IN SILICO TRIAL APPROACHES BETWEEN PHYTOCHEMICAL COMPOSITION OF VERBENA OFFICINALIS AND LIVER CANCER TARGETS

Yıl 2024, Cilt: 48 Sayı: 3, 975 - 992, 10.09.2024

Hatice Akkaya , Aydın Özmaldar

https://doi.org/10.33483/jfpau.1417289

Öz

Objective: The abundance of bioactive metabolites in Verbena officinalis explains the biological benefits and folkloric use of the plant. Liver cancer is an extremely heterogeneous malignant disease compared to other defined tumors. To explore the potential therapeutic value of bioactive metabolites in Verbena officinalis, this study aimed to filter secondary metabolites, conduct ADME-Tox assessments, perform drug similarity tests, and analyze with molecular dynamic simulations. The objective was to evaluate how potential drug candidates derived from Verbena officinalis behave in biological systems and assess their potential toxicity risks.
Material and Method: Ligands selected from the ADME assay were utilized in in silico molecular docking studies against Glucose-6-phosphate dehydrogenase enzyme in the oxidative part of the pentose phosphate pathway, which is crucial for liver diseases. These studies were conducted using Autodock Vina embedded in Chimera 1.16. Molecular dynamics simulations were performed with the AMBER16.
Result and Discussion: When the ADME test results were evaluated, 88 secondary metabolites were identified as ligands. Among all the ligands evaluated against Glucose-6-phosphate dehydrogenase enzyme, which is the key enzyme of the pentose phosphate pathway, quercetin flavonoid was determined to be the most active ligand with a docking score of -8.1 kcal/mol and binding energy of -118.51 kcal/mol. A molecular dynamics simulation performed for 300 nanoseconds confirmed that quercetin can remain stable in its microenvironment. The activity of this metabolite is worthy of further testing in vitro and in vivo as it may highlight a therapeutic modality within the pentose phosphate pathway.

Anahtar Kelimeler

In silico, liver cancer, pentose phosphate pathway, toxicitiy, Verbena officinalis

VERBENA OFFICINALIS'İN FİTOKİMYASAL BİLEŞİMİ İLE KARACİĞER KANSERİ HEDEFLERİ ARASINDAKİ İN SİLİKO DENEME YAKLAŞIMLARI

Öz

Amaç: Verbena officinalis bitkisinde bulunan biyoaktif metabolitlerin bolluğu, bitkinin biyolojik faydalarını ve halk arasındaki kullanımını açıklar. Karaciğer kanseri, diğer tanımlanmış tümörlere kıyasla son derece heterojen kötü huylu bir hastalıktır. Verbena officinalis'teki biyoaktif metabolitlerin potansiyel terapötik değerini keşfetmek için, bu çalışma ikincil metabolitleri filtrelemeyi, ADME-Tox değerlendirmeleri yapmayı, ilaç benzerlik testleri gerçekleştirmeyi ve moleküler dinamik simülasyonları ile analiz etmeyi amaçlamıştır. Hedef, Verbena officinalis'ten elde edilen potansiyel ilaç adaylarının biyolojik sistemlerde nasıl davrandığını değerlendirmek, potansiyel toksisite risklerini değerlendirmekti.
Gereç ve Yöntem: ADME testinden seçilen ligandlar, karaciğer hastalıkları için önemli olan pentoz fosfat yolunun oksidatif kısmındaki Glukoz-6-fosfat dehidrogenaz enzimi için in siliko moleküler bağlanma çalışmalarında kullanıldı. Bu çalışmalar Chimera 1.16'ya gömülü Autodock Vina kullanılarak gerçekleştirildi. Moleküler dinamik simülasyonları AMBER16 programı ile gerçekleştirildi.
Sonuç ve Tartışma: ADME test sonuçları değerlendirildiğinde, 88 sekonder metabolit ligand olarak belirlendi. Pentoz fosfat yolunun anahtar enzimi olan Glukoz-6-fosfat dehidrogenaz enzimine karşı değerlendirilen tüm ligandlar arasında, kuersetin flavonoidi, -8.1 kcal/mol bağlanma skoru ve -118.51 kcal/mol bağlanma enerjisi ile en etkin ligand olarak belirlendi. 300 nanosaniye boyunca yapılan moleküler dinamik simülasyonu ise quercetinin bulunduğu mikroçevrede stabil olarak kalabildiğini doğruladı. Bu metabolitin aktivitesi, pentoz fosfat yolu içinde terapötik bir modaliteyi ortaya koyabileceği için in vitro ve in vivo testlerle daha ileri incelenmeye değerdir.

