Mechanisms Underlying the Therapeutic Effects of Huangqi, Gegen, Renshen and Sangye in Treating Diabetic Cardiomyopathy Based on Data Mining, Network Pharmacology and Molecular Docking

A B S T R A C T

Objective: To evaluate the therapeutic effects of traditional Chinese medicines Radix astragali (Huangqi, HQ), Ginseng (Renshen, RS), Radix puerariae (Gegen, GG), and Mulberry leaf (Sangye, SY) on diabetic cardiomyopathy (DC) based on bioinformatics and network pharmacology, through gene expression analysis of geo clinical samples, molecular docking of compounds and targets, and molecular dynamics simulation, and to discover new targets for prevention or treatment of DC, in order to facilitate and better serve the discovery of new drugs as well as their application in the clinic.
Materials and Methods: For the initial selection of ingredients and targets using the TCMSP as a starting point, we performed a primary screening of ingredients and targets of the four herbs using tools including Cytoscape, Tbtools, R 4.0.2, Autodock Vina, PyMOL, and GROMACS. To further screen the effective ingredients and targets, we performed protein interaction network (PPI) analysis (gene = 12), gene expression analysis (n = 24) by clinical samples of DCs from the gse26887 dataset, biological process (BP) analysis (FDR ≤ 0.05, gene = 7), KEGG pathway analysis (FDR ≤ 0.05, gene = 7), and ingredient target pathway network analysis (gene = 7) by applying these targets from the screen, Biological processes, disease pathways regulated by targets and the relationship between each component target and pathway were obtained. We further screened the targets and visualized the docking results by precision molecular docking of ingredients and targets, after which we performed molecular dynamics simulation and consulted a large number of relevant literature for validation of the results.
Results: Through screening, analysis and validation of the data, we finally confirmed the presence of 36 active ingredients in HQ, RS, GG, and SY, which mainly act on AKT1, ADRB2, GSK3B, PPARG, and BCL2 targets, and these five targets mainly regulate PI3K-Akt, Adrenergic signaling in cardiomyocytes, AGE-RAGE signaling pathway in diabetic complications, JAK-STAT, cGMP-PKG, AMPK, and mTOR signaling pathway exert preventive or therapeutic effects on DCM. Molecular dynamics (MD) simulations revealed that the complex formed by Calycosin, Frutinone A, Puerarin, Inophyllum E, the four active components of HQ, RS, GG, and SY, and the four target proteins ADRB2, PPARG, AKT1, and GSK3B acting on DCS is able to exist in a very stable tertiary structure under human environment.
Conclusion: Our study successfully explains the effective mechanism of HQ, RS, GG, and SY in ameliorating DC, while predicting the potential targets and active components of HQ, RS, GG, and SY in treating DC, which provides a new basis for investigating novel mechanisms of action at the network pharmacology level and a great support for subsequent DC research.

Keywords

Molecular dynamics simulation, PI3K-Akt signaling pathway, mTOR signaling pathway, diabetic cardiomyopathy, Puerarin

Get access to the full version of this article.

Article Info

Article Type

Publication history

Copyright

Author Info

Xing-Chen Guo Wan-Hao Gao Zhi-Wen Zhang Dong-Dong Zhang Mu-Wei Li

Corresponding Author

Figures & Tables

Get access to the full version of this article.

References

1.     Dillmann WH (2019) Diabetic Cardiomyopathy. Circ Res 124: 1160-1162. [Crossref]

2.     Rubler S, Dlugash J, Yuceoglu YZ, Kumral T, Branwood AW et al. (1972) New type of cardiomyopathy associated with diabetic glomerulosclerosis. Am J Cardiol 30: 595-602. [Crossref]

3.     Kannel WB, Hjortland M, Castelli WP (1974) Role of diabetes in congestive heart failure: the Framingham study. Am J Cardiol 34: 29-34. [Crossref]

4.     Jia G, Whaley Connell A, Sowers JR (2018) Diabetic cardiomyopathy: a hyperglycaemia- and insulin-resistance-induced heart disease. Diabetologia 61: 21-28. [Crossref]

5.     Ma H, Li SY, Xu P, Babcock SA, Dolence EK et al. (2009) Advanced glycation endproduct (AGE) accumulation and AGE receptor (RAGE) up-regulation contribute to the onset of diabetic cardiomyopathy. J Cell Mol Med 13: 1751-1764. [Crossref]

6.     Sokos GG, Nikolaidis LA, Mankad S, Elahi D, Shannon RP (2006) Glucagon-like peptide-1 infusion improves left ventricular ejection fraction and functional status in patients with chronic heart failure. J Card Fail 12: 694-699. [Crossref]

7.     Udell JA, Cavender MA, Bhatt DL, Chatterjee S, Farkouh ME et al. (2015) Glucose-lowering drugs or strategies and cardiovascular outcomes in patients with or at risk for type 2 diabetes: a meta-analysis of randomised controlled trials. Lancet Diabetes Endocrinol 3: 356-366. [Crossref]

