基于网络药理学探讨金荞麦抗呼吸道合胞病毒作用机制

基于网络药理学筛选金荞麦抗呼吸道合胞病毒的核心作用成分及靶点,并使用芯片数据挖掘和分子对接做初步验证。通过中药系统药理学数据库与分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)筛选核心作用成分,借助SwissTargetPrediction预测核心作用成分靶点,通过GeneCards、GenCLiP 3、NCBI获取呼吸道合胞病毒涉及肺炎靶点。经靶点映射生成交集靶点网络,并通过STRING、DAVID平台构建蛋白质-蛋白质相互作用(Protein-protein interaction,PPI)关系及核心富集通路,获取核心靶点与通路。使用GEO芯片数据挖掘及AutoDock Vina分子对接初步验证核心靶点的有效性。最终通过TCMSP筛选到金荞麦15个成分,经靶点映射发现金荞麦通过45个靶点发挥作用,通过PPI和KEGG(Kyoto encyclopedia of genes and genomes) 通路综合分析可得金荞麦发挥抗呼吸道合胞病毒的作用靶点为AKT1、VEGFA、PTGS2、SRC、EGFR、KDR、STAT3、BCL2等,数据挖掘和分子对接结果与预测基本一致,为进一步深入揭示其作用机制奠定了良好基础。

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

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.