GİNKGO BİLOBA’NIN TEDAVİ POTANSİYELİNİN ORTAYA ÇIKARILMASI: PARKİNSON HASTALIĞINA YÖNELİK AĞ FARMAKOLOJİSİ YAKLAŞIMI

Yıl 2024, Cilt: 48 Sayı: 1, 97 - 108, 20.01.2024

Shiva Priya Mehak Tyagı Devadharshini Dhandayuthapanı Saravanan Jayaram

https://doi.org/10.33483/jfpau.1340094

Öz

Amaç: Mevcut çalışmanın amacı, ağ farmakolojisindeki yaklaşımları kullanarak Parkinson hastalığının patogenezinde yer alan ana terapötik hedeflerin rolünü modüle edebilen Ginkgo biloba'daki ana bitki kaynaklı bileşenleri belirlemektir.
Gereç ve Yöntem: Ginkgo biloba'daki bitki kaynaklı bileşenler ile bunların terapötik hedefleri ve Parkinson hastalığının hedefleri, çeşitli çevrimiçi veritabanları ve yazılımlar kullanılarak belirlendi. Tanımlanan bitki kaynaklı bileşenlerin, çeşitli farmakokinetik ve ilaç benzeri özellikleri değerlendirildi Uygun farmakokinetik ve ilaç benzeri özelliklere sahip bitki kaynaklı bileşenler ve daha iyi topolojik parametrelere sahip hedefler, moleküler yerleştirme çalışmasına ve MMGBSA analizine tabi tutuldu.
Sonuç ve Tartışma: Bu çalışma ile Ginkgo biloba'da 125 ana bitki kaynaklı bileşenin varlığı saptandı ve 125 bitki kaynaklı bileşenden 30’u uygun farmakokinetik ve ilaç benzeri özellik gösterdi. Seçilen bu bitki kaynaklı bileşenler için 468 terapötik hedef ve Parkinson için 2033 hastalık hedefi bulundu. Fito-hedefler ile hastalık hedefleri arasındaki ortak hedefler 44 hedef olarak bulundu. 44 ortak hedeften, Cytoscape 3.9.1 yazılımındaki derece merkeziliği ve arasındalık merkeziliği gibi topolojik parametrelere dayanılarak 5 üst protein CNR1, HPGDS, AR, RXRA ve HDAC1 tanımlandı. Yerleştirme çalışmaları ve MMGBSA analizi, beta-eudesmol'ün ilk 5 terapötik hedefle daha iyi etkileşime sahip olduğunu ortaya çıkardı.

Anahtar Kelimeler

Ağ farmakolojisi, cytoscape, Ginkgo biloba, parkinson hastalığı, schrödinger

Proje Numarası

NA

UNVEILING THE THERAPEUTIC POTENTIAL OF GINKGO BILOBA: A NETWORK PHARMACOLOGY APPROACH FOR PARKINSON’S DISEASE

Öz

Objective: The aim of the current study is to identify the major phytoconstituents in Ginkgo biloba that could modulate the role of major therapeutic targets involved in the pathogenesis of Parkinson’s disease using approaches in network pharmacology.
Material and Method: The phytoconstituents in Ginkgo biloba and their therapeutic targets and the targets of Parkinson’s disease were identified using various online databases and software. The identified phytoconstituents were subjected to evaluation of several pharmacokinetic properties and druglikeness study. The phytoconstituents with favourable pharmacokinetic and druglikeness properties and targets with better topological parameters were subjected to molecular docking study and MMGBSA analysis.
Result and Discussion: This study identified the presence of 125 major phytoconstituents in Ginkgo biloba and out of 125 phytoconstituents, 30 phytoconstituents passed the pharmacokinetics and druglikeness property. The therapeutic targets for these selected phytoconstituents were found to be 468 and the disease targets in PD were found to be 2033. The common targets between phyto-targets and disease targets were found to be 44 targets. Out of 44 common targets, 5 top proteins CNR1, HPGDS, AR, RXRA and HDAC1 were identified on the basis of the topological parameters such as degree centrality and betweenness centrality in the Cytoscape 3.9.1 software. The docking studies and MMGBSA analysis revealed that beta-eudesmol has better interaction with the top 5 therapeutic targets.

