Ju Yunjie
Medical College of China Three Gorges University, China Three Gorges University, Yichang 443002, China.
Appl Bionics Biomech. 2022 Apr 21;2022:5997895. doi: 10.1155/2022/5997895. eCollection 2022.
To study the mechanism of osthole in GC based on network pharmacology and molecular docking.
The potential targets of osthole were predicted through the TCM System Pharmacology Analysis Platform, SwissTargetPrediction, and PharmMapper database. Targets related to gastric cancer were obtained through OMIM and GeneCard database. The online tool Venny 2.1.0 was used to screen GC and common target of osthole. The targets after the intersection of drugs and diseases were entered into the STRING database, and the protein interaction network was constructed, and the core targets with high correlation were screened out. The WebGestalt website was used to GO functional enrichment and KEGG pathway analysis and visualization with KOBAS website. The Cytoscape 3.8.2 was employed to draw the C-T-P-D (compound-target-pathway-disease) network visualization diagram. Finally, molecular docking validation was performed using PyMOL 2.5 and Discovery Studio Standalone.
Through prediction and screening, 108 corresponding targets were screened from osthole, and 173 targets were obtained after intersecting with gastric cancer targets. Among them, the top ten targets were the core targets of this study, including MAPK3, MAPK1, SRC, AKT1, HSP90AA1, RXRA, ESR1, RELA, MAPK14, and EGFR. The analysis of GO, KEGG, and PPI showed that the mechanism of action of osthole against GC may be closely related to the regulation of the PI3K signaling pathway. The results of molecular docking showed that osthole had a good affinity with MAPK3, which is a crucial part of the PI3K signaling pathway.
This study preliminarily revealed the targets and related pathways of osthole in the treatment of gastric cancer and provided a new idea for further exploration of osthole targeted prevention and treatment of gastric cancer.
基于网络药理学和分子对接研究蛇床子素治疗胃癌的作用机制。
通过中药系统药理学分析平台、SwissTargetPrediction和PharmMapper数据库预测蛇床子素的潜在靶点。通过OMIM和GeneCard数据库获取与胃癌相关的靶点。使用在线工具Venny 2.1.0筛选胃癌与蛇床子素的共同靶点。将药物与疾病交集后的靶点输入STRING数据库，构建蛋白质相互作用网络，筛选出相关性高的核心靶点。利用WebGestalt网站进行GO功能富集和KEGG通路分析，并通过KOBAS网站进行可视化。采用Cytoscape 3.8.2绘制C-T-P-D（化合物-靶点-通路-疾病）网络可视化图。最后，使用PyMOL 2.5和Discovery Studio Standalone进行分子对接验证。
通过预测和筛选，从蛇床子素中筛选出108个对应靶点，与胃癌靶点交集后得到173个靶点。其中，前十个靶点为本研究的核心靶点，包括MAPK3、MAPK1、SRC、AKT1、HSP90AA1、RXRA、ESR1、RELA、MAPK14和EGFR。GO、KEGG和PPI分析表明，蛇床子素抗胃癌的作用机制可能与PI3K信号通路的调控密切相关。分子对接结果显示，蛇床子素与MAPK3具有良好的亲和力，MAPK3是PI3K信号通路的关键部分。
本研究初步揭示了蛇床子素治疗胃癌的靶点及相关通路，为进一步探索蛇床子素靶向防治胃癌提供了新思路。
