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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.
Liu, Jiaqin; Sun, Taoli; Liu, Sa; Liu, Jian; Fang, Senbiao; Tan, Shengyu; Zeng, Yucheng; Zhang, Bikui; Li, Wenqun.
  • Liu J; Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Institute of Clinical Pharmacy, Central South University, Changsha, Hunan, 410011, China.
  • Sun T; School of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China.
  • Liu S; Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Institute of Clinical Pharmacy, Central South University, Changsha, Hunan, 410011, China.
  • Liu J; Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Institute of Clinical Pharmacy, Central South University, Changsha, Hunan, 410011, China.
  • Fang S; Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410083, China.
  • Tan S; Department of Gerontology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Zeng Y; School of Pharmaceutical Science, Hunan University of Medicine, Huaihua, Hunan, 418000, China.
  • Zhang B; Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Institute of Clinical Pharmacy, Central South University, Changsha, Hunan, 410011, China. Electronic address: 505595@csu.edu.cn.
  • Li W; Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Institute of Clinical Pharmacy, Central South University, Changsha, Hunan, 410011, China. Electronic address: liwq1204@csu.edu.cn.
Comput Biol Med ; 151(Pt A): 106298, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2104650
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 combination between CEP and 9 central hub genes is extremely strong. Noteworthy, ACE2, considered the most important gene in CEP against COVID-19, binds to CEP most stably, which was further validated by MD simulation.

CONCLUSION:

Our study comprehensively illustrated the potential targets and underlying molecular mechanism of CEP against COVID-19, which further provided the theoretical basis for exploring the potential protective mechanism of CEP against COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Molecular Dynamics Simulation / COVID-19 Drug Treatment Type of study: Prognostic study / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article Affiliation country: J.compbiomed.2022.106298

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Molecular Dynamics Simulation / COVID-19 Drug Treatment Type of study: Prognostic study / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article Affiliation country: J.compbiomed.2022.106298