Shandong Science ›› 2022, Vol. 35 ›› Issue (4): 28-37.doi: 10.3976/j.issn.1002-4026.2022.04.005

• Pharmacology and Toxicology • Previous Articles     Next Articles

The mechanism underlying Fagopyri Dibotryis Rhizoma's action against respiratory syncytial virus using network pharmacology

DU Hai-tao1,2(), WANG Ping1,3,*(), LI Na2, HAN Li1, DING Jie2, HU Ya-nan2   

  1. 1. Shandong Academy of Chinese Medicine, Jinan 250014, China
    2. School of Pharmaceutical Sciences, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
    3. State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
  • Received:2021-07-21 Online:2022-08-20 Published:2022-07-25
  • Contact: WANG Ping E-mail:kkitdht@foxmail.com;wangpingjinan@163.com

Abstract:

The core ingredients and targets of Fagopyri Dibotryis Rhizoma against respiratory syncytial virus (RSV) were screened using network pharmacology and verified via gene chip mining and molecular docking. The core ingredients were screened using the traditional Chinese medicine systems pharmacology database(TCMSP), targets of the core ingredients were predicted using SwissTargetPrediction, and targets of pneumonia-causing RSV were obtained using GeneCards, GenCLiP 3, and National Center for Biotechnology Information database. The intersection target network was generated via target mapping, and the protein-protein interaction (PPI) network and core enrichment Kyoto encyclopedia of genes and genomes (KEGG) pathway were constructed through STRING and DAVID platforms to obtain the core targets and pathways. Gene expression omnibus chip data mining and AutoDock Vina molecular docking were used to verify the effectiveness of the core targets. Fifteen components of Fagopyri Dibotryis Rhizoma were screened using TCMSP database. Furthermore, target mapping showed that Fagopyri Dibotryis Rhizoma had 45 targets. Through the comprehensive analysis of PPI network and KEGG pathway, the targets of Fagopyri Dibotryis Rhizoma against RSV were found to be AKT1, VEGFA, PTGS2, SRC, EGFR, KDR, STAT3, BCL2,etc. The results of data mining and molecular docking were basically consistent with the prediction. This study preliminarily predicted the main active components, targets, and related pathways of Fagopyri Dibotryis Rhizoma, which would prove to be beneficial in the treatment of RSV-induced diseases, and laid a good foundation for further revealing its mechanism.

Key words: network pharmacology, molecular docking, targets, respiratory syncytial virus, Fagopyri Dibotryis Rhizoma

CLC Number: 

  • R285.5