| 引用本文: | 靳晓杰,王燕如,王玉,关瑞宁,罗宏,石生青,李潮新,李丹桂,张志明,刘永琦.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[J].中国现代应用药学,2020,37(8):897-906. |
| JIN Xiaojie,WANG Yanru,WANG Yu,GUAN Ruining,LUO Hong,SHI Shengqing,LI Chaoxin,LI Dangui,ZHANG Zhiming,LIU Yongqi.Explore the Material Basis of Treating Pulmonary Fibrosis with Yifei Jianpi Prescription Based on Network Pharmacology, Molecular Docking and Chemical Informatics[J].Chin J Mod Appl Pharm(中国现代应用药学),2020,37(8):897-906. |
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| 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 |
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靳晓杰1,2, 王燕如2, 王玉1, 关瑞宁1, 罗宏1, 石生青1, 李潮新1, 李丹桂1, 张志明3, 刘永琦2,4
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1.甘肃中医药大学, 药学院, 兰州 730000;2.甘肃中医药大学, 甘肃省高校重大疾病分子医学与中医药防治研究重点实验室, 兰州 730000;3.甘肃中医药大学, 附属医院, 兰州 730000;4.甘肃中医药大学, 敦煌医学与转化省部共建教育部重点实验室, 兰州 730000
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| 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。 |
| 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 |
| DOI：10.13748/j.cnki.issn1007-7693.2020.08.001 |
| 分类号:R285.6 |
| 基金项目:甘肃省新型冠状病毒肺炎（NCP）科技重大专项（2020）；2020年度甘肃中医药大学新型冠状病毒感染的肺炎应急防治专项项目（2020XGZX-01，2020XGZX-02）；甘肃省高等学校科研项目（2017A-048）；2020年度甘肃省重大疾病分子医学与中医药防治研究重点实验室新型冠状病毒防治研究专项开放基金（FZYX20-1，FZYX20-2，FZYX20-3） |
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| Explore the Material Basis of Treating Pulmonary Fibrosis with Yifei Jianpi Prescription Based on Network Pharmacology, Molecular Docking and Chemical Informatics |
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JIN Xiaojie1,2, WANG Yanru2, WANG Yu1, GUAN Ruining1, LUO Hong1, SHI Shengqing1, LI Chaoxin1, LI Dangui1, ZHANG Zhiming3, LIU Yongqi2,4
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1.Gansu University of Chinese Medicine, School of Pharmacy, Lanzhou 730000, China;2.Gansu University of Chinese Medicine, Gansu University Key Laboratory for Molecular Medicine&Chinese Medicine Prevention and Treatment of Major Diseases, Lanzhou 730000, China;3.Gansu University of Chinese Medicine, Affiliated Hospital, Lanzhou 730000, China;4.Gansu University of Chinese Medicine, Key Laboratory of Dunhuang Medicine, Ministry of Education, Lanzhou 730000, China
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| 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. |
| Key words: network pharmacology Yifei Jianpi prescription pulmonary fibrosis αvβ6 molecular docking hierarchical clustering analysis COVID-19 |
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