Dissecting the molecular mechanism of cepharanthine against COVID-19, based on a network pharmacology strategy combined with RNA-sequencing analysis, molecular docking, and molecular dynamics simulation
Abstract
OBJECTIVES: Recently, it has been reported that cepharanthine (CEP) is highly likely to be an agent against Coronavirus disease 2019 (COVID-19). In the present study, a network pharmacology-based approach combined with RNA-sequencing (RNA-seq), molecular docking, and molecular dynamics (MD) simulation was performed to determine hub targets and potential pharmacological mechanism of CEP against COVID-19.
METHODS: Targets of CEP were retrieved from public databases. COVID-19-related targets were acquired from databases and RNA-seq datasets GSE157103 and GSE155249. The potential targets of CEP and COVID-19 were then validated by GSE158050. Hub targets and signaling pathways were acquired through bioinformatics analysis, including protein-protein interaction (PPI) network analysis and enrichment analysis. Subsequently, molecular docking was carried out to predict the combination of CEP with hub targets. Lastly, MD simulation was conducted to further verify the findings.
RESULTS: A total of 700 proteins were identified as CEP-COVID-19-related targets. After the validation by GSE158050, 97 validated targets were retained. Enrichment results indicated that CEP acts on COVID-19 through multiple pathways, multiple targets, and overall cooperation. Specifically, PI3K-Akt signaling pathway is the most important pathway. Based on PPI network analysis, 9 central hub genes were obtained (ACE2, STAT1, SRC, PIK3R1, HIF1A, ESR1, ERBB2, CDC42, and BCL2L1). Molecular docking suggested that the…
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