8.     Eraky SM, Ramadan NM (2021) Effects of omega-3 fatty acids and metformin combination on diabetic cardiomyopathy in rats through autophagic pathway. J Nutr Biochem 2021: 108798. [Crossref]

9.     Zhen YP, Zhao SB, Zhong MW, Wang XM, Zheng JZ et al. (2009) The myocardial protective effects of puerarin on STZ-induced diabetic rats. Fen Zi XI Bao Sheng Wu Xue Bao 42: 137-144. [Crossref]

10.  Xue J, Zhou N, Yang Y, Yun J, Yue Q et al. (2020) Puerarin-loaded ultrasound microbubble contrast agent used as sonodynamic therapy for diabetic cardiomyopathy rats. Colloids Surf B Biointerfaces 190: 110887. [Crossref]

11.  Wang X, Zhao L (2016) Calycosin ameliorates diabetes-induced cognitive impairments in rats by reducing oxidative stress via the PI3K/Akt/GSK-3β signaling pathway. Biochem Biophys Res Commun 473: 428-434. [Crossref]

12.  Zhang YY, Tan RZ, Zhang XQ, Yu Y, Yu C (2019) Calycosin Ameliorates Diabetes-Induced Renal Inflammation via the NF-κB Pathway In Vitro and In Vivo. Med Sci Monit 25: 1671-1678. [Crossref]

13.  Ru J, Li P, Wang J, Zhou W, Li B et al. (2014) TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 6: 13. [Crossref]

14.  Piero J, Ramírez Anguita JM, Saüch Pitarch J, Ronzano F, Centeno E et al. (2019) The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res 48: D845-D855. [Crossref]

15.  Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13: 2498-2504. [Crossref]

16.  Damian S, Gable AL, Nastou KC, Lyon D, Kirsch R et al. (2020) The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res D1: D605-D612. [Crossref]

17.  Pinzi L, Rastelli G (2019) Molecular Docking: Shifting Paradigms in Drug Discovery. Int J Mol Sci 20: 4331. [Crossref]

18.  Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31: 455-461. [Crossref]

19.  Seeliger D, de Groot BL (2010) Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 24: 417-422. [Crossref]

20.  Collier TA, Piggot TJ, Allison JR (2020) Molecular Dynamics Simulation of Proteins. Methods Mol Biol 2073: 311-327. [Crossref]

21.  Hess B, Kutzner C, David V, Lindahl E (2008) GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J Chem Theory Comput 4: 435-447. [Crossref]

22.  Cousins KR (2011) Computer review of ChemDraw Ultra 12.0. J Am Chem Soc 133: 8388. [Crossref]

23.  Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN et al. (2000) The Protein Data Bank. Nucleic Acids Res 28: 235-242. [Crossref]

24.  Song R, Zhao X, Cao R, Liang Y, Zhang DQ et al. (2021) Irisin improves insulin resistance by inhibiting autophagy through the PI3K/Akt pathway in H9c2 cells. Gene 769: 145209. [Crossref]

25.  El Sayed N, Mostafa YM, AboGresha NM, Ahmed A, Mahmoud IZ et al. (2021). Dapagliflozin attenuates diabetic cardiomyopathy through erythropoietin up-regulation of AKT/JAK/MAPK pathways in streptozotocin-induced diabetic rats. Chem Biol Interact 347: 109617. [Crossref]

26.  Zhao L, Wang Y, Liu J, Wang K, Guo X et al. (2016) Protective Effects of Genistein and Puerarin against Chronic Alcohol-Induced Liver Injury in Mice via Antioxidant, Anti-inflammatory, and Anti-apoptotic Mechanisms. J Agric Food Chem 64: 7291-7297. [Crossref]

27.  Zhang H, Zhang L, Zhang Q, Yang XC, Yu JY et al. (2011) Puerarin: a novel antagonist to inward rectifier potassium channel (I K1). Mol Cell Biochem 352: 117-123. [Crossref]

28.  Zhen YP, Zhao SB, Zhong MW, Wang XM, Zheng JZ et al. (2009) The myocardial protective effects of puerarin on STZ-induced diabetic rats. Fen Zi XI Bao Sheng Wu Xue Bao 42: 137-144. [Crossref]

29.  Zhang S, Qian W, Li S (2017) Effects of Huangqi Injection Combined with Puerarin Injection on KKAy Mice with Diabetic Cardiomyopathy on Endoplasmic Reticulum Stress. World Chinese Med.

30. Guo XC, Gao WH, Zhang DD, et al. (2022) The molecular mechanism of Radix astragali, Ginseng, Radix puerariae, and Mulberry leaf in the treatment of diabetic cardiomyopathy based on bioinformatics and network pharmacology. Researchsquare.