Exploring the Mechanism of Action of Glyasperin A in Intervening Menopause Based on Network Pharmacology and Molecular Docking Technology

[Objectives]To investigate the mechanism of action of glyasperin A(GAA)in intervening menopause using network pharmacology and molecular docking technology.[Methods]All target names of the active ingredients were screened using TCMSP,3D model molecules converted into SMILES online tool,Swiss target prediction and literature search.The relevant target genes corresponding to menopause were identified using the Genecards database.Venn 2.1.0 was then used to generate the corresponding Venn diagram.Finally,the protein-protein interaction(PPI)network was constructed using Cytoscape 3.9.1 software.The core targets that were screened underwent enrichment and analysis using the Gene Ontology(GO)biological process and KEGG pathways with the assistance of the DAVID database and bioinformatics.The molecular docking was then verified using AutoDock and Pymol software on the core targets.[Results]This study screened 100 target genes of active ingredients.In the PPI network,ESR1 and AKT1 were found to have a higher degree.The GO and KEGG enrichment analyses revealed that the biological processes primarily involved platelet activation,regulation of circadian rhythms,and regulation of mRNA stability.The signalling pathways included hepatitis B,cytotoxicity,and gastric cancer.The molecular docking results indicated that the key active ingredients and proteins bound well,as evidenced by their small binding energies.[Conclusions]Using a systematic network pharmacology approach,this study predicts the basic pharmacological effects and potential mechanisms of GAA in intervening menopause,which provides a foundation for further research on its pharmacological mechanisms.

Study on the Mechanism of Action of Glyasperin A in the Treatment of Atherosclerosis Based on Network Pharmacology and Molecular Docking

[Objectives] This study was conducted to investigate the mechanism of action of glyasperin A in the treatment of atherosclerosis using a network pharmacology approach. [Methods] Targets related to atherosclerosis were searched in GeneCards database. An active ingredient-disease-target network was constructed by Cytoscape 3.7.1. A target protein interaction network was constructed by String database. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the DAVID database. [Results] Glyasperin A acted on 36 atherosclerosis-related targets, and the biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, barrier, and lipid oxidation, etc. The results showed that glyasperin A acted on 36 atherosclerosis-related targets. The biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, positive regulation of protein localization to nucleus, and hepoxilin biosynthetic process, and it played an anti-fatigue role through signal pathways such as serotonergic synapse, efferocytosis, arachidonic acid metabolism, chemical carcinogenesis-receptor activation and platelet activation. [Conclusions] Glyasperin A has multi-target and multi-pathway effects in the treatment of atherosclerosis. This study provides reference for further research on glyasperin A in the treatment of atherosclerosis.

Therapeutic Effects and Potential Mechanisms of Glyasperin A against Myocardial Ischemia Based on Network Pharmacology and Molecular Docking

[Objectives]To explore the therapeutic effects and potential mechanisms of Glyasperin A(GAA)on myocardial ischemia(MI)based on network pharmacology and molecular docking.[Methods]The molecular structure of GAA was downloaded from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),and all targets of GAA were predicted by converting 3D model molecules into SMILES online tool and Swiss target prediction.Genecards database and DisGeNET database were used to find the targets related to MI,and then Venny 2.1.0 was used to generate the corresponding Wayne diagram,and then Cytoscape 3.9.1 software was used to construct the protein-protein interaction(PPI)network.With the help of DAVID database and Microbiology,the selected core targets were enriched and analyzed by gene ontology(GO),biological process(BP),and Kyoto Encyclopedia of Genes and Genomes(KEGG),and then the molecular docking between GAA and core targets was verified by AutoDock and Pymol software.[Results]A total of 1883 MI targets were screened,and in the protein-protein interaction network,AKT1,PTGS2,PPARG,ESR1,GSK3B were the proteins with higher values.Gene ontology and KEEG enrichment analysis showed that the biological processes involved mainly included inflammatory response,negative regulation of gene expression,and response to exogenous stimuli.Signaling pathways mainly include IL-17 signaling pathway,HIF-1 signaling pathway,and so on.The results of molecular docking showed that the binding energy of GAA and core protein was less than-5 Kcal/mol in four groups.These indicated that GAA with good binding had a certain therapeutic effect on myocardial ischemia.[Conclusions]Based on the systematic network pharmacology method,this study predicts the basic pharmacological effects and potential mechanisms of GAA in the treatment of MI,and reveals that GAA may treat MI through multiple targets and signaling pathways.It is expected to provide a basis for further study of its pharmacological mechanisms.

