目的 基于GEO數(shù)據(jù)庫(kù)挖掘多發(fā)性硬化癥(multiple sclerosis,MS)疾病進(jìn)展的潛在藥物靶點(diǎn),并通過(guò)反向篩選預(yù)測(cè)具有干預(yù)作用的中藥活性成分,為MS的中醫(yī)藥治療提供理論依據(jù)。方法 整合GSE224377和GSE149326數(shù)據(jù)集,篩選MS患者白質(zhì)病灶區(qū)與正常外觀白質(zhì)的差異表達(dá)基因(differentially expressed genes,DEGs),結(jié)合加權(quán)基因共表達(dá)網(wǎng)絡(luò)分析(weighted gene co-expression network analysis,WGCNA)鑒定疾病進(jìn)展相關(guān)核心模塊。利用基因本體(gene ontology,GO)和京都基因與基因組百科全書(shū)(Kyoto encyclopedia of genes and genomes,KEGG)富集分析關(guān)鍵基因的生物學(xué)功能及通路。通過(guò)ETCM、TCMIP和NPASS數(shù)據(jù)庫(kù)反向篩選靶向中藥成分,結(jié)合Swiss Target Prediction評(píng)估成藥性,使用Autodock vina進(jìn)行分子對(duì)接驗(yàn)證核心靶點(diǎn)髓鞘堿性蛋白(myelin basic protein,MBP)和少突膠質(zhì)細(xì)胞轉(zhuǎn)錄因子2(oligodendrocyte transcription factor 2,OLIG2)與中藥成分的結(jié)合潛力。結(jié)果 共鑒定172個(gè)DEGs(59個(gè)上調(diào)、113個(gè)下調(diào)),加權(quán)基因共表達(dá)網(wǎng)絡(luò)分析(weighted correlation network analysis,WGCNA)揭示11個(gè)與MS表型顯著相關(guān)的基因模塊,其中藍(lán)色模塊(107個(gè)樞紐基因)與疾病進(jìn)展相關(guān)性最高(相關(guān)系數(shù)=0.74)。GO和KEGG分析顯示,關(guān)鍵基因富集于髓鞘形成、軸突導(dǎo)向及血腦屏障破壞相關(guān)通路。根據(jù)8個(gè)疾病核心靶點(diǎn)匹配到45個(gè)中藥成分,來(lái)源于62個(gè)中藥。45個(gè)成分與MBP、OLIG2分子對(duì)接結(jié)果表明,涼薯素(與OLIG2結(jié)合能:-8.2 kcal/mol,與MBP結(jié)合能:7 kcal/mol)、白屈菜紅堿(與MBP結(jié)合能:-7.5 kcal/mol)等成分與靶點(diǎn)的結(jié)合能力顯著。結(jié)論 系統(tǒng)鑒定了MS進(jìn)展的核心基因及通路,并預(yù)測(cè)了多種潛在中藥活性成分,為MS的分子機(jī)制解析及中藥干預(yù)策略開(kāi)發(fā)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

國(guó)家自然科學(xué)基金面上項(xiàng)目（82174046）；中國(guó)醫(yī)學(xué)科學(xué)院醫(yī)學(xué)與健康科技創(chuàng)新工程（2021 I2M-1-031）；名貴中藥資源可持續(xù)利用能力建設(shè)項(xiàng)目（2060302）