目的 探讨小檗Berberis kansuensis Schneid.皮治疗2型糖尿病的药效物质与作用机制。方法 基于藏药小檗皮入血成分，利用SwissADME、TCMSP和Swiss Target Prediction数据库分别开展活性成分初筛、潜在作用靶点预测，其次利用GeneCards、DisGeNET和DrugBank数据库获取2型糖尿病相关靶点，STRING数据库构建靶点蛋白相互作用（PPI）网络筛选核心靶点，根据筛选结果应用R语言开展基因本体（GO）生物功能和京都基因与基因组百科全书（KEGG）通路分析，最终利用Cytoscape 3.10.1软件构建“药材-入血成分-靶点-通路-疾病”互作网络筛选核心成分与关键靶点，以及开展分子对接验证“核心成分-关键靶点”的生物活性。结果 活性初筛得到28个候选活性成分，经Swiss Target Prediction预测后，得到571个成分作用靶点；网络药理学分析结果发现，小檗皮与2型糖尿病有306个交集靶点，小檗皮可能通过8-氧化小檗碱、蟾毒色胺、蟾毒色胺内盐、小檗碱、药根碱等成分，分别作用于磷脂酰肌醇3-激酶催化亚型（PIK3CA）、丝氨酸/苏氨酸蛋白激酶（MAPK1）、B细胞κ轻肽基因增强子抑制因子（IKBKB）、蛋白激酶B1（Akt1）和表皮生长因子受体（EGFR）等关键靶点，调节磷脂酰肌醇3激酶（PI3K）/Akt、MAPK、肿瘤坏死因子（TNF）和核因子-κB（NF-κB）等信号通路，协同发挥抗糖尿病作用。结论 通过整合入血成分鉴定、网络药理学与分子对接结果，预测了小檗皮治疗2型糖尿病的潜在药效成分和作用靶点，为揭示小檗皮的药效物质基础及其作用机制研究提供参考，也为小檗皮治疗2型糖尿病的深入研究提供靶向。

Objective To explore the effective substances and mechanism of Berberidis Cortex in treating type 2 diabetes mellitus. Methods Based on the absorbed components derived from Berberidis Cortex, SwissADME, TCMSP, and Swiss Target Prediction databases were employed to conduct an initial activity assessment and forecast potential targets. Subsequently, GeneCards, DisGeNET, and DrugBank databases were utilized to obtain targets related to type 2 diabetes mellitus. The STRING database was used to construct a protein interaction network of targets for core target selection. R language was applied for GO function and KEGG pathway analysis based on the screening results. Finally, Cytoscape 3.10.1 software was used to construct an interaction network of “herbs - absorbed components - targets - signal pathways - disease” to screen core and key targets. Additionally, molecular docking was performed to verify the biological activity of “core components - key targets”. Results After preliminary activity screening, 28 candidate active components were obtained, and subsequent Swiss Target Prediction predicted interactions with 571 components. Network pharmacology analysis revealed that Berberidis Cortex had 306 intersecting targets with type 2 diabetes mellitus. Berberidis Cortex potentially exerts its anti-diabetic effects through components such as 8-oxoberberine, bufotenine, bufotenidine, berberine, and jatrorrhizine, acting on key targets like PIK3CA, MAPK1, IKBKB, Akt1, and EGFR. This modulation occurs through PI3K/Akt, MAPK, TNF, and NF-κB signaling pathways, collectively contributing to its anti-diabetic effects. Conclusion By integrating the identification of absorbed components, network pharmacology, and molecular docking results, predicted potential therapeutic components and targets of Berberidis Cortex in treating type 2 diabetes mellitus were preliminarily predicted. This provides a reference for revealing the pharmacological substance basis and mechanism of action of Berberidis Cortex and a target for further research on treating type 2 diabetes mellitus with Berberidis Cortex.

R285

成都市科技项目(2018-YFYF-00053-SN)