目的 基于網(wǎng)絡(luò)藥理學(xué)、分子對(duì)接及細(xì)胞實(shí)驗(yàn)探究當(dāng)歸補(bǔ)血湯抗糖尿病腎病（DN）的作用機(jī)制。方法 利用中藥系統(tǒng)藥理學(xué)數(shù)據(jù)庫(kù)與分析平臺(tái)（TCMSP）及中藥綜合數(shù)據(jù)庫(kù)（TCMID），篩選當(dāng)歸補(bǔ)血湯中黃芪與當(dāng)歸的有效成分；通過(guò)UniProt和Swiss Target Prediction數(shù)據(jù)庫(kù)，識(shí)別活性成分的相關(guān)靶點(diǎn)；利用GeneCards與OMIM數(shù)據(jù)庫(kù)預(yù)測(cè)DN的潛在靶點(diǎn)；基于獲取的數(shù)據(jù)，利用STRING數(shù)據(jù)庫(kù)以及Cytoscape軟件構(gòu)建蛋白質(zhì)-蛋白質(zhì)相互作用（PPI）網(wǎng)絡(luò)及“藥物-活性成分-靶點(diǎn)”網(wǎng)絡(luò)。利用DAVID數(shù)據(jù)庫(kù)對(duì)上述靶點(diǎn)進(jìn)行了基因本體（GO）注釋及京都基因與基因組百科全書(shū)（KEGG）通路富集分析。通過(guò)分子對(duì)接實(shí)驗(yàn)及細(xì)胞實(shí)驗(yàn)進(jìn)行驗(yàn)證，揭示當(dāng)歸補(bǔ)血湯治療DN的作用機(jī)制。結(jié)果 網(wǎng)絡(luò)藥理學(xué)分析，得到當(dāng)歸補(bǔ)血湯32個(gè)活性成分，與疾病交集靶點(diǎn)255個(gè)； KEGG通路富集結(jié)果顯示，關(guān)鍵靶點(diǎn)主要參與晚期糖基化終末產(chǎn)物及其受體（AGE/RAGE）信號(hào)通路、脂質(zhì)代謝異常導(dǎo)致的動(dòng)脈粥樣硬化通路等多個(gè)與免疫反應(yīng)和炎癥過(guò)程密切相關(guān)的信號(hào)通路。此外，分子對(duì)接研究表明，該方劑的主要化學(xué)成分對(duì)于AGE/RAGE信號(hào)通路上的主要靶點(diǎn)表現(xiàn)出良好的結(jié)合能力。細(xì)胞實(shí)驗(yàn)結(jié)果表明，當(dāng)歸補(bǔ)血湯能夠抵抗HK-2細(xì)胞經(jīng)高糖誘導(dǎo)產(chǎn)生的炎癥反應(yīng)，并且能夠抑制AGE/RAGE信號(hào)通路上的核心蛋白表達(dá)。結(jié)論 當(dāng)歸補(bǔ)血湯可能通過(guò)抑制AGE/RAGE信號(hào)通路，減輕高糖所致的炎癥反應(yīng)，從而達(dá)到治療DN的目的，可為當(dāng)歸補(bǔ)血湯深入研究提供方向。

Objective To investigate the mechanism of Danggui Buxue Decoction (DBD) against diabetic nephropathy (DN) based on network pharmacology, molecular docking and cell experiments. Methods Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Traditional Chinese Medicine Integrated Database (TCMID) were used to screen the active components of Astragalus membranaceus and Angelica sinensis in DBD. Potential targets of these active compounds were identified using the UniProt and Swiss Target Prediction databases. Disease-related targets of DN were retrieved from GeneCards and OMIM. Protein-protein interaction (PPI) networks and a "drug-active component-target" network were constructed using the STRING database and visualized with Cytoscape. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, was performed using the DAVID database. The key findings were further validated through molecular docking and in vitro cell experiments. Results Network pharmacology analysis identified 32 active components in DBD and 255 overlapping targets associated with DN. KEGG pathway enrichment revealed that the core targets were primarily involved in the AGE/RAGE (advanced glycation end products/receptor for AGEs) signaling pathway, atherosclerosis pathways linked to lipid metabolism disorders, and other critical pathways related to immune response and inflammatory processes. Molecular docking studies demonstrated strong binding affinities between the major bioactive compounds of DBD and key targets in the AGE/RAGE pathway. In vitro experiments confirmed that DBD significantly attenuated high glucose-induced inflammatory responses in HK-2 cells and suppressed the expression of core proteins in the AGE/RAGE signaling pathway. Conclusion DBD may exert therapeutic effects against diabetic nephropathy by inhibiting the AGE/RAGE signaling pathway, thereby alleviating hyperglycemia-induced inflammation. These findings provide a scientific foundation for further research into the pharmacological mechanisms of DBD in DN treatment.

R285.5

江蘇省基礎(chǔ)研究計(jì)劃自然科學(xué)基金-前沿引領(lǐng)技術(shù)基礎(chǔ)研究專(zhuān)項(xiàng)（ BK20232014）