Anahtar Kelimeler

Ginkgo biloba, network pharmacology, parkinson’s disease, schrödinger, sitoscape

Destekleyen Kurum

JSS College of Pharmacy

Proje Numarası

NA

Teşekkür

DST-FIST

Kaynakça

• 1. Hopkins, A.L. (2008). Network pharmacology: The next paradigm in drug discovery. Natural Chemical Biology, 4(11), 682-690. [CrossRef]
• 2. Chandran, U., Mehendale, N., Patil, S., Chaguturu, R., Patwardhan, B. (2017). Network pharmacology ınnovative approaches in drug discovery: ethnopharmacology, systems biology and holistic targeting. Journal of Ayurvedha and Integrative Medicine, 10(2), 127-164. [CrossRef]
• 3. Padhy, I., Mahapatra, A., Banerjee, B., Sharma, T. (2023). Computational approaches in drug discovery. Phytochemicals Phytochemistry Computational Tools and Databases in Drug Discovery, 11, 57-88. [CrossRef]
• 4. Van Beek, T.A., Montoro, P. (2009). Chemical analysis and quality control of Ginkgo biloba leaves, extracts, and phytopharmaceuticals. Journal of Chromatography A, 1216(11), 2002-2032. [CrossRef]
• 5. Van Beek, T.A. (2002). Chemical analysis of Ginkgo biloba leaves and extracts. Journal of Chromatography A. 967(1), 21-55. [CrossRef]
• 6. Noor-E-Tabassum, Das, R., Lami, M.S., Chakraborty, A.J., Mitra, S., Tallei, T.E. (2022). Ginkgo biloba: A treasure of functional phytochemicals with multimedicinal applications. Evidence-Based Complementary and Alternative Medicine, 2022, 1-30. [CrossRef]
• 7. Yan, Y.C., Xu, Z.H., Wang, J., Yu, W.B. (2022). Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson’s disease. Frontiers in Pharmacology, 2022(13), 1-13. [CrossRef]
• 8. Váradi, C. (2020) Clinical features of Parkinson’s disease: The evolution of critical symptoms. Biology, 9(5), 1-13. [CrossRef]
• 9. Duan, H., Khan, G.J., Shang, L.J., Peng, H., Hu, W., chen., Zhang, J. (2021). Computational pharmacology and bioinformatics to explore the potential mechanism of Schisandra against atherosclerosis. Food and Chemical Toxicology, 150, 1-9. [CrossRef]
• 10. Pahal, S., Gupta, A., Choudhary, P., Chaudhary, A., Singh, S. (2022). Network pharmacological evaluation of Withania somnifera bioactive phytochemicals for identifying novel potential inhibitors against neurodegenerative disorder. Journal of Biomolecular Structure and Dynamics, 40, 10887-10898. [CrossRef]
• 11. Daina, A., Michielin, O., Zoete, V. (2019). SwissTargetPrediction: Updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Research, 47, 357-364. [CrossRef]
• 12. Gao, Q., Tian, D., Han, Z., Lin, J., Chang, Z., Zhang, D. (2021). Network pharmacology and molecular docking analysis on molecular targets and mechanisms of buyang huanwu decoction in the treatment of ischemic stroke. Evidence-Based Complementary and Alternative Medicine, 2021, 1-15. [CrossRef]
• 13. Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L., Ideker, T. (2011). Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics, 27, 431-432. [CrossRef]
• 14. Tang, Y., Li, M., Wang, J., Pan, Y., Wu, F.X. (2015). CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems, 127, 67-72. [CrossRef]
• 15. Hasan, M.M., Khan, Z., Chowdhury, M.S., Khan, M.A., Moni, M.A., Rahman, M.H. (2022). In silico molecular docking and ADME/T analysis of Quercetin compound with its evaluation of broad-spectrum therapeutic potential against particular diseases. Informatics in Medicine Unlocked, 29, 1-8. [CrossRef]
• 16. Fatriansyah, J.F., Rizqillah, R.K., Yandi, M.Y., Fadilah., Sahlan, M. (2022). Molecular docking and dynamics studies on propolis sulabiroin-A as a potential inhibitor of SARS-CoV-2. Journal of King Saud University Science, 34(1), 1-9. [CrossRef]
• 17. Bakal, R.L., Jawarkar, R.D., Manwar, J.V., Jaiswal, M.S., Ghosh, A., Gandhi, A. (2022). Identification of potent aldose reductase inhibitors as antidiabetic (Anti-hyperglycemic) agents using QSAR based virtual Screening, molecular Docking, MD simulation and MMGBSA approaches. Saudi Pharmaceutical Journal, 30, 693-710. [CrossRef]
