基于网络药理学及分子对接技术探究天麻抗疲劳成分及其机制

Probing anti-fatigue ingredients and mechanism of Gastrodia elata based on network pharmacology and molecular docking technology

【目的】探究天麻的抗疲劳主要成分及其作用机制。【方法】通过中药系统药理学数据库与分析平台(TCMSP)、Web of Science (WOS)及中国知网(CNKI)等数据库,对天麻活性成分进行检索;通过数据库SwissTarget Prediction对天麻有效成分的作用靶点进行预测。采用数据库Disgenet获取与机体疲劳相关的靶基因,通过Venny及Cytoscape等软件,建立天麻-药效成分-抗疲劳靶点相互作用的调控网络,对其有效成分进行筛选。通过数据库String建立蛋白质相互作用关系网络,对中药活性成分的作用靶点进行筛选,并对其作用机制进行探究。利用数据库DAVID执行基因本体(GO)功能富集和京都基因与基因组百科全书(KEGG)通路富集分析。通过软件Autodock Vina,将天麻中的主要活性成分与抗疲劳相关的靶点进行分子对接。【结果】共获得98个天麻活性成分,预测得到94个天麻抗疲劳靶点。筛选出5个抗疲劳的主要活性成分,分别为天麻素(gastrodin)、L-焦谷氨酸(L-pyroglutamicacid)、原儿茶酸(protocatechuicacid)、3,4-二羟基苯甲醛(3,4-dihydroxybenz-aldehyde)、4-乙氧基甲基苯酚[4-(ethoxymethyl)-glucopyranosyl-phenol]。蛋白互作网络拓扑分析结果表明,信号转导及转录激活蛋白3(STAT3)、磷酸肌醇3激酶(PIK3CA)、磷酸肌醇-3-激酶催化亚基Β肽(PIK3CB)、磷酸肌醇-3-激酶催化亚基δ肽(PIK3CD)、磷酸肌醇3激酶调节亚基1(PIK3R1)以及雌激素受体(ESR1)为天麻抗疲劳的关键靶点。GO和KEGG富集分析显示,天麻抗疲劳作用涉及110个条目和141个通路。分子对接结果显示,天麻的5个主要活性成分与抗疲劳关键靶点能够稳定结合。【结论】天麻抗疲劳作用涉及多种活性成分、多个信号通路以及多个作用靶点。天麻可能通过清除自由基、降低细胞炎症反应、促进能量代谢、加快细胞周期进程等多个生物学过程发挥其抗疲劳功效。

[Objective]The study aimed to explore the potential anti-fatigue ingredients and mechanism of Gastrodia elata by network phar-macology methods and molecular docking technology.[Method]The key active components of G.elata were sourced from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Web of Science(WOS),and China National Knowledge Infra-structure(CNKI).The targets of effective ingredients were predicted through the SwissTarget Prediction database,And the fatigue-related tar-gets were obtained from the Disgenet database.Aregulatory network of G.elata ingredients and anti-fatigue targets was constructed using Ven-ny and Cytoscape software,facilitating the selection of effective ingredients.The protein-protein interaction(PPI)network was generated through the String database to screen the targets of active components and explore their mechanisms of action.Functional enrichment analysis of Gene Ontology(GO),as well as Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways was conducted by the DAVID database,followed by molecular docking of the key active components with the key anti-fatigue targets using Autodock Vina software.[Result]A total of 98 active ingredients of G.elata were identified,and 94 anti-fatigue targets were predicted.Five major anti-fatigue active ingredients were selected,including gastrodin,L-pyroglutamic acid,protocatechuic acid,3,4-dihydroxybenzaldehyde,and 4-(ethoxymethyl)-glucopyranosyl-phenol.Topological analysis of protein interaction networks revealed that STAT3,PIK3CA,PIK3CB,PIK3CD,PIK3RI and ESRI were the key targets for anti-fatigue effects of G.elata.GO and KEGG enrichment analyses indicated anti-fatigue mechanisms of G.elata involved 110 entries and 141 pathways,Molecular docking results demonstrated that five main active ingredients and key anti-fatigue targets had stable binding.[Conclusion]The anti-fatigue effects of G.elata involve multiple active ingredients,signaling pathways,and target points.G.elata potentially exerts anti-fatigue efficacy through biological processes such as scavenging free radicals,reducing cellular inflammation,accelera-ting energy metabolism,and enhancing cell cycle progression.