Anahtar Kelimeler

İn siliko, karaciğer kanseri, pentoz fosfat yolu, toksisite, Verbena officinalis

Kaynakça

• 1. Prieto-Martínez, F.D., López-López, E., Eurídice Juárez-Mercado, K., MedinaFranco, J.L. (2019). Computational drug design methods-current and future perspectives, in in silico drug design. Academic Press, p. 19-44. [CrossRef]
• 2. López-López, E., Bajorath, J., Medina-Franco, J.L. (2021). Informatics for chemistry, biology, and biomedical sciences. Journal of Chemical Infori Modeling, 61 (1), 26-35. [CrossRef]
• 3. Medina-Franco, J.L., Martinez-Mayorga, K., Fernández-de Gortari, E., Kirchmair, J., Bajorath, J. (2021). Rationality over fashion and hype in drug design. F1000Research, 10, Chem Inf Sci-397. [CrossRef]
• 4. Stuart, J. (2014). Herbal medicines. Fourth edition. Journal of the Medical Library Association: Journal of the Medical Library Association, 102(3), 222-223. [CrossRef]
• 5. Ghazanfar, S.A. (1994). Handbook of Arabian Medicinal Plants, CRC Press, Boca Raton, Florida, p. 176. [CrossRef]
• 6. Kubica, P., Szopa, A., Dominiak, J., Luczkiewicz, M., Ekiert, H. (2020). Verbena officinalis (Common Vervain)-A Review on the investigations of this medicinally important plant species. Planta Medica, 86(17). [CrossRef]
• 7. Rehecho, S., Hidalgo, O., de Cirano, M. G.I., Navarro, I., Astiasarán, I., Ansorena, D., Cavero, R.Y., Calvo, M.I. (2011). Chemical composition, mineral content and antioxidant activity of Verbena officinalis L. LWT-Food Science and Technology, 44 (4), 875-882. [CrossRef]
• 8. Liu, Z., Xu, Z., Zhou, H., Cao, G., Cong, X.D., Zhang, Y., Cai, B.C. (2012). Simultaneous determination of four bioactive compounds in Verbena officinalis L. by using high-performance liquid chromatography. Pharmacognosy Magazine, 8(30), 162-165. [CrossRef]
• 9. Van Wyk, B.E., Wink, M. (2017). Medicinal Plants of The World, Cabi, London, p.520.
• 10. Akour, A., Kasabri, V., Afifi, F.U., Bulatova, N. (2016). The use of medicinal herbs in gynecological and pregnancy-related disorders by Jordanian women: A review of folkloric practice vs. evidence-based pharmacology. Pharmaceutical Biology, 54(9), 1901-1918. [CrossRef]
• 11. Khan, A.W., Khan, A.U., Ahmed, T. (2016). Anticonvulsant, anxiolytic, and sedative activities of Verbena officinalis. Frontiers in Pharmacology, 7, 499. [CrossRef]
• 12. Lai, S.W., Yu, M.S., Yuen, W.H., Chang, R.C. (2006). Novel neuroprotective effects of the aqueous extracts from Verbena officinalis Linn. Neuropharmacology, 50(6), 641-650. [CrossRef]
• 13. Ashok Kumar, B.S., Lakshman, K., Velmurugan, C., Sridhar, S.M., Gopisetty, S. (2014). Antidepressant activity of methanolic extract of amaranthus spinosus. Basic and Clinical Neuroscience, 5(1), 11-17.
• 14. De Martino, L., D'Arena, G., Minervini, M.M., Deaglio, S., Fusco, B.M., Cascavilla, N., De Feo, V. (2009). Verbena officinalis essential oil and its component citral as apoptotic-inducing agent in chronic lymphocytic leukemia. International Journal of Immunopathology and Pharmacology, 22(4), 1097-1104. [CrossRef]
