Exploration of medication rules and mechanisms of traditional Chinese medical doctor Jia Yuejin for treating depressive disorder based on bio-informatic method
10.3760/cma.j.cn115398-20201031-00209
- VernacularTitle:基于生物信息学探讨贾跃进治疗抑郁症用药规律和作用机制
- Author:
Yi LIU
1
;
Ruimin WANG
;
Fei LI
;
Yuejin JIA
Author Information
1. 山西中医药大学第二临床学院，太原 030024
- Keywords:
Depression;
Data mining;
Network pharmacology;
Molecular docking;
Mechanism;
Jia Yuejin;
Ancient and Modern Medical Records Cloud Platform
- From:
International Journal of Traditional Chinese Medicine
2022;44(4):428-437
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the medication rules and mechanisms of traditional Chinese medical doctor Jia Yuejin for treating depressive disorder based on data mining and network pharmacology. Methods:The medication rules and core prescription were analyzed with the statistics of frequency, properties and analysis of correlation, clustering, and complex network of prescriptions for the treatment of depressive disorder from the outpatient service of Professor Jia in the past five years, from 1st Jan. 2016 to 1st Jul. 2020, with the help of the Ancient and Modern Medical Records Cloud Platform (V 2.2.3). Then we obtained the targets of effective ingredients of each drug of the core prescription and disease targets and took the intersection by virtue of TCMSP, GEO and other databases. We used Cytoscape V 3.8.0 to construct disease-drug-ingredient-target and protein-protein interaction networks, and performed GO and KEGG pathway enrichment analysis, and finally selected the key effective ingredients and key targets to apply software of Vina to molecularly dock. Results:A total of 120 medical records, 148 prescriptions and 138 drugs were obtained. The most common drug properties were gentle, warm, cold. The main tastes were sweet, pungent and bitter, and the meridians were concentrated in two spleen and liver meridians. The core prescription of 8 drugs was obtained through analysis of drug correlation, clustering and complex network. A total of 80 effective ingredients, 772 related targets, 542 intersectional genes of the core prescription were obtained, the key ingredients included dehydroeburicoic acid, α-Amyrin, and the key targets included AKT1, ESR1. The GO enrichment analysis showed metabolic process, immune system process, signaling process, and the KEGG pathway enrichment analysis showed neuroactive ligand-receptor interaction, NF-κB signaling pathway. The results of molecular docking of key ingredients and key targets showed them stable binding.Conclusion:The rules of Chinese Medicines of Professor Jia for depressive disorders show the related multi-ingredient, multi-target, multi-pathway mechanisms, which can provide references for clinical use and further research.
