub genes involved in the growth of CC.Communicated by Ramaswamy H. Sarma.


Asunto(s)
Medicamentos Herbarios Chinos , Neoplasias del Cuello Uterino , Humanos , Femenino , Neoplasias del Cuello Uterino/tratamiento farmacológico , Neoplasias del Cuello Uterino/genética , Simulación del Acoplamiento Molecular , Farmacología en Red , Receptores ErbB
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