• 15. Speroni, E., Cervellati, R., Costa, S., Guerra, M.C., Utan, A., Govoni, P., Berger, A., Müller, A., Stuppner, H. (2007). Effects of differential extraction of Verbena officinalis on rat models of inflammation, cicatrization and gastric damage. Planta Medica, 73(3), 227-235. [CrossRef]
• 16. Calvo M.I. (2006). Anti-inflammatory and analgesic activity of the topical preparation of Verbena officinalis L. Journal of Ethnopharmacology, 107(3), 380-382. [CrossRef]
• 17. Casanova, E., García-Mina, J.M., Calvo, M.I. (2008). Antioxidant and antifungal activity of Verbena officinalis L. leaves. Plant Foods for Human Nutrition (Dordrecht, Netherlands), 63(3), 93-97. [CrossRef]
• 18. Li, Y. (2008). Chinese medicinal herbs for effectively treating cirrhosis, in liver ascites. CN101244158.
• 19. Zhang, S., Gu, H., Zhang, W., Li, X., Li, Y., Liu, B., Wang, M., Zhang, X. (2008). Chinese medicine composition for treating nephropathy. CN101313971i.
• 20. Hu, S. (2008). Chinese medicine for treating prostatitis and hyperplasia. CN101195011.
• 21. Yang, H.C., Wu, Y.H., Liu, H.Y., Stern, A., Chiu, D.T. (2016). What has passed is prolog: New cellular and physiological roles of G6PD. Free Radical Research, 50(10), 1047-1064. [CrossRef]
• 22. Patra, K.C., Hay, N. (2014). The pentose phosphate pathway and cancer. Trends in Biochemical Sciences, 39(8), 347-354. [CrossRef]
• 23. Liu, B., Fu, X., Du, Y., Feng, Z., Chen, R., Liu, X., Yu, F., Zhou, G., Ba, Y. (2023). Pan-cancer analysis of G6PD carcinogenesis in human tumors. Carcinogenesis, 44(6), 525-534. [CrossRef]
• 24. Yang, H.C., Stern, A., Chiu, D.T. (2021). G6PD: A hub for metabolic reprogramming and redox signaling in cancer. Biomedical Journal, 44(3), 285-292. [CrossRef]
• 25. Li, R., Ke, M., Qi, M., Han, Z., Cao, Y., Deng, Z., Qian, J., Yang, Y., Gu, C. (2022). G6PD promotes cell proliferation and dexamethasone resistance in multiple myeloma via increasing anti-oxidant production and activating Wnt/β-catenin pathway. Experimental Hematology & Oncology, 11(1), 77. [CrossRef]
• 26. Sun, L., Suo, C., Li, S.T., Zhang, H., Gao, P. (2018). Metabolic reprogramming for cancer cells and their microenvironment: Beyond the Warburg Effect. Biochimica et Biophysica Acta-Reviews on Cancer, 1870(1), 51-66. [CrossRef]
• 27. Li, R., Wang, W., Yang, Y., Gu, C. (2020). Exploring the role of glucose‑6‑phosphate dehydrogenase in cancer (Review). Oncology Reports, 44(6), 2325-2336. [CrossRef]
• 28. Butt, S.S., Badshah, Y., Shabbir, M., Rafiq, M. (2020). Molecular docking using chimera and autodock vina software for nonbioinformaticians. JMIR Bioinformatics and Biotechnology, 1(1), e14232. [CrossRef]
• 29. Setlur, A.S., Chandrashekar, K., Panhalkar, V., Sharma, S., Sarkar, M., Niranjan, V. (2023). In-silico-based toxicity investigation of natural repellent molecules against the human proteome: A safety profile design. Protocols.io, 83767. [CrossRef]
• 30. Chen, Y., Gan, Y., Yu, J., Ye, X., Yu, W. (2023). Key ingredients in Verbena officinalis and determination of their anti-atherosclerotic effect using a computer-aided drug design approach. Frontiers in Plant Science, 14, 1154266. [CrossRef]