• 18. Chandran, U., Mehendale, N., Patil, S., Chaguturu, R., Patwardhan, B.N. (2017). Innovative approaches in drug discovery: ethnopharmacology, systems biology and holistic targeting. Journal of Ayurvedha and Integrative Medicine, 10(2), 127-164. [CrossRef]
• 19. Giaever, G., Chu, A.M., Ni, L., Connelly, C., Riles, L., Véronneau, S. (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature, 418, 387-391. [CrossRef]
• 20. Winzeler, E.A., Shoemaker, D.D., Astromoff, A., Liang, H., Anderson, K., Andre, B. (1999). Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science, 285, 901-906. [CrossRef]
• 21. Zambrowicz, B.P., Sands, A.T. (2004). Modeling drug action in the mouse with knockouts and RNA interference. Drug Discovery Today: Targets, 3(5), 198–207. [CrossRef]
• 22. Deutschbauer, A.M., Jaramillo, D.F., Proctor, M., Kumm, J., Hillenmeyer, M.E., Davis, R.W. (2005). Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast. Genetics, 169(4), 1915-1925. [CrossRef]
• 23. Kang, X., Chen, J., Xu, Z., Li, H., Wang, B. (2007). Protective effects of Ginkgo biloba extract on paraquat-induced apoptosis of PC12 cells. Toxicology in Vitro, 21(6), 1003-1009. [CrossRef]
• 24. Su-Fen, Y., Zheng-Qin, Y., Qin, W., An-Sheng, S., Xie-Nan, H, Jing-Shan, S. (2001). Protective effect and mechanism of Ginkgo biloba leaf extracts for Parkinson disease induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Acta Pharmacologica Sinica, 22(12), 1089-1093.
• 25. Yu, D., Zhang, P., Li, J., Liu, T., Zhang, Y., Wang, Q. (2021). Neuroprotective effects of Ginkgo biloba dropping pills in Parkinson’s disease. Journal of Pharmaceutical Analysis, 11(2), 220-231. [CrossRef]
• 26. Rojas, P., Montes, S., Serrano-García, N., Rojas-Castañeda, J. (2009). Effect of EGb761 supplementation on the content of copper in mouse brain in an animal model of Parkinson’s disease. Nutrition, 25(4), 482-485. [CrossRef]
• 27. Rojas, P., Ruiz-Sánchez, E., Rojas, C., Ögren, S.O. (2012). Ginkgo biloba extract (EGb 761) modulates the expression of dopamine-related genes in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced Parkinsonism in mice. Neuroscience, 223, 246-257. [CrossRef]
• 28. Kuang, S., Yang, L., Rao, Z., Zhong, Z., Li, J., Zhong, H. (2018) Effects of Ginkgo Biloba Extract on A53T α-Synuclein Transgenic Mouse Models of Parkinson’s Disease. Canadian Journal of Neurological Sciences, 45(2), 182-187. [CrossRef]
• 29. Siddique, Y.H., Mujtaba, S.F., Jyoti, S., Naz, F. (2013). GC-MS analysis of Eucalyptus citriodora leaf extract and its role on the dietary supplementation in transgenic Drosophila model of Parkinson’s disease. Food and Chemical Toxicology, 55, 29-35. [CrossRef]
• 30. Murayama, C., Wang, C.C., Michihara, S., Norimoto, H. (2014). Pharmacological effects of “Jutsu” (Atractylodis rhizome and Atractylodis lanceae rhizome) on 1-(2,5-Dimethoxy-4-iodophenyl)-2-aminopropane (DOI)-Induced head twitch response in mice (I). Molecules, 19(9), 14979-14986. [CrossRef]
• 31. Zhang, R., Tang, B. (2020). Research advances on neurite outgrowth inhibitor B receptor. Journal of Cellular and Molecular Medicine, 24(14), 7697-7705. [CrossRef]
• 32. Dhillon, K., Aizel, K., Broomhall, T. J., Secret, E., Goodman, T., Rotherham, M., Gates, M. A. (2022). Directional control of neurite outgrowth: emerging technologies for Parkinson's disease using magnetic nanoparticles and magnetic field gradients. Journal of the Royal Society Interface, 19(196), 20220576. [CrossRef]
• 33. Obara, Y., Aoki, T., Kusano, M., Ohizumi Y. (2002). Eudesmol ınduces neurite outgrowth in rat pheochromocytoma cells accompanied by an activation of mitogen-activated protein kinase. The Journal of Pharmacology and Experimental Therapeutics, 301(3), 803-811. [CrossRef]