Design of New Quinazoline Derivative as EGFR (Epidermal Growth Factor Receptor) Inhibitor through Molecular Docking and Dynamics Simulation

Herlina Rasyid(1), Bambang Purwono(2), Harno Dwi Pranowo(3*)

(1) Austrian-Indonesian Centre (AIC) for Computational Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(2) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(3) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(*) Corresponding Author


Erlotinib, Afatinib, and WZ4002 are quinazoline derivative compounds and classified as first, second, and third-generation EGFR inhibitor. All inhibitors have been given directly to cancer patients for many years but find some resistance. These three compounds are candidates as the lead compound in designing a new inhibitor. This work aims to design a new potential quinazoline derivative as an EGFR inhibitor focused on the molecular docking result of the lead compound. The research method was started in building a pharmacophore model of the lead compound then used to design a new potential inhibitor by employing the AutoDock 4.2 program. Molecular dynamics simulation evaluates the interaction of all complexes using the Amber15 program. There are three new potential compounds (A1, B1, and C1) whose hydrogen bond interaction in the main catalytic area (Met769 residue). The Molecular Mechanics Generalized Born Surface Area (MM-GBSA) binding energy calculation shows that B1 and C1 compounds have lower binding energies than erlotinib as a positive control, which indicates that B1 and C1 are potential as EGFR inhibitor.


quinazoline; EGFR; molecular docking; molecular dynamics simulation

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[1] Herbst, R.S., 2004, Review of epidermal growth factor receptor biology, Int. J. Radiat. Oncol. Biol. Phys., 59 (2), S21–S26.

[2] Vallbohmer, D., and Lenz, H.J., 2005, Epidermal growth factor receptor as a target for chemotherapy, Clin. Colorectal Cancer, 5 (Suppl. 1), S19–27.

[3] Baselga, J., 2002, Why the epidermal growth factor receptor? The rationale for cancer therapy, Oncologist, 7 (Suppl. 4), 2–8.

[4] Singh, M., and Jadhav, H.R., 2018, Targeting non-small cell lung cancer with small-molecule EGFR tyrosine kinase inhibitors, Drug Discovery Today, 23 (3), 745–753.

[5] Ismail, R.S.M., Ismail, N.S.M., Abuserii, S., and Abou El Ella, D.A., 2016, Recent advances in 4-aminoquinazoline based scaffold derivatives targeting EGFR kinases as anticancer agents, Future J. Pharm. Sci., 2 (1), 9–19.

[6] Yu, H., Li, Y., Ge, Y., Song, Z., Wang, C., Huang, S., Jin, Y., Han, X., Zhen, Y., Liu, K., Zhou, Y., and Ma, X., 2016, Novel 4-anilinoquinazoline derivatives featuring an 1-adamantyl moiety as potent EGFR inhibitors with enhanced activity against NSCLC cell lines, Eur. J. Med. Chem., 110, 195–203.

[7] Chen, Y.M., Luo, Y.H., Wu, C., Lee, Y.C., Perng, R.P., and Whang-Peng, J., 2015, Erlotinib or chemotherapy in second-lne or later treatment of tumor EGFR wild-type pulmonary adenocarcinoma patients, J. Cancer Res. Pract., 2 (1), 3–11.

[8] Teraishi, F., Kagawa, S., Watanabe, T., Tango, Y., Kawashima, T., Umeoka, T., Nisizaki, M., Tanaka, N., and Fujiwara, T., 2005, ZD1839 (Gefitinib, ’Iressa’), an epidermal growth factor receptor-tyrosine kinase inhibitor, enhances the anti-cancer effects of TRAIL in human esophageal squamous cell carcinoma, FEBS Lett., 579 (19), 4069–4075.

[9] Tu, Y., Ouyang, Y., Xu, S., Zhu, Y., Li, G., Sun, C., Zheng, P., and Zhu, W., 2016, Design, synthesis, and docking studies of afatinib analogs bearing cinnamamide moiety as potent EGFR inhibitors, Bioorg. Med. Chem., 24 (7), 1495–1503.

[10] Cheng, H., Nair, S.K., and Murray, B.W., 2016, Recent progress on third generation covalent EGFR inhibitors, Bioorg. Med. Chem. Lett., 26 (8), 1861–1868.

