目的 运用网络药理学和动物实验相结合的方法，多维度挖掘金线莲Anoectochilus roxburghii治疗2型糖尿病的作用机制，为金线莲的开发利用提供依据。方法 通过文献检索建立金线莲化合物数据库，检索Swiss Target Prediction数据库和Similarity ensemble approach数据库获取金线莲化合物的作用靶标，检索Disgenet和GeneCards数据库获得2型糖尿病的相关靶标。利用软件Venny 2.1筛选出金线莲与2型糖尿病的共有靶标。运用String数据库构建共有靶标的蛋白相互作用（protein-protein interaction，PPI）网络，通过NetworkAnalyzer工具和MCODE插件进行拓扑分析、基因簇分析及核心靶标的筛选。通过基因注释工具DAVID对核心靶标进行基因本体（gene ontology，GO）和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）富集分析。采用高糖、高脂饲料诱导结合小剂量链脲佐菌素（40 mg/kg）一次性ip构建2型糖尿病大鼠模型，将造模成功大鼠分为对照组、模型组、二甲双胍组和金线莲高、中、低剂量组，持续给药3周，采用酶联免疫法检测大鼠给药后血清中相应预测的8种靶标的水平。结果 从数据库中获得80个金线莲化学成分，金线莲成分作用靶标与2型糖尿病的共有靶标有249个。金线莲治疗2型糖尿病的关键活性成分为槲皮素、异鼠李素、金线莲苷、齐墩果酸和熊果酸，主要调控靶标包括白细胞介素-2（interleukin-2，IL-2）、蛋白酪氨酸磷酸酶-1B（protein tyrosine phosphatase-1B，PTP-1B）、花生四烯酸-5-脂加氧酶（arachidonic acid-5-lipoxygenase，ALOX-5）、环氧化酶-2（cyclooxygenenase-2，COX-2）、醛糖还原酶（aldose reductase，AR）、细胞色素P4501B1（cytochrome P4501B1，CYP1B1）、细胞色素P45019A1（cytochrome P45019A1，CYP19A1）及乙酰胆碱酯酶（acetylcholinesterase，AChE）。动物实验结果显示，与模型组相比，金线莲各剂量组大鼠血清IL-2、ALOX5、CYP1B1和CYP19A1水平不同程度升高，COX-2、AR、PTP1B和AChE水平不同程度降低。结论 金线莲可以通过减少炎症信号通路关键酶的表达，改善胰岛素抵抗从而发挥降血糖的作用，具有多成分、多靶标及多通路的治疗特点，值得临床推广运用。

Objective A multi-dimensional mining strategy was proposed for elucidating the action mechanism of Jinxianlian (Anoectochilus roxburghii) in the treatment of type 2 diabetic mellitus by using a combination of network pharmacology and animal experiments, which will provide a basis for the development and application of A. roxburghii. Methods The compound database of A. roxburghii was established by literature search, whereas the targets of the compounds were obtained by browsing the Swiss Target Prediction database and the Similarity ensemble approach database. Targets of type 2 diabetic mellitus was obtained by using Disgenet and GeneCards databases. The software Venny 2.1 was applied to screen out the shared targets of A. roxburghii and type 2 diabetic mellitus. String database was interrogated to construct the protein-protein interaction (PPI) network for the shared targets. Network Analyzer tool and the MCODE plug-in were employed to perform topology analysis, gene cluster analysis, and core target screening. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the core target was carried out by the gene annotation tool DAVID. Furthermore, high-sugar and high-fat feed administration and one-time intraperitoneal injection of low-dose streptozotocin were implemented to induce a type 2 diabetic rat model. The rats were divided into control group, model group, metformin positive group, high dosage group, medium dosage group, and low dosage group of A. roxburghii. According to the predicted results of network pharmacology, enzyme-linked immunosorbent assay was used to detect the level of the eight predicted core targets in the serum of rats after administration. Results Eighty chemical components of A. roxburghii were collected from databases. A total of 249 shared targets of A. roxburghii and type 2 diabetic mellitus were identified. The key bioactive ingredients of A. roxburghii in the treatment of type 2 diabetic mellitus include quercetin, isorhamnetin, anoectin, oleanolic acid, and ursolic acid, which were mainly related to targets including interleukin-2 (IL-2), protein tyrosine phosphatase-1B (PTP1B), arachidonic acid-5-lipoxygenase (ALOX5), cyclooxygenase-2 (COX-2), aldose reductase (AR), cytochrome P4501B1(CYP1B1), cytochrome P45019A1 (CYP19A1) and acetylcholinesterase (AChE). Compared with the model group, the serum levels of IL-2, ALOX5, CYP1B1 and CYP19A1 were increased in all dosage groups of A. roxburghii, whereas the levels of COX-2, AR, PTP1B and AChE were reduced in all dosage groups of A. roxburghii. Conclusion A. roxburghii can reduce the expression of key enzymes in inflammatory signal pathways and improve insulin resistance to lower blood sugar. It owns the characteristics of multi-component, multi-target and multi-pathway, which is worthy of clinical application.

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国家自然科学基金项目（81703701）；浙江省自然科学基金项目（Y21H280036）