Prediction of the molecular mechanism of eucommiae Cortex - Achyranthis bidentatae radix in the treatment of osteoarthritis: network pharmacology and molecular docking

To retrieve the core drug of osteoarthritis in clinic using Data Mining, predict the drug molecular action target through the Network Pharmacology, identify the key nodes of the interaction by combining with the related targtes of osteoarthritis, explore the pharmacological mechanism of Traditional Chinese Medicine against osteoarthritis and other possible mechanisms of actions. to retrieve the commonly used therapeutic formulations for osteoarthritis patients in clinical with PubMed, CNKI, VIP, CBM, Wan Fang Database and other databases, and screen out the core drugs through the Ancient and Modern Medical Case Cloud Platform and software Gephi, filter out the core drug molecules and targets combined with TCMSP database and the targets of osteoarthritis in Genecard and OMIM database, plunge those data into R project and Cytoscape to construct the intersection model of Drug molecule-osteoarthritis, establish PPI network and GO and conduct KEGG enrichment analysis with String database. Vina molecular docking was finally implemented to draw molecular docking diagram, and the results were analyzed after comprehensive analysis. The core drug pairs were identified as ‘Eucommiae Cortex - Achyranthis Bidentatae Radix’ through correlation analysis, complex network analysis based on the coefficient. ‘Eucommiae Cortex - Achyranthis Bidentatae Radix’ can intervene cell behavior through multiple pathways and regulate cell metabolism, cytokine synthesis, oxidative and cellular immunity with the help of topology analysis in String Database. The core molecules of Quercetin and Kaempferol derived from ‘Eucommia bark – achyranthes’ can change the spatial conformation of PTGSs by hydrogen bonding with PTGSs, the hydrophobic bonds and van der Waals forces generated by Baicalein, Wogonin and β-carotene, thereby changing the activity of PTGSs and affecting bone properties the process of osteoarthritis.

本研究借助数据挖掘（Data Mining）技术检索临床治疗骨关节炎（osteoarthritis）的核心药物，通过网络药理学（Network Pharmacology）预测药物分子作用靶点，结合骨关节炎相关靶点明确相互作用的关键节点，探究中药抗骨关节炎的药理作用机制及其他潜在作用途径。通过PubMed、中国知网（CNKI）、维普资讯（VIP）、中国生物医学文献数据库（CBM）、万方数据库等数据库检索临床骨关节炎患者常用治疗方剂，依托古今医案云平台与Gephi软件筛选核心药物，结合中药系统药理学数据库与分析平台（TCMSP）、Genecard数据库及在线人类孟德尔遗传数据库（OMIM）中的骨关节炎靶点筛选核心药物分子及对应靶点；将上述数据导入R语言项目（R project）与Cytoscape软件，构建药物分子-骨关节炎交集模型，构建蛋白质相互作用（Protein-Protein Interaction, PPI）网络与基因本体（Gene Ontology, GO）注释，并通过String数据库开展京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析。最终采用Vina分子对接（Vina molecular docking）技术绘制分子对接图，并经综合分析后解读研究结果。经相关性分析与基于系数的复杂网络分析，确定核心药对为杜仲（Eucommiae Cortex）-牛膝（Achyranthis Bidentatae Radix）。依托String数据库的拓扑分析结果可知，该杜仲-牛膝药对可通过多条通路干预细胞行为，调控细胞代谢、细胞因子合成、氧化应激及细胞免疫过程。从该药对中提取的核心分子槲皮素（Quercetin）与山奈酚（Kaempferol）可通过与环氧合酶（Prostaglandin-endoperoxide Synthase, PTGSs）形成氢键改变其空间构象；黄芩素（Baicalein）、汉黄芩素（Wogonin）及β-胡萝卜素（β-carotene）则可通过疏水作用与范德华力发挥类似调控作用，进而改变环氧合酶活性，影响骨关节炎进程中的骨代谢状态。