To investigate the effects of artemisinin on inflammatory factors and intestinal microbiota in rats with ulcerative colitis based on network pharmacology - Guo, Yuxi; Li, Ze; Cheng, Nan; Jia, Xuemei; Wang, Jie; Ma, Hongyu; Zhao, Runyuan; Li, Bolin; Cai, Yanru; Yang, Qian (Frontiers in Gastroenterology, 2022)
Objective To investigate the therapeutic effect and possible mechanism of artemisinin on ulcerative colitis (UC) induced by sodium glucan sulfate (DSS) in rats based on network pharmacology. Methods First, according to the 3D structure of artemisinin, the effective targets of the active compounds were obtained through the Swissstarge website (www.swisstargetprediction.ch/) and the TargetNet website (http://targetnet.scbdd.com/). With the aid of Genecards (https://www.genecards.org/), OMIM (https://omim.org/), TTD (http://db.idrblab.net/ttd/) to obtain effective targets of disease. The disease gene-drug target network was constructed by extracting the intersection targets of the two, and the visualization operation and analysis were performed by using Cytoscape 3.7.2. Gene function enrichment analysis and pathway analysis were performed on the intersection targets with the help of R language software. Autidock Vina was used for molecular docking of artemisinin to key targets. Then, 40 male Wistar rats were randomly divided into normal group, model group, mesalazine group (0.315 g/kg·d) and artemisinin group (0.1 g/kg·d), with 10 rats in each group. Except for the normal group, the rats in the other groups were given 3.5% DSS solution freely for 10 days to replicate the UC model. After the successful modeling, the rats were given intragastric administration. The normal group and the model group were given the same amount of 0.9% normal saline, once a day, for 14 days. The general condition of the rats was recorded every day and the disease activity index (DAI) score was performed. After the administration, the colonic mucosal damage index (CMDI) was scored, the histopathological changes of the colon were observed by HE staining, and the levels or activities of serum CRP, TNF-α, MDA, SOD, HIF-1α and T-AOC were detected by ELISA, and fecal and intestinal microbiota of rats were detected by 16S rDNA sequencing. Results Network pharmacology shows that, there were 98 key targets of artemisinin screening, 4853 effective targets of UC, and 43 intersection targets for artemisinin and UC, involving 48 signaling pathways. The molecular docking results showed that the binding energies of the key proteins to artemisinin were less than -5.0 kJ·mol-1, and the binding energy of PTGS2 NOS3 to artemisinin was the best. Animal experiments have shown that, Compared with the model group, the DAI and CMDI scores of the artemisinin group and the mesalazine group decreased, the levels and activities of serum CRP, TNF-α, MDA and HIF-1α decreased, the levels and activities of SOD and T-AOC increased, the abundance and diversity of inteatinal microbiota increased, and the abundance of p-Acidobacteria, p-Chloroflexi, p-Gemmatimonadetes, p-Nitrospirae in artemisinin group increased (P＜0.05), and there was no significant change in others. Conclusion Artemisinin intervenes with UC through key target proteins such as PTGS2 and ESR1, and involves various biological processes such as inflammation and intestinal microbiota, revealing that molecular basis of artemisinin in the treatment of UC. Artemisinin is effective in improving the symptoms of UC rats, and its mechanism may be to relieve oxidative stress response by inhibiting inflammation, thus promoting intestinal mucosal repair. The regulatory effect on intestinal microbiota needs to be further studied.