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A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson’s Disease

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Abstract

Parkinson’s disease (PD) is another major neurodegenerative disorder following Alzheimer’s disease, which not only seriously reduces the survival in patients, affecting patient’s quality of life, but also imposes a tremendous burden on families and even the whole society. It is urgent to find out effective drugs without side effects. The present study applied a creative approach called network pharmacology to explore the active compounds and therapeutic targets of Shaoyao-Gancao Decoction (SYGCD) for treating PD. We identified a total of 48 active compounds mediating 30 PD-related targets to exert synergism, and the same target can be enriched in multiple signal pathways and biological processes, expounding that the decoction can exert synergistic effect on PD by multi-targets and multi-pathways. Furthermore, the molecular docking analysis showed that active compounds and targets can be well combined. These results highlighted the molecular mechanisms underlying the efficiency of SYGCD for PD treatment at a systematic level, investigating thoroughly the innovative therapeutic tactics for PD in traditional Chinese medicine.

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References

  1. Gokcal E, Gur VE, Selvitop R, Babacan Yildiz G, Asil T (2017) Motor and non-motor symptoms in parkinson’s disease: effects on quality of life. Noro Psikiyatri Arsivi 54(2):143–148. https://doi.org/10.5152/npa.2016.12758

    Article  PubMed  Google Scholar 

  2. Chinese Medical Association Neurology Branch Parkinson’s Disease and Movement Disorders Group (2014) Chinese guidelines for the treatment of Parkinson’s disease (3rd Edition). Chin J Neurol 43(6):428–433

    Google Scholar 

  3. Ma CL, Su L, Xie JJ, Long JX, Wu P, Gu L (2014) The prevalence and incidence of Parkinson’s disease in China: a systematic review and meta-analysis. J Neural Trans 121(2):123–133. https://doi.org/10.1007/s00702-013-1092-z

    Article  Google Scholar 

  4. Sun ZR, Yang WM (2016) Neurology. People’s Health Publishing House, Beijing

    Google Scholar 

  5. Dorsey ER, Constantinescu R, Thompson JP, Biglan KM, Holloway RG, Kieburtz K, Marshall FJ, Ravina BM, Schifitto G, Siderowf A, Tanner CM (2006) Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology 68(5):384–386. https://doi.org/10.1212/01.wnl.0000247740.47667.03

    Article  PubMed  Google Scholar 

  6. Obeso JA, Olanow CW, Nutt JG (2000) Levodopa motor complications in Parkinson’s disease. Trends Neurosci 23(10 Suppl):S2–S7. https://doi.org/10.1016/S1471-1931(00)00031-8

    Article  CAS  PubMed  Google Scholar 

  7. Jenner P (2015). Treatment of the later stages of Parkinson’s disease - pharmacological approaches now and in the future. Transl Neurodegener. Feb 12; 4:3. https://doi.org/10.1186/2047-9158-4-3

  8. Giugni JC, Okun MS (2014) Treatment of advanced Parkinson’s disease. Curr Opin Neutrol 27(4):450–460. https://doi.org/10.1097/WCO.0000000000000118

    Article  CAS  Google Scholar 

  9. Fernandez HH (2015) 2015 Update on Parkinson disease. Cleve Clin J Med. 82(9):563–568. https://doi.org/10.3949/ccjm.82gr.15004

    Article  PubMed  Google Scholar 

  10. Yang H (2008) Evidence-based medical evaluation of 112 prescriptions of Shang Han Lun in modern clinical research. Beijing University of Traditional Chinese Medicine, Beijing

    Google Scholar 

  11. Nam KN, Yae CG, Hong J, Cho DH, Lee JH, Lee EH (2013) Paeoniflorin, a monoterpene glycoside, attenuates lipopolysaccharide-induced neuronal injury and brain microglial inflammatory response. Biotechnol Lett 35(8):1183–1189. https://doi.org/10.1007/s10529-013-1192-8

    Article  CAS  PubMed  Google Scholar 

  12. Hou YY, Yang Y, Yao Y, Bai Y (2010) Neuroprotection of glycyrrhizin against ischemic vascular dementia in vivo and glutamate-induced damage in vitro. Chin Herb Med 2(2):125–131. https://doi.org/10.3969/j.issn.1674-6384.2010.02.005

    Article  CAS  Google Scholar 

  13. Zhan C, Yang J, Zhan L, Zhang J, Zhang L (2005) Protective effects of isoliquiritigenin against cerebral ischemia-reperfusion injury in mice. J Wuhan Univ Med Sci 26(3):398–401. https://doi.org/10.14188/j.1671-8852.2005.03.035

