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Discussion On The Internal Mechanism Of The Biological Potency Detection Index Of Ranae Oviductus Based On Metabonomics

Posted on:2024-08-15Degree:MasterType:Thesis
Country:ChinaCandidate:Y GaoFull Text:PDF
GTID:2544307112487074Subject:Medicine identification study
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Objective: The research team has established a quality evaluation scheme for Ranae Oviductus based on aging as a detection index and using biological potency testing methods,but its mechanism of action has not been clarified.Therefore,this study combined pharmacodynamics,metabolomics and network pharmacology to clarify the anti-aging mechanism of Ranae Oviductus from the metabolic level and the computer simulation protein level.Methods: 48 mice were divided into control group,positive control group,model group and Ranae Oviductus(low,medium and high)group,with 8 mice in each group.The anti-aging effect of Ranae Oviductus was evaluated by behavioral test,serum biochemical index test and pathological tissue morphology change after successful intragastric administration of D-gal.On this basis,the best concentration of Ranae Oviductus was determined.The differential metabolites in the serum of mice with or without the intervention of Ranae Oviductus were detected by liquid chromatography-mass spectrometry,and multivariate statistical analysis was performed.In addition,the technology of network pharmacology is used to predict the key effective components and key targets of anti-aging of Ranae Oviductus and further predict the potential pathway.The molecular docking method is used to explore the interaction mode of key active ingredients and key targets.Further screen the interaction target between network pharmacology and metabolomics,analyze the KEGG pathway of the interaction target,use Western Blot experiment to verify the effect of Ranae Oviductus on the signal pathway,and comprehensively and specifically reveal the anti-aging mechanism of Ranae Oviductus.Results: The aging model of mice was constructed with D-gal,and the cognitive ability of aging mice was significantly improved after the intervention of Ranae Oviductus by water maze experiment.Ranae Oviductus can increase the activity of SOD and GSH-Px in serum of mice induced by D-gal,and reduce the level of MDA.The results of H&E staining showed that Ranae Oviductus can effectively improve the organ and tissue damage caused by D-gal stimulation in mice.A total of 36 different metabolites such as Taurine,Creatinine and Erucic acid were found in mouse serum samples,mainly involving beta-Alanine metabolism,Tryptophan metabolism,Histidine metabolism and other processes.The anti-aging mechanism of Ranae Oviductus was studied by using the network pharmacology method,and 154 targets were selected for the intersection of Ranae Oviductus and aging.Combined with the network topology analysis of "traditional Chinese medicine-effective ingredients-target-disease",Testosterone,Campesterol,11,14-Eicosadienoic acid and other key effective components were found,while TP53,MAPK3,SRC and other key targets were found through the PPI network topology analysis.In the molecular docking experiment,the binding energy between the receptor and the ligand is less than-5 kcal · mol-1,indicating that the ligand and the receptor bind well.Among them,the combination of Campesterol with key targets is better and the conformation is stable.Further carry out STRING interaction on the key targets of network pharmacology and metabolomics,and conduct pathway enrichment analysis on the interaction targets.Western blot results showed that the relative expression of p-PI3 K,p-Akt and HIF-1 α protein and the ratio of p-PI3 K / PI3 K and p-Akt / Akt were reduced in mouse brain tissue under Ranae Oviductus intervention.Conclusion: This study combined with network pharmacology and metabonomics to elaborate the anti-aging mechanism of Ranae Oviductus,and further proved the feasibility and scientific nature of Ranae Oviductus can be used for anti-aging.
Keywords/Search Tags:Metabonomics, Ranae Oviductus, Anti-aging, Network pharmacology
PDF Full Text Request
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