栽培甘草的化学成分及其抗菌活性研究

目的:为进一步利用甘草资源,为开发安全、绿色和无污染的植物源杀菌剂提供依据,对栽培甘草的化学成分进行研究。方法:运用硅胶、葡聚糖凝胶LH-20(Sephadex LH-20)及制备型高效液相色谱仪(HPLC)等多种色谱方法对甘草成分进行分离纯化,根据其理化性质和波谱数据对化合物的结构进行鉴定,采用菌丝生长速率法对甘草素(10)、半甘草异黄酮B(11)、isoangustone A(12)和粗毛甘草素C(13)4个酚类化合物进行了4种常见农业植物病原菌(油菜菌核菌、立枯丝核菌、番茄灰霉菌和小麦赤霉菌)的抗菌活性筛选。结果:从甘草中分离鉴定出14个化合物,半甘草异黄酮B和粗毛甘草素C对农业植物病原菌的抑制率较高。结论:本次实验报道了化合物10~13对常见农业植物病原菌的抗菌活性,其中半甘草异黄酮B抗菌效果显著。

基于Box-Behnken设计-响应面法与质量综合评价优化葛根芩连汤煎煮工艺

目的优化和科学评价葛根芩连汤(Gegen Qinlian Decoction,GQD)的煎煮工艺,为其经典方剂中药复方制剂的研究与开发奠定基础以及提供参考。方法以指纹图谱概貌结合多指标定量为综合评价,采用Box-Behnken设计-响应面法对加水量、浸泡时间、煎煮时间、煎煮次数进行优化。指纹图谱研究采用Waters Acquity UPLC BEH C_(18)色谱柱(100 mm×2.1 mm,1.7μm),流动相为乙腈-0.1%甲酸水溶液(梯度洗脱),体积流量为0.3 mL/min,柱温为35℃,进样量为1μL;采用电喷雾离子源,以正、负离子模式检测,在质荷比(m/z)50~1200进行扫描,建立29批GQD指纹图谱并对共有峰进行指认。对图谱信息进行主成分分析,建立UPLC多波长检测方法测定木兰花碱、葛根素、药根碱、巴马汀、黄芩苷、大豆苷元、黄芩素、甘草苷8个成分含量,计算各样品综合得分,优化煎煮工艺。结果建立了29个试验号GQD样品的UPLC-Q-TOF-MS正、负离子模式下指纹图谱。正、负离子模式下分别有共有峰23、19个,并对其进行指认,指认出葛根素、大豆苷元、黄芩素、黄芩苷、巴马汀、药根碱、木兰花碱、甘草苷、甘草次酸、大豆苷、异甘草苷、汉黄芩苷、汉黄芩素、甘草酸、glyasperins D、甘草醇、绿原酸、韧黄芩素Ⅱ。对共有峰中8个指标成分进行含量测定,以计算综合得分,综合得分结果显示,26号工艺为最佳工艺。最终确定GQD最佳煎煮工艺为加10倍量水,浸泡0.5 h,煎煮3次,每次0.5 h。结论所得出的GQD最佳煎煮工艺主要成分溶出率高,稳定可行,可为经典方剂GQD复方制剂的进一步研究和开发提供一定的依据。

甘草中抑制脂多糖诱导小鼠RAW264.7产生NO的活性成分研究

目的研究甘草Glycyrrhizae Radix et Rhizoma中的抗炎活性成分。方法采用大孔树脂、ODS、半制备液相等色谱手段进行分离纯化,并通过LC-MS、1H-NMR、13C-NMR等波谱技术进行结构鉴定。用细菌脂多糖(LPS)诱导小鼠巨噬细胞RAW264.7炎症模型对分离到的化合物进行抗炎活性筛选。结果从甘草中分离得到10个化合物,分别鉴定为甘草苷(1)、芹糖甘草苷(2)、异甘草苷(3)、芹糖异甘草苷(4)、sophoraisoflavone A(5)、粗毛甘草素F(6)、光甘草酮(7)、光甘草定(8)、甘草黄酮醇(9)和粗毛甘草素D(10)。结论化合物1、3、5、6、8和9对LPS诱导的RAW264.7细胞NO分泌有一定的抑制作用。其中化合物5、6和9抑制LPS诱导的RAW 264.7细胞NO分泌为首次报道。