• 31. Goddard, T.D., Huang, C.C, Ferrin, T.E. (2007). Visualizing density maps with UCSF Chimera. Journal of Structural Biology, 157(1), 281-287. [CrossRef]
• 32. Del Águila Conde, M., Febbraio, F. (2022). Risk assessment of honey bee stressors based on in silico analysis of molecular interactions. EFSA Journal- European Food Safety Authority, 20(Suppl 2), e200912. [CrossRef]
• 33. Chen, X., Li, H., Tian, L., Li, Q., Luo, J., Zhang, Y. (2020). Analysis of the physicochemical properties of acaricides based on Lipinski's Rule of five. Journal of Computational Biology: A Journal of Computational Molecular Cell Biology, 27(9), 1397-1406. [CrossRef]
• 34. Kalay, Ş., Akkaya, H. (2023). Molecular modelling of some ligands against acetylcholinesterase to treat Alzheimer’s Disease. Journal of Research Pharmacy, 27(6), 2199-2209. [CrossRef]
• 35. Maier, J.A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K.E., Simmerling, C. (2015). ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. Journal of Chemical Theory and Computation, 11(8), 3696-3713. [CrossRef]
• 36. Jorgensen, W.L., Chandrasekhar, J., Madura, J.D. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79, 926-935. [CrossRef]
• 37. Adasme, M.F., Linnemann, K.L., Bolz, S.N., Kaiser, F., Salentin, S., Haupt, V.J., Schroeder, M. (2021). PLIP 2021: Expanding the scope of the protein-ligand interaction profiler to DNA and RNA. Nucleic Acids Research, 49(W1), 530-534. [CrossRef]
• 38. Case, D.A., Betz, R.M., Cerutti, D.S., Cheatham, III, T.E., Darden, T.A., Duke, R.E., Giese, T.J., Gohlke, H., Goetz, A.W., Homeyer, N., Izadi, S., Janowski, P., Kaus, J., Kovalenko, A., Lee, T.S., LeGrand, S., Li, P., Lin, C., Luchko, T., Luo, R., Madej, B., Mermelstein, D., Merz, K.M., Monard, G., Nguyen, H., Nguyen, H.T., Omelyan, I., Onufriev, A., Roe, D.R., Roitberg, A., Sagui, C., Simmerling, C.L., Botello-Smith, W.M., Swails, J., Walker, R.C., Wang, J., Wolf, R.M., Wu, X., Xiao, L., Kollman, P.A. (2016). AMBER 2016, University of California, San Francisco.
• 39. Sumera, Anwer, F., Waseem, M., Fatima, A., Malik, N., Ali, A., Zahid, S. (2022). Molecular docking and molecular dynamics studies reveal secretory proteins as novel targets of temozolomide in glioblastoma multiforme. Molecules (Basel, Switzerland), 27(21), 7198. [CrossRef]
• 40. Ghosh, P., Bhakta, S., Bhattacharya, M., Sharma, A.R., Sharma, G., Lee, S.S., Chakraborty, C. (2021). A novel multi-epitopic peptide vaccine candidate against Helicobacter pylori: In-Silico identification, design, cloning and validation through molecular dynamics. International Journal of Peptide Research and Therapeutics, 27(2), 1149-1166. [CrossRef]
• 41. Shah, S.A.A., Qureshi, N.A., Qureshi, M.Z., Alhewairini, S.S., Saleem, A., Zeb, A. (2023). Characterization and bioactivities of M. arvensis, V. officinalis and P. glabrum: In-silico modeling of V. officinalis as a potential drug source. Saudi Journal of Biological Sciences, 30(6), 103646. [CrossRef]
• 42. Nisar, R., Ahmad, S., Khan, K.U., Sherif, A.E., Alasmari, F., Almuqati, A.F., Ovatlarnporn, C., Khan, M. A., Umair, M., Rao, H., Ghalloo, B.A., Khurshid, U., Dilshad, R., Nassar, K.S., Korma, S.A. (2022). Metabolic Profiling by GC-MS, in vitro biological potential, and ın silico molecular docking studies of Verbena officinalis. Molecules (Basel, Switzerland), 27(19), 6685. [CrossRef]
