Yu Yunfeng, Zhou Manli, Long Xi, Yin Shuang, Hu Gang, Yang Xinyu, Jian Weixiong, Yu Rong
College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan, China.
The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Front Pharmacol. 2023 Jun 19;14:1147360. doi: 10.3389/fphar.2023.1147360. eCollection 2023.
This is the first study to explore the mechanism of colchicine in treating coronary artery disease using network pharmacology and molecular docking technology, aiming to predict the key targets and main approaches of colchicine in treating coronary artery disease. It is expected to provide new ideas for research on disease mechanism and drug development. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Swiss Target Prediction and PharmMapper databases were used to obtain drug targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), DrugBank and DisGeNET databases were utilized to gain disease targets. The intersection of the two was taken to access the intersection targets of colchicine for the treatment of coronary artery disease. The Sting database was employed to analyze the protein-protein interaction network. Gene Ontology (GO) functional enrichment analysis was performed using Webgestalt database. Reactom database was applied for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking was simulated using AutoDock 4.2.6 and PyMOL2.4 software. A total of 70 intersecting targets of colchicine for the treatment of coronary artery disease were obtained, and there were interactions among 50 targets. GO functional enrichment analysis yielded 13 biological processes, 18 cellular components and 16 molecular functions. 549 signaling pathways were obtained by KEGG enrichment analysis. The molecular docking results of key targets were generally good. Colchicine may treat coronary artery disease through targets such as Cytochrome c (CYCS), Myeloperoxidase (MPO) and Histone deacetylase 1 (HDAC1). The mechanism of action may be related to the cellular response to chemical stimulus and p75NTR-mediated negative regulation of cell cycle by SC1, which is valuable for further research exploration. However, this research still needs to be verified by experiments. Future research will explore new drugs for treating coronary artery disease from these targets.
这是第一项利用网络药理学和分子对接技术探索秋水仙碱治疗冠状动脉疾病机制的研究,旨在预测秋水仙碱治疗冠状动脉疾病的关键靶点和主要途径。有望为疾病机制研究和药物开发提供新思路。利用中药系统药理学数据库与分析平台(TCMSP)、瑞士靶点预测数据库和PharmMapper数据库获取药物靶点。利用基因卡片数据库、人类孟德尔遗传在线数据库(OMIM)、治疗靶点数据库(TTD)、药物银行数据库和疾病基因数据库(DisGeNET)获取疾病靶点。取两者的交集以获得秋水仙碱治疗冠状动脉疾病的交集靶点。使用Sting数据库分析蛋白质-蛋白质相互作用网络。利用Webgestalt数据库进行基因本体(GO)功能富集分析。应用Reactom数据库进行京都基因与基因组百科全书(KEGG)富集分析。使用AutoDock 4.2.6和PyMOL2.4软件模拟分子对接。共获得70个秋水仙碱治疗冠状动脉疾病的交集靶点,其中50个靶点之间存在相互作用。GO功能富集分析产生了13个生物学过程、18个细胞成分和16个分子功能。通过KEGG富集分析获得549条信号通路。关键靶点的分子对接结果总体良好。秋水仙碱可能通过细胞色素c(CYCS)、髓过氧化物酶(MPO)和组蛋白去乙酰化酶1(HDAC1)等靶点治疗冠状动脉疾病。其作用机制可能与细胞对化学刺激的反应以及SC1介导的p75NTR对细胞周期的负调控有关,这对进一步的研究探索具有重要价值。然而, 本研究仍需通过实验验证。未来的研究将从这些靶点探索治疗冠状动脉疾病的新药。