Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

Identification of the Active Constituents and Significant Pathways of Guizhi-Shaoyao-Zhimu Decoction for the Treatment of Diabetes Mellitus Based on Molecular Docking and Network Pharmacology

Author(s): Qing Zhang, Ruolan Li, Wei Peng, Mengmeng Zhang, Jia Liu, Shujun Wei, Jiaolong Wang, Chunjie Wu, Yongxiang Gao* and Xufeng Pu*

Volume 22, Issue 9, 2019

Page: [584 - 598] Pages: 15

DOI: 10.2174/1386207322666191022101613

Price: $65

Abstract

Aim and Objective: This study was designed to explore the active compounds and significant pathways of Guizhi-Shaoyao-Zhimu decoction (GSZD) for treating diabetes mellitus using molecular docking combined with network pharmacology.

Materials and Methods: Chemical constituents of GSZD and diabetes-related target proteins were collected from various databases. Then, compounds were filtered by Lipinski’s and Veber’s rules with Discovery studio software. The “Libdock” module was used to carry out molecular docking, and LibDockScores, default cutoff values for hydrogen bonds, and van der Waals interactions were recorded. LibDockScore of the target protein and its prototype ligand was considered as the threshold, and compounds with higher LibDockScores than the threshold were regarded as the active constituents of GSZD. Cytoscape software was used to construct the herb-active molecule-target interaction network of GSZD. ClueGO and CluePedia were applied to enrich the analysis of the biological functions and pathways of GSZD.

Results: A total of 275 potential active compounds with 57 possible pathways in GSZD were identified by molecular docking combined with network pharmacology. TEN, INSR, PRKAA2, and GSK3B are the four most important target proteins. Gancaonin E, 3'-(γ,γ-dimethylallyl)-kievitone, aurantiamide, curcumin and 14-O-cinnamoylneoline, could interact with more than 14 of the selected target proteins. Besides, 57 potential pathways of GSZD were identified, such as insulin signaling pathway, metabolites and energy regulation, glucose metabolic process regulation, and positive regulation of carbohydrate metabolic process, etc.

Conclusion: These results showed that molecular docking combined with network pharmacology is a feasible strategy for exploring bioactive compounds and mechanisms of Chinese medicines, and GSZD can be used to effectively treat diabetes through multi-components and multi-targets & pathways.

Keywords: Guizhi-Shaoyao-Zhimu decoction, diabetes mellitus, treatment, molecular pathways, network pharmacology, molecular docking.