• 43. Jamshidzadeh, A., Rezaeian Mehrabadi, A. (2010). Protective effect of quercetin on oxidative stress in glucose-6-phosphate dehydrogenase-deficient erythrocytes in vitro. Iranian Journal of Pharmaceutical Research: IJPR, 9(2), 169-175. [CrossRef]
• 44. Anandan, S., Gowtham, H.G., Shivakumara, C.S., Thampy, A., Singh, S.B., Murali, M., Shivamallu, C., Pradeep, S., Shilpa, N., Shati, A.A., Alfaifi, M.Y., Elbehairi, S.E.I., Ortega-Castro, J., Frau, J., Flores-Holguín, N., Kollur, S.P., Glossman-Mitnik, D. (2022). Integrated approach for studying bioactive compounds from Cladosporium spp. against estrogen receptor alpha as breast cancer drug target. Scientific Reports, 12(1), 22446. [CrossRef]
• 45. Bissantz, C., Kuhn, B., Stahl, M. (2010). A medicinal chemist's guide to molecular interactions. Journal of Medicinal Chemistry, 53(14), 5061-5084. [CrossRef]
• 46. Hwang, S., Mruk, K., Rahighi, S., Raub, A.G., Chen, C.H., Dorn, L.E., Horikoshi, N., Wakatsuki, S., Chen, J.K., Mochly-Rosen, D. (2018). Correcting glucose-6-phosphate dehydrogenase deficiency with a small-molecule activator. Nature Communications, 9(1), 4045. [CrossRef]
• 47. Ge, Z., Xu, M., Ge, Y., Huang, G., Chen, D., Ye, X., Xiao, Y., Zhu, H., Yin, R., Shen, H., Ma, G., Qi, L., Wei, G., Li, D., Wei, S., Zhu, M., Ma, H., Shi, Z., Wang, X., Ge, X., Qian, X. (2023). Inhibiting G6PD by quercetin promotes degradation of EGFR T790M mutation. Cell Reports, 42(11), 113417. [CrossRef]
• 48. Knapp, B., Frantal, S., Cibena, M., Schreiner, W., Bauer, P. (2011). Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible? Journal of Computational Biology, 18(8), 997-1005. [CrossRef]
• 49. Montanari, F., Ecker, G.F. (2015). Prediction of drug-ABC-transporter interaction-Recent advances and future challenges. Advanced Drug Delivery Reviews, 86, 17-26. [CrossRef]
• 50. Poczta, A., Krzeczyński, P., Tobiasz, J., Rogalska, A., Gajek, A., Marczak, A. (2022). Synthesis and in vitro activity of novel melphalan analogs in hematological malignancy cells. International Journal of Molecular Sciences, 23(3), 1760. [CrossRef]
• 51. Hennessy, M., Spiers, J.P. (2007). A primer on the mechanics of P-glycoprotein the multidrug transporter. Pharmacological Research, 55(1), 1-15. [CrossRef]
• 52. Simanjuntak, K., Simanjuntak, J.E., Prasasty, V.D. (2017). Structure-based drug design of quercetin and its derivatives against HMGB1. Biomedical and Pharmacology Journal. 10 (4), 1973-1982. [CrossRef]
• 53. Daina, A., Michielin, O., Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7, 42717. [CrossRef]
• 54. Medoro, A., Jafar, T.H., Ali, S., Trung, T.T., Sorrenti, V., Intrieri, M., Scapagnini, G., Davinelli, S. (2023). In silico evaluation of geroprotective phytochemicals as potential sirtuin 1 interactors. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 161, 114425. [CrossRef]
