目的 基于GEO数据库挖掘多发性硬化症(multiple sclerosis,MS)疾病进展的潜在药物靶点,并通过反向筛选预测具有干预作用的中药活性成分,为MS的中医药治疗提供理论依据。方法 整合GSE224377和GSE149326数据集,筛选MS患者白质病灶区与正常外观白质的差异表达基因(differentially expressed genes,DEGs),结合加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)鉴定疾病进展相关核心模块。利用基因本体(gene ontology,GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析关键基因的生物学功能及通路。通过ETCM、TCMIP和NPASS数据库反向筛选靶向中药成分,结合Swiss Target Prediction评估成药性,使用Autodock vina进行分子对接验证核心靶点髓鞘碱性蛋白(myelin basic protein,MBP)和少突胶质细胞转录因子2(oligodendrocyte transcription factor 2,OLIG2)与中药成分的结合潜力。结果 共鉴定172个DEGs(59个上调、113个下调),加权基因共表达网络分析(weighted correlation network analysis,WGCNA)揭示11个与MS表型显著相关的基因模块,其中蓝色模块(107个枢纽基因)与疾病进展相关性最高(相关系数=0.74)。GO和KEGG分析显示,关键基因富集于髓鞘形成、轴突导向及血脑屏障破坏相关通路。根据8个疾病核心靶点匹配到45个中药成分,来源于62个中药。45个成分与MBP、OLIG2分子对接结果表明,凉薯素(与OLIG2结合能:-8.2 kcal/mol,与MBP结合能:7 kcal/mol)、白屈菜红碱(与MBP结合能:-7.5 kcal/mol)等成分与靶点的结合能力显著。结论 系统鉴定了MS进展的核心基因及通路,并预测了多种潜在中药活性成分,为MS的分子机制解析及中药干预策略开发提供新思路。

Objective To identify potential drug targets for multiple sclerosis (MS) progression by mining the GEO database and predict bioactive components from traditional Chinese medicine (TCM) with intervention effects through reverse screening, providing a theoretical basis for TCM-based MS treatment. Methods Datasets GSE224377 and GSE149326 were integrated to identify differentially expressed genes (DEGs) between white matter lesions (WML) and normal-appearing white matter (NAWM) in MS patients. Weighted gene co-expression network analysis (WGCNA) was employed to identify key modules associated with disease progression. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were conducted to elucidate the biological functions and pathways of critical genes. Potential TCM components targeting these genes were screened using the ETCM, TCMIP, and NPASS databases, followed by druggability assessment via Swiss Target Prediction. Molecular docking (AutoDock vina) was performed to validate interactions between core targets myelin basic protein (MBP) and oligodendrocyte transcription factor 2 (OLIG2) and predicted TCM compounds. Results A total of 172 DEGs (59 upregulated, 113 downregulated) were identified. WGCNA revealed 11 gene modules significantly associated with MS phenotypes, with the blue module (107 hub genes) showing the highest correlation with disease progression (correlation coefficient = 0.74). GO and KEGG analyses indicated enrichment in pathways related to myelination, axon guidance, and blood-brain barrier disruption. Reverse screening identified 45 TCM bioactive components (derived from 62 herbs) targeting eight core disease-related genes. Molecular docking demonstrated strong binding affinities between key targets and TCM compounds, including pachyrhizin (binding energy with OLIG2: -8.2 kcal/mol, binding energy with MBP: -7 kcal/mol) and chelerythrine (binding energy with MBP: -7.5 kcal/mol). Conclusion This study systematically identified core genes and pathways involved in early MS progression and predicted multiple potential TCM-derived bioactive compounds, offering novel insights into the molecular mechanisms of MS and the development of TCM-based intervention strategies.

Q811.4;R285

国家自然科学基金面上项目（82174046）；中国医学科学院医学与健康科技创新工程（2021 I2M-1-031）；名贵中药资源可持续利用能力建设项目（2060302）