In Vitro and In Silico Studies of Quercetin and Daidzin as Selective Anticancer Agents

https://doi.org/10.22146/ijc.53552

Muhammad Sulaiman Zubair(1*), Syariful Anam(2), Saipul Maulana(3), Muhammad Arba(4)

(1) Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Tadulako University, Palu 94118, Indonesia
(2) Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Tadulako University, Palu 94118, Indonesia
(3) Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Tadulako University, Palu 94118, Indonesia
(4) Department of Pharmacy, Faculty of Pharmacy, Universitas Halu Oleo, Kendari 93231, Indonesia
(*) Corresponding Author

Abstract


Quercetin and daidzin are flavonoid and flavonoid glycoside type compounds that have been found in many plants and nutraceuticals. This study aims to examine the in vitro cytotoxic and selectivity properties of quercetin and daidzin on breast and cervical cancers and to study their molecular interaction and stability on epidermal growth factor receptor tyrosine kinase (EGFR-TK) by applying molecular docking and molecular dynamics (MD) simulations. In vitro anticancer activity was performed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method on breast cancer cell (T47D), cervical cancer cells (HeLa), and Vero normal cells, while molecular docking and MD simulation were done by using AutoDock Vina and Amber18 package software, respectively. Quercetin and daidzin showed potent cytotoxic and high selectivity on both cell lines. Daidzin was found to has a higher IC50 and selectivity index than quercetin. Docking and MD results showed that both compounds prefer to interact with epidermal growth factor receptor tyrosine kinase (EGFR-TK). Daidzin showed better interaction than quercetin with a docking score of -9.6 kcal/mol. Also, daidzin was found more stable than quercetin with low RMSD and RMSF values.


Keywords


quercetin; daidzin; T47D; HeLa; docking; molecular dynamics

Full Text:

Full Text PDF


References

[1] Vasseur, R., Baud, S., Steffenel, L.A., Vigouroux, X., Martiny, L., Krajecki, M., and Dauchez, M., 2015, Inverse docking method for new proteins targets identification: A parallel approach, Parallel Comput., 42, 48–59.

[2] Istyastono, E.P., 2017, Binary quantitative structure-activity relationship analysis to increase the predictive ability of structure-based virtual screening campaigns targeting cyclooxygenase-2, Indones. J. Chem., 17 (2), 322–329.

[3] Phosrithong, N., and Ungwitayatorn, J., 2010, Molecular docking study on anticancer activity of plant-derived natural products, Med. Chem. Res., 19 (8), 817–835.

[4] Teekaraman, D., Elayapillai, S.P., Viswanathan, M.P., and Jagadeesan, A., 2019, Quercetin inhibits human metastatic ovarian cancer cell growth and modulates components of the intrinsic apoptotic pathway in PA-1 cell line, Chem. Biol. Interact., 300, 91–100.

[5] Li, H., and Chen, C., 2018, Quercetin has antimetastatic effects on gastric cancer cells via the interruption of uPA/uPAR function by modulating NF-κb, PKC-δ, ERK1/2, and AMPKα, Integr. Cancer Ther., 17 (2), 511–523.

[6] Khan, F., Niaz, K., Maqbool, F., Hassan, F.I., Abdollahi, M., Venkata, K.C.N., Nabavi, S.M., and Bishayee, A., 2016, Molecular targets underlying the anticancer effects of quercetin: An update, Nutriens, 8 (9), 529.

[7] Xiang, T., Fang, Y., and Wang, S.X., 2014, Quercetin suppresses HeLa cells by blocking PI3K/Akt pathway, J. Huazhong Univ. Sci. Technol., Med. Sci., 34 (5), 740–744.

[8] Wang, Q., Ge, X., Tian, X., Zhang, Y., Zhang, J., and Zhang, P., 2013, Soy isoflavone: The multipurpose phytochemical (Review), Biomed. Rep., 1 (5), 697–701.

[9] Boucher, B.A., Cotterchio, M., Anderson, L.N., Kreiger, N., Kirsh, V.A., and Thompson, L.U., 2012, Use of isoflavone supplements is associated with reduced postmenopausal breast cancer risk, Int. J. Cancer, 132, 1439–1450.

[10] Shan, C., Tan, J.H., Ou, T.M., and Huang, Z.S., 2013, Natural products and their derivatives as G-quadruplex binding ligands, Sci. China Chem., 56 (10), 1351–1363.

[11] Chen, H., Yao, K., Nadas, J., Bode, A.M., Malakhova, M., Oi, N., Li, H., Lubet, R.A., and Dong, Z., 2012, Prediction of molecular targets of cancer preventing flavonoid compounds using computational methods, PLoS ONE, 7 (5), e38261.

[12] Zubair, M.S., Anam, S., and Lallo, S., 2016, Cytotoxic activity and phytochemical standardization of Lunasia amara Blanco wood extract, Asian Pac. J. Trop. Biomed., 6 (11), 962–966.

[13] Trott, O., and Olson, A.J., 2010, AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, J. Comput. Chem., 31 (2), 455–461.

[14] Dassault Systèmes BIOVIA, 2016, Discovery Studio Modeling Environment Release 2017, Dassault Systèmes, San Diego, USA.

[15] Seeliger, D., and de Groot, B.L., 2010. Ligand docking and binding site analysis with PyMOL and Autodock/Vina, J. Comput.-Aided Mol. Des., 24 (5), 417–422.