• 55. David, S., Cunningham, R. (2019). Echinacea for the prevention and treatment of upper respiratory tract infections: A systematic review and meta-analysis. Complementary Therapies in Medicine, 44, 18-26. [CrossRef]
• 56. Saini, N., Bakshi, S., Sharma, S. (2018). In-silico approach for drug induced liver injury prediction: Recent advances. Toxicology Letters, 295, 288-295. [CrossRef]
• 57. Kelleci Çelik, F., Karaduman, G. (2023). Machine learning-based prediction of drug-induced hepatotoxicity: An OvA-QSTR approach. Journal of Chemical Information and Modeling, 63(15), 4602-4614. [CrossRef]
• 58. Sethi, G., Rath, P., Chauhan, A., Ranjan, A., Choudhary, R., Ramniwas, S., Sak, K., Aggarwal, D., Rani, I., Tuli, H.S. (2023). Apoptotic mechanisms of quercetin in liver cancer: Recent trends and advancements. Pharmaceutics, 15(2), 712. [CrossRef]
• 59. Bouayed, J., Bohn, T. (2010). Exogenous antioxidants-double-edged swords in cellular redox state: Health beneficial effects at physiologic doses versus deleterious effects at high doses. Oxidative Medicine and Cellular Longevity, 3(4), 228-237. [CrossRef]
• 60. Vrba, J., Kren, V., Vacek, J., Papouskova, B., Ulrichova, J. (2012). Quercetin, quercetin glycosides and taxifolin differ in their ability to induce AhR activation and CYP1A1 expression in HepG2 cells. Phytotherapy Research: PTR, 26(11), 1746-1752. [CrossRef]
• 61. Wang, Z., Zhang, G., Le, Y., Ju, J., Zhang, P., Wan, D., Zhao, Q., Jin, G., Su, H., Liu, J., Feng, J., Fu, Y., Hou, R. (2020). Quercetin promotes human epidermal stem cell proliferation through the estrogen receptor/β-catenin/c-Myc/cyclin A2 signaling pathway. Acta Biochimica et Biophysica Sinica, 52(10), 1102-1110. [CrossRef]
• 62. Caltagirone, S., Ranelletti, F.O., Rinelli, A., Maggiano, N., Colasante, A., Musiani, P., Aiello, F.B., Piantelli, M. (1997). Interaction with type II estrogen binding sites and antiproliferative activity of tamoxifen and quercetin in human non-small-cell lung cancer. American Journal of Respiratory Cell and Molecular Biology, 17(1), 51-59. [CrossRef]
• 63. Vijayababu, M.R., Arunkumar, A., Kanagaraj, P., Venkataraman, P., Krishnamoorthy, G., Arunakaran, J. (2006). Quercetin downregulates matrix metalloproteinases 2 and 9 proteins expression in prostate cancer cells (PC-3). Molecular and Cellular Biochemistry, 287(1-2), 109-116. [CrossRef]
• 64. Mirazimi, S.M.A., Dashti, F., Tobeiha, M., Shahini, A., Jafari, R., Khoddami, M., Sheida, A.H., EsnaAshari, P., Aflatoonian, A.H., Elikaii, F., Zakeri, M.S., Hamblin, M.R., Aghajani, M., Bavarsadkarimi, M., Mirzaei, H. (2022). Application of quercetin in the treatment of gastrointestinal cancers. Frontiers in Pharmacology, 13, 860209. [CrossRef]
• 65. Costa, L.G., Garrick, J.M., Roquè, P.J., Pellacani, C. (2016). Mechanisms of neuroprotection by quercetin: Counteracting oxidative stress and more. Oxidative Medicine and Cellular Longevity, 2016, 2986796. [CrossRef]
• 66. Ali, A., Kim, M.J., Kim, M.Y., Lee, H.J., Roh, G.S., Kim, H.J., Cho, G.J., Choi, W.S. (2018). Quercetin induces cell death in cervical cancer by reducing O-GlcNAcylation of adenosine monophosphate-activated protein kinase. Anatomy & Cell Biology, 51(4), 274-283. [CrossRef]