[1]
Sun, R.; Deng, X.; Zhang, D.; Xie, F.; Wang, D.; Wang, J.; Tavallaie, M.S.; Jiang, F.; Fu, L. Anti-diabetic potential of Pueraria lobata root extract through promoting insulin signaling by PTP1B inhibition. Bioorg. Chem., 2019, 87, 12-15.
[http://dx.doi.org/10.1016/j.bioorg.2019.02.046] [PMID: 30852232]
[2]
Velmurugan, G.; Ramprasath, T.; Gilles, M.; Swaminathan, K.; Ramasamy, S. Gut microbiota, endocrine-disrupting chemicals, and the diabetes epidemic. Trends Endocrinol. Metab., 2017, 28(8), 612-625.
[http://dx.doi.org/10.1016/j.tem.2017.05.001] [PMID: 28571659]
[3]
Melmed, S.; Polonsky, K.S.; Larsen, P.R.; Kronenberg, H.M. Williams Textbook of Endocrinology, 12th ed; Elsevier/Saunders: Philadelphia, 2011, pp. 1371-1435.
[4]
Grunberger, G. Should side effects influence the selection of antidiabetic therapies in type 2 diabetes? Curr. Diab. Rep., 2017, 17(4), 21.
[http://dx.doi.org/10.1007/s11892-017-0853-8] [PMID: 28293908]
[5]
Harsch, I.A.; Kaestner, R.H.; Konturek, P.C. Hypoglycemic side effects of sulfonylureas and repaglinide in ageing patients - knowledge and self-management. J. Physiol. Pharmacol., 2018, 69
[http://dx.doi.org/10.26402/jpp.2018.4.15] [PMID: 30552308]
[6]
Newman, D.J.; Cragg, G.M. Natural products as sources of new drugs from 1981 to 2014. J. Nat. Prod., 2016, 79(3), 629-661.
[http://dx.doi.org/10.1021/acs.jnatprod.5b01055] [PMID: 26852623]
[7]
Zhang, Q.; Peng, W.; Wei, S.; Wei, D.; Li, R.; Liu, J.; Peng, L.; Yang, S.; Gao, Y.; Wu, C.; Pu, X. Guizhi-Shaoyao-Zhimu decoction possesses anti-arthritic effects on type II collagen-induced arthritis in rats via suppression of inflammatory reactions, inhibition of invasion & migration and induction of apoptosis in synovial fibroblasts. Biomed. Pharmacother., 2019, 118109367
[8]
Wang, Y.R. Analysis of abnormal effect of Guizhi Shaoyao Zhimu Tang in improving the diabetic peripheral neuropathy sensation. Diabetes New World., 2017, 24, 166-167.
[9]
Zhang, C.X. Treatments of 20 cases of diabetic foot with modified Guizhi-Shaoyao-Zhimu docoction. Chiang-Hsi Chung I Yao, 2010, 327, 63.
[10]
Zhao, F.; Guo, L.; Yang, Y.; Shi, L.; Xu, L.; Yin, L. A network pharmacology approach to determine active ingredients and rationality of herb combinations of Modified-Simiaowan for treatment of gout. J. Ethnopharmacol., 2015, 168, 1-16.
[http://dx.doi.org/10.1016/j.jep.2015.03.035] [PMID: 25824593]
[11]
Pang, X.C.; Kang, D.; Fang, J.S.; Zhao, Y.; Xu, L.J.; Lian, W.W.; Liu, A.L.; Du, G.H. Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer’s disease. Chin. J. Nat. Med., 2018, 16(1), 53-62.
[http://dx.doi.org/10.1016/S1875-5364(18)30029-3] [PMID: 29425590]
[12]
Boezio, B.; Audouze, K.; Ducrot, P.; Taboureau, O. Network-based approaches in pharmacology. Mol. Inform., 2017, 36(10)
[http://dx.doi.org/10.1002/minf.201700048] [PMID: 28692140]
[13]
Yuan, H.; Ma, Q.; Cui, H.; Liu, G.; Zhao, X.; Li, W.; Piao, G. How can synergism of traditional medicines benefit from network pharmacology? Molecules, 2017, 22(7), 1135.
[http://dx.doi.org/10.3390/molecules22071135] [PMID: 28686181]
[14]
Hopkins, A.L. Network pharmacology: The next paradigm in drug discovery. Nat. Chem. Biol., 2008, 4(11), 682-690.
[http://dx.doi.org/10.1038/nchembio.118] [PMID: 18936753]
[15]
Cui, Y.; Li, C.; Zeng, C.; Li, J.; Zhu, Z.; Chen, W.; Huang, A.; Qi, X. Tongmai Yangxin pills anti-oxidative stress alleviates cisplatin-induced cardiotoxicity: Network pharmacology analysis and experimental evidence. Biomed. Pharmacother., 2018, 108, 1081-1089.
[http://dx.doi.org/10.1016/j.biopha.2018.09.095] [PMID: 30372808]
[16]
Shan, J.J.; Yang, R.R.; Zhang, X.Z.; Shen, C.S.; Shen, C.S.; Ji, J.J.; Xie, T.; Xu, J.Y.; Di, L.Q. Network pharmacological study of antitussive and expectorant effective of Jiegeng Decotion. Chin. Tradit. Herbal Drugs, 2018, 49, 3501-3508.
[17]
Zhang, J.; Liang, R.; Wang, L.; Yang, B. Effects and mechanisms of Danshen-Shanzha herb-pair for atherosclerosis treatment using network pharmacology and experimental pharmacology. J. Ethnopharmacol., 2019, 229, 104-114.
[http://dx.doi.org/10.1016/j.jep.2018.10.004] [PMID: 30312741]
[18]
Li, C.; Zhang, W.Y.; Yu, Y.; Cheng, C.S.; Han, J.Y.; Yao, X.S.; Zhou, H. Discovery of the mechanisms and major bioactive compounds responsible for the protective effects of Gualou Xiebai Decoction on coronary heart disease by network pharmacology analysis. Phytomedicine, 2019, 56, 261-268.
[http://dx.doi.org/10.1016/j.phymed.2018.11.010] [PMID: 30668346]
[19]
Deb, P.K. Recent updates in the computer aided drug design strategies for the discovery of agonists and antagonists of adenosine receptors. Curr. Pharm. Des., 2019, 25(7), 747-749.
[http://dx.doi.org/10.2174/1381612825999190515120510] [PMID: 31232230]
[20]
