Table1_Study on the mechanism of action of colchicine in the treatment of coronary artery disease based on network pharmacology and molecular docking technology.XLSX

Objective: 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.Methods: 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.Results: 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.Conclusion: 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.

本研究旨在运用网络药理学与分子对接技术，探析秋水仙碱治疗冠状动脉疾病的机制，旨在预测秋水仙碱治疗冠状动脉疾病的关键靶点及主要作用途径，以期为新病机研究及药物研发提供新的思路。研究方法上，采用中医药系统药理学数据库与分析平台（TCMSP）、瑞士靶点预测及PharmMapper数据库获取药物靶点；通过GeneCards、在线孟德尔遗传学数据库（OMIM）、治疗靶点数据库（TTD）、DrugBank及DisGeNET数据库获取疾病靶点，并取其交集以确定秋水仙碱治疗冠状动脉疾病的相关靶点。利用Sting数据库分析蛋白质-蛋白质相互作用网络，并通过Webgestalt数据库进行基因本体（GO）功能富集分析。此外，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，并使用AutoDock 4.2.6及PyMOL2.4软件进行分子对接模拟。研究结果显示，共获得70个秋水仙碱治疗冠状动脉疾病的相关靶点，其中50个靶点存在相互作用。GO功能富集分析揭示了13个生物学过程、18个细胞组分及16个分子功能。KEGG富集分析得到549个信号通路。关键靶点的分子对接结果总体良好。结论指出，秋水仙碱可能通过如细胞色素c（CYCS）、髓过氧化物酶（MPO）及组蛋白去乙酰化酶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响应以及由SC1介导的p75NTR对细胞周期负调控有关，这些发现对于进一步的研究探索具有重要意义。然而，本研究仍需通过实验进行验证。未来的研究将基于这些靶点探索治疗冠状动脉疾病的新药。