基于网络药理学、分子对接和化学信息学方法探索益肺健脾方治疗肺纤维化的物质基础

Explore the Material Basis of Treating Pulmonary Fibrosis with Yifei Jianpi Prescription Based on Network Pharmacology, Molecular Docking and Chemical Informatics

关键词:  网络药理学  益肺健脾方  肺纤维化  整合素αvβ6  分子对接  层次聚类分析  新型冠状病毒肺炎

Key words:  network pharmacology  Yifei Jianpi prescription  pulmonary fibrosis  αvβ6  molecular docking  hierarchical clustering analysis  COVID-19

摘要:

目的 运用网络药理学、分子对接以及化学信息学方法探索益肺健脾方治疗肺纤维化的分子机制和物质基础。方法 TCMSP、TCMID数据库下载益肺健脾方11味中药化合物。利用SwissTargetPrediction预测化合物潜在靶点，运用Cytoscape构建化合物-靶点网络。TTD、Drugbank筛选肺纤维化相关靶点，STRING分析靶点蛋白互相作用并进行GO分析和KEGG分析。进一步采用分子对接对化合物与肺纤维化关键靶点整合素αvβ6的亲和能力进行评估，对筛选得到活性较高的化合物进行化学信息学层次聚类分析。结果 益肺健脾方与肺纤维化共有靶点27个，PPI分析得到关键靶点6个，GO分析和KEGG分析得到GO条目336个、KEGG通路35条。分子对接获得了具有靶向αvβ6潜在亲和力的成分，eRo5规则和打分排名筛选30个化合进行化学信息学聚类分析，结果显示化合物Naphthol aS-bl phosphate、Tangshenoside IV_qt、（2R）-2-azaniumyl-3-（1H-indol-3-yl）propanoate、（3S）-3-azaniumyl-4-hydroxy-4-oxobutanoate、[（2R）-2-Formyloxy-3-phosphonooxypropyl]formate所代表的骨架结构具有潜在抑制肺纤维化活性，主要相互作用为氢键和疏水相互作用。结论 本研究为中医药抗新冠病毒引起肺纤维化的治疗和相关医方的研究提供基于生物信息学、网络药理学、分子对接、化学信息学的系统研究方法。

Abstract:

OBJECTIVE to explore the molecular mechanism and material basis of treating pulmonary fibrosis with yifei jianpi prescription based on network pharmacology, molecular docking and chemical informatics. METHODS TCMSP and TCMID database were used to download the compounds of 11 traditional Chinese medicines. Prediction of potential targets was made by SwissTargetPrediction, Cytoscape was used to construct a chemical-target network. TTD and Drugbank screened pulmonary fibrosis related targets, constructed target protein interaction(PPI) network and conducted gene function GO analysis and KEGG pathway enrichment analysis in String database. Further, molecular docking technology was used to evaluate the affinity of key compounds with αvβ6 and Hierarchical Clustering analysis was carried out on the compounds with high activity.RESULTS There were 27 targets of yifei jianpi prescription and pulmonary fibrosis. PPI analysis yielded 6 key targets, 336 GO items and 35 KEGG pathways. Molecular docking was used to obtain 30 pharmacokinetic active compounds with potential affinity forαvβ6. ER o5 and scoring rankings were used to select 30 combinations for chemical informatics cluster analysis. Naphthol aS-bl phosphate, Tangshenoside IV_qt, (2R)-2-azaniumyl-3-(1H-indol-3-yl)propanoate, (3S)-3-azaniumyl-4-hydroxy-4-oxobutanoate and[(2R)-2-Formyloxy-3-phosphonooxypropyl] formate had potential inhibitory activities against pulmonary fibrosis. CONCLSION This study is expected to provide a systematic research method of bioinformatics, network pharmacology, molecular docking and chemical informatics for the treatment of pulmonary fibrosis caused by SARS-CoV-2 in traditional Chinese medicine and the related medical prescription.