Huang, S.; Ren, Y.; Peng, X.; Qian, P.; Meng, L. Computer-aid drug design, synthesis, and anticoagulant activity evaluation of novel dabigatran derivatives as thrombin inhibitors. Eur. J. Pharm. Sci., 2019, 137104965
[http://dx.doi.org/10.1016/j.ejps.2019.104965] [PMID: 31247296]
[21]
Powers, C.N.; Setzer, W.N. A molecular docking study of phytochemical estrogen mimics from dietary herbal supplements. In Silico Pharmacol., 2015, 3, 4.
[http://dx.doi.org/10.1186/s40203-015-0008-z] [PMID: 25878948]
[22]
Lohning, A.E.; Levonis, S.M.; Williams-Noonan, B.; Schweiker, S.S. A practical guide to molecular docking and homology modelling for medicinal chemists. Curr. Top. Med. Chem., 2017, 17(18), 2023-2040.
[http://dx.doi.org/10.2174/1568026617666170130110827] [PMID: 28137238]
[23]
Peng, W.; Shen, H.; Lin, B.; Han, P.; Li, C.H.; Zhang, Q.Y.; Ye, B.Z.; Rahman, K.; Xin, H.L.; Qin, L.P.; Han, T. Docking study and antiosteoporosis effects of a dibenzylbutane lignan isolated from Litsea cubeba targeting Cathepsin K and MEK1. Med. Chem. Res., 2018, 27, 2062-2070.
[http://dx.doi.org/10.1007/s00044-018-2215-8]
[24]
Wang, J.L.; Peng, W.; Li, X.Y.; Fan, W.X.; Wei, D.N.; Wu, B.; Fan, L.H.; Wu, C.J.; Li, L. Towards to potential 2-cyano-pyrimidines cathepsin-K inhibitors: An in silico design and screening research based on comprehensive application of quantitative structureeactivity relationships, molecular docking and ADMET prediction. J. Mol. Struct., 2019, 1195, 914-928.
[http://dx.doi.org/10.1016/j.molstruc.2019.06.020]
[25]
Yang, X.; Liu, H.; Liu, J.; Li, F.; Li, X.; Shi, L.; Chen, J. Rational selection of the 3D structure of biomacromolecules for molecular docking studies on the mechanism of endocrine disruptor action. Chem. Res. Toxicol., 2016, 29(9), 1565-1570.
[http://dx.doi.org/10.1021/acs.chemrestox.6b00245] [PMID: 27556396]
[26]
Missiuro, P.V.; Liu, K.; Zou, L.; Ross, B.C.; Zhao, G.; Liu, J.S.; Ge, H. Information flow analysis of interactome networks. PLOS Comput. Biol., 2009, 5(4)e1000350
[http://dx.doi.org/10.1371/journal.pcbi.1000350] [PMID: 19503817]
[27]
Raman, K.; Damaraju, N.; Joshi, G.K. The organisational structure of protein networks: Revisiting the centrality-lethality hypothesis. Syst. Synth. Biol., 2014, 8(1), 73-81.
[http://dx.doi.org/10.1007/s11693-013-9123-5] [PMID: 24592293]
[28]
Zhang, Y.; Bai, M.; Zhang, B.; Liu, C.; Guo, Q.; Sun, Y.; Wang, D.; Wang, C.; Jiang, Y.; Lin, N.; Li, S. Uncovering pharmacological mechanisms of Wu-tou decoction acting on rheumatoid arthritis through systems approaches: drug-target prediction, network analysis and experimental validation. Sci. Rep., 2015, 5, 9463.
[http://dx.doi.org/10.1038/srep09463] [PMID: 25820382]
[29]
Dong, D.; Xu, Z.; Zhong, W.; Peng, S. Parallelization of molecular docking: A review. Curr. Top. Med. Chem., 2018, 18(12), 1015-1028.
[http://dx.doi.org/10.2174/1568026618666180821145215] [PMID: 30129415]
[30]
Peng, W.; Liu, Y.; Zhao, C.; Huang, X.; Wu, N.; Hu, M.; Xie, D.; Wu, C.J. In silico assessment of drug-like properties of alkaloids from fruits of Areca catechu L. Trop. J. Pharm. Res., 2015, 14, 635-639.
[http://dx.doi.org/10.4314/tjpr.v14i4.11]
[31]
Duchowicz, P.R.; Talevi, A.; Bellera, C.; Bruno-Blanch, L.E.; Castro, E.A. Application of descriptors based on Lipinski’s rules in the QSPR study of aqueous solubilities. Bioorg. Med. Chem., 2007, 15(11), 3711-3719.
[http://dx.doi.org/10.1016/j.bmc.2007.03.044] [PMID: 17418580]
[32]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev., 2001, 46(1-3), 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0] [PMID: 11259830]
[33]
Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, J.H.; Bork, P.; Jensen, L.J.; Mering, C.V. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res., 2019, 47(D1), D607-D613.
[http://dx.doi.org/10.1093/nar/gky1131] [PMID: 30476243]
[34]
Pagadala, N.S.; Syed, K.; Tuszynski, J. Software for molecular docking: a review. Biophys. Rev., 2017, 9(2), 91-102.
[http://dx.doi.org/10.1007/s12551-016-0247-1] [PMID: 28510083]
[35]
Huang, J.; Cheung, F.; Tan, H.Y.; Hong, M.; Wang, N.; Yang, J.; Feng, Y.; Zheng, Q. Identification of the active compounds and significant pathways of yinchenhao decoction based on network pharmacology. Mol. Med. Rep., 2017, 16(4), 4583-4592.
[http://dx.doi.org/10.3892/mmr.2017.7149] [PMID: 28791364]
[36]
Chen, L.; Cao, Y.; Zhang, H.; Lv, D.; Zhao, Y.; Liu, Y.; Ye, G.; Chai, Y. Network pharmacology-based strategy for predicting active ingredients and potential targets of Yangxinshi tablet for treating heart failure. J. Ethnopharmacol., 2018, 219, 359-368.
[http://dx.doi.org/10.1016/j.jep.2017.12.011] [PMID: 29366769]

Rights & Permissions Print Export Cite as
© 2024 Bentham Science Publishers | Privacy Policy