[16] Arba, M., Ruslin, Kalsum, W.U., Alroem, A., Muzakkar, M.Z., Usman, I., and Tjahjono, D.H., 2018, QSAR, molecular docking and dynamics studies of quinazoline derivatives as inhibitor of phosphatidylinositol 3-kinase, J. Appl. Pharm. Sci., 8 (5), 1–9.

[17] Maier, J.A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K.E., and Simmerling, C., 2015, ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB, J. Chem. Theory Comput., 11 (8), 3696–3713.

[18] Wang, J.M., Wolf, R.M., Caldwell, J.W., Kollman, P.A., and Case, D.A., 2004, Development and testing of a general amber force field, J. Comput. Chem., 25 (9), 1157–1174.

[19] Jakalian, A., Jack, D.B., and Bayly, C.I., 2002, Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation, J. Comput. Chem., 23 (16), 1623–1641.

[20] Elber, R., Ruymgaart, A.P., and Hess, B., 2011, SHAKE parallelization, Eur. Phys. J. Spec. Top., 200 (1), 211–223.

[21] Darden, T., York, D., and Pedersen, L., 1993, Particle mesh Ewald: An N·log(N) method for Ewald sums in large systems, J. Chem. Phys., 98 (12), 10089–10092.

[22] Roe, D.R., and Cheatham III, T.E., 2013, PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data, J. Chem. Theory Comput., 9 (7), 3084–3095.

[23] Humphrey, W., Dalke, A., and Schulten, K., 1996, VMD: Visual molecular dynamics, J. Mol. Graphics, 14 (1), 33–38.

[24] Mahmoud, A.M., and El-Shemy, H.A., 2012, Efficacy assessment for several natural products with potential cytotoxic activity against breast and cervix cancers, J. Arid Land Stud., 22, 107–110.

[25] Kim, D.H., Jung, H.A., Park, S.J., Kim, J.M., Lee, S., Choi, J.S., Cheong, J.H., Ko, K.H., and Ryu, J.H., 2010, The effects of daidzin and its aglycon, daidzein, on the scopolamine-induced memory impairment in male mice, Arch. Pharmacal Res., 33 (10), 1685–1690.

[26] Liu, H., Zhu, Y., Wang, T., Qi, J., and Liu, X., 2018, Enzyme-site blocking combined with optimization of molecular docking for efficient discovery of potential tyrosinase specific inhibitors from Puerariae lobatae Radix, Molecules, 23 (10), 2612.

[27] Heim, K.E., Tagliaferro, A.R., and Bobilya, D.J., 2002, Flavonoid antioxidants: Chemistry, metabolism and structure-activity relationships, J. Nutr. Biochem., 13 (10), 572–584.

[28] Wee, P., and Wang, Z., 2017, Epidermal growth factor receptor cell proliferation signaling pathways, Cancers, 9 (5), 52.

[29] Fajrin, F.A., Nugroho, A.E., Susilowati, R., and Nurrochmad, A., 2018, Molecular docking analysis of ginger active compound on transient receptor potential cation channel subfamily V member 1 (TRPV1), Indones. J. Chem., 18 (1), 179–185.

[30] Zubair, M.S., Anam, S., Khumaidi, A., Susanto, Y., Hidayat, M., and Ridhay, A., 2016, Molecular docking approach to identify potential anticancer compound from Begonia (Begonia sp), AIP Conf. Proc., 1755 (1), 080005.

[31] Prasasty, V.D., and Istyastono, E.P., 2020, Structure-based design and molecular dynamics simulations of pentapeptide AEYTR as a potential acetylcholinesterase inhibitor, Indones. J. Chem., 20 (4), 953–959.

[32] Liu, K., and Kokubo, H., 2017, Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations: A cross-docking study, J. Chem. Inf. Model., 57 (10), 2514–2522.

[33] Arba, M., and Tjahjono, D.H., 2015, The binding modes of cationic porphyrin-anthraquinone hybrids to DNA duplexes: in silico study, J. Biomol. Struct. Dyn., 33 (3), 657–665.

[34] Masuda, H., Zhang, D., Bartholomeusz, C., Doihara, H., Hortobagyi, G.N., and Ueno, N.T., 2012, Role of epidermal growth factor receptor in breast cancer, Breast Cancer Res. Treat., 136 (2), 331–345.

[35] Viswanath, L., Naveen, T., Siddanna, P.,Chetana, P., Geethasree, M., Pasha, S.C.R.T., Bindhu, J., Pramod, K.P.R., Ashalatha, D., Priyadarshni, V., Ajai, G.V., Ashwini, V., Mahalakshmi, A., Riach, T., Sugashwaran, S., and Yeshaswini, T., 2014, Epidermal growth factor receptor (EGFR) overexpression in patients with advanced cervical cancer, J. Clin. Oncol., 321 (Suppl. 15), e16538.



DOI: https://doi.org/10.22146/ijc.53552

Article Metrics

Abstract views : 5378 | views : 3786


Copyright (c) 2021 Indonesian Journal of Chemistry

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

 


Indonesian Journal of Chemistry (ISSN 1411-9420 /e-ISSN 2460-1578) - Chemistry Department, Universitas Gadjah Mada, Indonesia.

Web
Analytics View The Statistics of Indones. J. Chem.