目的 通過網(wǎng)絡(luò)藥理學(xué)和分子對接方法，篩選癲癇寧片治療癲癇的主要活性成分和分子機(jī)制。方法 采用TCMSP、Herb數(shù)據(jù)庫篩選癲癇寧片中的主要活性成分及靶點；GeneCard、OMIM、DisGent篩選癲癇的治療靶點；使用Cytoscape 3.8.2軟件構(gòu)建“藥物活性成分–靶點”網(wǎng)絡(luò)；將藥物–交集基因上傳至相互作用數(shù)據(jù)庫String構(gòu)建蛋白相互作用（PPI）網(wǎng)絡(luò)。將藥物–疾病交集基因上傳至利用生物信息學(xué)開源軟件Bioconductor，對其進(jìn)行生物學(xué)過程的基因本體論（GO）和京都基因與基因組百科全書（KEGG）通路富集分析，并對關(guān)鍵靶點與成分進(jìn)行分子對接驗證。結(jié)果 共篩選到癲癇寧片有效成分70個，靶點308個，其中degree前9位的活性成分分別為毛鉤藤堿、山柰酚、狼尾草麥角堿、β-谷甾醇；核心靶點共10個，分別為V-Rel網(wǎng)狀內(nèi)皮增生病毒癌基因同源物A（RELA）、轉(zhuǎn)錄因子AP-1（JUN）、有絲分裂原活化蛋白激酶1（MAPK1）、信號傳導(dǎo)和轉(zhuǎn)錄激活蛋白3（STAT3）、腫瘤蛋白p53（TP53）、蛋白激酶B1（Akt1）、雌激素受體α（ESR1）、腫瘤壞死因子（TNF）、有絲分裂原活化蛋白激酶8（MAPK8）。共篩選出5 195個GO條目，富集到259條與藥物治療癲癇相關(guān)的通路。分子對接結(jié)果顯示，核心靶點與活性成分間結(jié)合良好。結(jié)論 基于網(wǎng)絡(luò)藥理學(xué)和分子對接方法對癲癇寧片治療癲癇作用機(jī)制有了新的認(rèn)識，闡明藥物活性成分與癲癇的關(guān)系，為臨床藥物治療提供了科學(xué)依據(jù)。

Objective To screen the main active ingredients and molecular mechanism of Dianxianning Tablets through network pharmacology and molecular docking methods. Method TCMSP and Herb database were used to screen the main active ingredients and targets of Dianxianning Tablets. GeneCard, OMIM, and DisGent were selected as therapeutic targets for epilepsy. Construct the "drug active ingredient-target" network using Cytoscape 3.8.2 software. The drug-intersection gene was uploaded to the interaction database String to construct the PPI network. The drug-disease intersection genes were uploaded to Bioconductor, the bioinformatics software was used to GO and KEGG pathways of biological processes, and the key targets and components were validated by molecular docking. Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed, and key targets and components were validated by molecular docking. Results A total of 70 active ingredients and 308 targets were selected for Dianxianning Tablets, in which the first 9 active ingredients of the degree were hirsutine, kaempferol, penniclavin, and β-sitosterol, respectively. There are 10 core targets, including RELA, JUN, MAPK1, STAT3, TP53, Akt1, ESR1, TNF, MAPK8. A total of 5 195 GO entries were screened, and 259 pathways related to drug treatment of epilepsy were enriched. The results of molecular docking showed that the core target was well bound to the active ingredient. Conclusion This study provided a new understanding of DianxianNing Tables' benefitting effect for treatment of epilepsy based on network pharmacology and molecular docking technology, which jointly elucidated the relationship between the active ingredients of drugs and epilepsy, and provided a scientific basis for clinical drug treatment.

R285.5；R971