[關(guān)鍵詞]
[摘要]
目的 探討小檗Berberis kansuensis Schneid.皮治療2型糖尿病的藥效物質(zhì)與作用機制。方法 基于藏藥小檗皮入血成分,利用SwissADME、TCMSP和Swiss Target Prediction數(shù)據(jù)庫分別開展活性成分初篩、潛在作用靶點預(yù)測,其次利用GeneCards、DisGeNET和DrugBank數(shù)據(jù)庫獲取2型糖尿病相關(guān)靶點,STRING數(shù)據(jù)庫構(gòu)建靶點蛋白相互作用(PPI)網(wǎng)絡(luò)篩選核心靶點,根據(jù)篩選結(jié)果應(yīng)用R語言開展基因本體(GO)生物功能和京都基因與基因組百科全書(KEGG)通路分析,最終利用Cytoscape 3.10.1軟件構(gòu)建“藥材-入血成分-靶點-通路-疾病”互作網(wǎng)絡(luò)篩選核心成分與關(guān)鍵靶點,以及開展分子對接驗證“核心成分-關(guān)鍵靶點”的生物活性。結(jié)果 活性初篩得到28個候選活性成分,經(jīng)Swiss Target Prediction預(yù)測后,得到571個成分作用靶點;網(wǎng)絡(luò)藥理學(xué)分析結(jié)果發(fā)現(xiàn),小檗皮與2型糖尿病有306個交集靶點,小檗皮可能通過8-氧化小檗堿、蟾毒色胺、蟾毒色胺內(nèi)鹽、小檗堿、藥根堿等成分,分別作用于磷脂酰肌醇3-激酶催化亞型(PIK3CA)、絲氨酸/蘇氨酸蛋白激酶(MAPK1)、B細(xì)胞κ輕肽基因增強子抑制因子(IKBKB)、蛋白激酶B1(Akt1)和表皮生長因子受體(EGFR)等關(guān)鍵靶點,調(diào)節(jié)磷脂酰肌醇3激酶(PI3K)/Akt、MAPK、腫瘤壞死因子(TNF)和核因子-κB(NF-κB)等信號通路,協(xié)同發(fā)揮抗糖尿病作用。結(jié)論 通過整合入血成分鑒定、網(wǎng)絡(luò)藥理學(xué)與分子對接結(jié)果,預(yù)測了小檗皮治療2型糖尿病的潛在藥效成分和作用靶點,為揭示小檗皮的藥效物質(zhì)基礎(chǔ)及其作用機制研究提供參考,也為小檗皮治療2型糖尿病的深入研究提供靶向。
[Key word]
[Abstract]
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.
[中圖分類號]
R285
[基金項目]
成都市科技項目(2018-YFYF-00053-SN)