    Article  CAS  Google Scholar 

  14. Liu RT, Bian GX, Zou LB, Huang XW, Lv QJ (2008) Neuroprotective effects of liquiritin and its inhibitory actions on cholinesterase activity. Chin J New Drugs 17(7):574–577. https://doi.org/10.3321/j.issn:1003-3734.2008.07.009

    Article  CAS  Google Scholar 

  15. Luo SH, Zhou DK (2002) 68 Cases of infant colic treated with modified SYGCD. ZHONGGUO ZHONGYI JIZHENG 11(4):309

    Google Scholar 

  16. Giuliano AR, Nyitray AG, Kreimer AR, Pierce Campbell CM, Goodman MT, Sudenga SL, Monsonego J, Franceschi S (2015) EUROGIN 2014 roadmap: differences in human papillomavirus infection natural history, transmission and human papil-lomavirus-related cancer incidence by gender and anatomic site of infection. Int J Cancer 136(12):2752–2760. https://doi.org/10.1002/ijc.29082

    Article  CAS  PubMed  Google Scholar 

  17. He F, Ru CH, Shen XQ (2017) Effects of Shaoyao Gancao decoction on the Th17 and Its cytokine IL-17 in rats with asthma. J Zhejiang Univ TCM 2(41):112–116. https://doi.org/10.16466/j.issn1005-5509.2017.02.004

    Article  Google Scholar 

  18. Hopkins AL (2007) Network pharmacology. Nat Biotechnol 25(10):1110

    Article  CAS  PubMed  Google Scholar 

  19. Tao W, Xu X, Wang X, Li B, Wang Y (2013) Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J Ethnopharmacol 145(1):1–10. https://doi.org/10.1016/j.jep.2012.09.051

    Article  CAS  PubMed  Google Scholar 

  20. Heng X, Zhu BJJ, Sun LM, Zhang QC (2018) Network pharmacology-based study on mechanisms of Huanglian Jiedu Decoction impact on macrophage inflammation response. Acta Pharm Sin 53(9):1449–14457. https://doi.org/10.16438/j.0513-4870.2018-0276

    Article  Google Scholar 

  21. Ru J, Li P, Wang J, Zhou W, Li B, Huang C, Li P, Guo Z, Tao W, Yang Y, Xu X, Li Y, Wang Y, Yang L (2014) TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 6:1498–1504. https://doi.org/10.1186/1758-2946-6-13

    Article  CAS  Google Scholar 

  22. Xu X, Zhang W, Huang C, Li Y, Yu H, Wang Y, Duan J, Ling Y (2012) A novel chemometric method for the prediction of human oral bioavailability. Int J Mol Sci 13(6):6964–6982. https://doi.org/10.3390/ijms13066964

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. van der Graaf PH, Benson N (2011) Systems pharmacology: bridging systems biology and pharmacokinetics-pharmacodynamics (PKPD) in drug discovery and development. Pharm Res 28(7):1460–1464. https://doi.org/10.1007/s11095-011-0467-9

    Article  CAS  PubMed  Google Scholar 

  24. Ma C, Wang L, Xie XQ (2011) GPU accelerated chemical similarity calculation for compound library comparison. J Chem Inf Model 51(7):1521–1527. https://doi.org/10.1021/ci1004948

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yu H, Chen J, Xu X, Li Y, Zhao H, Fang Y, Li X, Zhou W, Wang W, Wang Y (2012) A systematic prediction of multiple drug-target interactions from chemical, genomic, and pharmacological data. PLoS ONE 7(5):e37608. https://doi.org/10.1371/journal.pone.0037608

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Becker KG, Barnes KC, Bright TJ, Wang SA (2004) The genetic association database. Nat Genet 36:431–432. https://doi.org/10.1038/ng0504-431

    Article  CAS  PubMed  Google Scholar 

  27. Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ (2018) Accessing an expanded exposure science module at the comparative Toxicogenomics database. Environ Health Perspect 126(1):014501. https://doi.org/10.1289/EHP2873

    Article  PubMed  PubMed Central  Google Scholar 

  28. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, Gautam B, Hassanali M (2008) DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 36:D901–D906. https://doi.org/10.1093/nar/gkm958

    Article  CAS  PubMed  Google Scholar 

  29. Li YH, Yu CY, Li XX et al (2018) Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics. Nucleic Acids Res 46(D1):D1121–D1127. https://doi.org/10.1093/nar/gkx1076

    Article  CAS  PubMed  Google Scholar 

  30. Whirl-Carrillo M, Mcdonagh EM, Hebert JM, Gong L, Sangkuhl K, Thorn CF, Altman RB, Klein TE (2012) Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther 92(4):414–417. https://doi.org/10.1038/clpt.2012.96

    Article  CAS  PubMed  Google Scholar 

  31. Szklarczyk D, Morris JH, Cook H et al (2017) The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 45(Database issue):D362–D368. https://doi.org/10.1093/nar/gkw937

    Article  CAS  PubMed  Google Scholar 

  32. Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatic 27(3):431–432. https://doi.org/10.1093/bioinformatics/btq675

    Article  CAS  Google Scholar 

  33. Tang Y, Li M, Wang J, Pan Y, Wu FX (2015) CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems 127:67–72. https://doi.org/10.1016/j.biosystems.2014.11.005

    Article  CAS  PubMed  Google Scholar 

  34. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, Fridman WH, Pages F, Trajanoski Z, Galon J (2009) ClueGO: a cytoscape plug-into decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25:1091–1093. https://doi.org/10.1093/bioinformatics/btp101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Bindea G, Galon J, Mlecnik B (2013) CluePedia cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics 29(5):661–663. https://doi.org/10.1093/bioinformatics/btt019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Jiao X, Sherman BT, da Huang W, Stephens R, Baseler MW, Lane HC, Lempicki RA (2012) DAVID-WS: a stateful web service to facilitate gene/protein list analysis. Bioinformatics 28(13):1805–1806. https://doi.org/10.1093/bioinformatics/bts251

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Li JZ, Tang XN, Li TT, Liu LJ, Yu SY, Zhou GY, Shao QR, Sun HP, Wu C, Yang Y (2016) Paeoniflorin inhibits doxorubicin-induced cardiomyocyte apoptosis by downregulating microRNA-1 expression. Exp Ther Med 11(6):2407–2412. https://doi.org/10.3892/etm.2016.3182

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Yang N, Cui H, Han F, Zhang L, Huang T, Zhou Y, Zhou J (2016) Paeoniflorin inhibits human pancreatic cancer cell apoptosis via suppression of MMP-9 and ERK signaling. Oncol Lett 12(2):1471–1476. https://doi.org/10.3892/ol.2016.4761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhang Y, Wang L, Wu Y, Wang N, Wang SM, Zhang B, Shi CG, Zhang SC (2016) Paeoniflorin attenuates hippocampal damage in a rat model of vascular dementia. Exp Ther Med 12(6):3729–3734. https://doi.org/10.3892/etm.2016.3849

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Zhang LG, Wang LJ, Shen QQ (2015) Paeoniflorin improves regional cerebral blood flow and suppresses inflammatory factor in the hippocampus of rats with vascular dementia. Chin J Integr Med. https://doi.org/10.1007/s11655-015-2124-3

    Article  PubMed  Google Scholar 

  41. Zhang X, Liang MH (2015) Formononeti-induced apoptosis in bladder cancer cells and its mechanism. Chin J Public Health 31(3):314–317. https://doi.org/10.11847/zgggws2015-31-03-18

    Article  CAS  Google Scholar 

  42. Vegeto E, Bonincontro C, Pollio G, Sala A, Viappiani S, Nardi F, Brusadelli A, Viviani B, Ciana P, Maggi A (2001) Estrogen prevents the lipopolysaccharide-induced inflammatory response in microglia. J Neurosci 21(6):1809–1818. https://doi.org/10.1523/jneurosci.21-06-01809.2001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Deroo BJ, Korach KS (2006) Estrogen receptors and human disease. J Clin Invest 116:561–570. https://doi.org/10.1172/jci27987

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Teismann P, Ferger B (2001) Inhibition of the cyclooxygenase isoenzymes COX-1 and COX-2 provide neuroprotection in the MPTP-mouse model of Parkinson’s disease. Synapse 39(2):167–174. https://doi.org/10.1002/1098-2396(200102)39:2<167::AID-SYN8>3.0.CO;2-U

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the Natural Science Foundation of Guangdong Province Grant of China (No. 2014A030313585) and the Guangdong Province innovative strong school project—“Guangdong University cloud computing based precision medicine big data engineering technology research center” of Guangdong Pharmaceutical University, China. Thanks to the NCCBB 2019 conference for recommending this paper.

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Authors and Affiliations

  1. Guangdong Pharmaceutical University, Guangzhou, Guangdong, China

    Liting Li, Mimi Liu & Yongming Cai

  2. Guangdong Provincial TCM Precision Medicine Big Data Engineering Technology Research Center, Guangzhou, Guangdong, China

    Yongming Cai

  3. Guangdong University College of Precision Medicine Big Data Engineering Research Center Based on Cloud Computing, Guangzhou, Guangdong, China

    Yongming Cai

  4. Guangdong Huangcun Sports Training Center (Rehabilitation Center), Guangzhou, Guangdong, China

    Haiyan Qiu

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  1. Liting Li
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Correspondence to Yongming Cai.

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Li, L., Qiu, H., Liu, M. et al. A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson’s Disease. Interdiscip Sci Comput Life Sci 12, 131–144 (2020). https://doi.org/10.1007/s12539-020-00359-7

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