[11] Kobayashi, S., Boggon, T.J., Dayaram, T., Jänne, P.A., Kocher, O., Meyerson, M., Johnson, B.E., Eck, M.J., Tenen, D.G., and Halmos, B., 2005, EGFR mutation and resistance of non–small-cell lung cancer to gefitinib, N. Engl. J. Med., 352 (8), 786–792.

[12] Li, D., Ambrogio, L., Shimamura, T., Kubo, S., Takahashi, M., Chirieac, L.R., Padera, R.F., Shapiro, G.I., Baum, A., Himmelsbach, F., Rettig, W.J., Meyerson, M., Solca, F., Greulich, H., and Wong, K.K., 2008, BIBW2992, an irreversible EGFR/HER2 inhibitor highly effective in preclinical lung cancer models, Oncogene, 27 (34), 4702–4711.

[13] Wang, S., Song, Y., and Liu, D., 2017, EAI045: The fourth-generation EGFR inhibitor overcoming T790M and C797S resistance, Cancer Lett., 385, 51–54.

[14] Huey, R., Morris, G.M., Olson, A.J., and Goodsell, D.S., 2007, A semiempirical free energy force field with charge-based desolvation, J. Comput. Chem., 28 (6), 1145–1152.

[15] Traxler, P., Green, J., Mett, H., Séquin, U., and Furet, P., 1999, Use of a pharmacophore model for the design of EGFR tyrosine kinase inhibitors: Isoflavones and 3-phenyl-4(1H)-quinolones, J. Med. Chem., 42, 1018–1026.

[16] 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.

[17] Rasyid, H., Purwono, B., and Armunanto, R., 2018, Quantitative structure activity relationship (QSAR) based on electronic descriptors and docking studies of quinazoline derivatives for anticancer activity, Orient. J. Chem., 34 (5), 2361–2369.

[18] Pranowo, H.D., Tahir, I., and Widiatmoko, A., 2007, Quantitative relationship of electronic structure and inhibition activity of curcumin analogs on ethoxyresorufin o-dealkylation (EROD) reaction, Indones. J. Chem., 7 (1), 78–82.

[19] Rasyid, H., Purwono, B., Hofer, T.S., and Pranowo, H.D., 2019, Hydrogen bond stability of quinazoline derivatives compounds in complex against EGFR using molecular dynamics simulation, Indones. J. Chem., 19 (2), 461–469.

[20] Pitaloka, D.A.E., Damayanti, S., Artarini, A.A., and Sukandar, E.Y., 2019, Molecular docking, dynamics simulation, and scanning electron microscopy (SEM) examination of clinically isolated Mycobacterium tuberculosis by ursolic acid: A pentacyclic triterpenes, Indones. J. Chem., 19 (2), 328–336.

[21] Dwiastuti, R., Radifar, M., Marchaban, M., Noegrohati, S., and Istyastono, E.P., 2016, Molecular dynamics simulations and empirical observations on soy lecithin liposome preparation, Indones. J. Chem., 16 (2), 222–228.

[22] Arba, M., Sufriadin, M., and Tjahjono, D.H., 2020, Identification of phosphatidylinositol 3-kinase δ (PI3Kδ) Inhibitor: pharmacophore-based virtual screening and molecular dynamics simulation, Indones. J. Chem., 20 (5), 1070–1079.

[23] Morris, G., and Huey, R., 2009, AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility, J. Comput. Chem., 30 (16), 2785–2791.

[24] Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A., Cheeseman, J.R., Scalmani, G., Barone, V., Petersson, G. A., Nakatsuji, H., Li, X., Caricato, M., Marenich, A.V., Bloino, J., Janesko, B.G., Gomperts, R., Mennucci, B., Hratchian, H.P., Ortiz, J.V., Izmaylov, A.F., Sonnenberg, J.L., Williams-Young, D., Ding, F., Lipparini, F., Egidi, F., Goings, J., Peng, B., Petrone, A., Henderson, T., Ranasinghe, D., Zakrzewski, V.G., Gao, J., Rega, N., Zheng, G., Liang, W., Hada, M., Ehara, M., Toyota, K., Fukuda, R., Hasegawa, J., Ishida, M., Nakajima, T., Honda, Y., Kitao, O., Nakai, H., Vreven, T., Throssell, K., Montgomery, J.A., Jr., Peralta, J.E., Ogliaro, F., Bearpark, M.J., Heyd, J.J., Brothers, E.N., Kudin, K.N., Staroverov, V.N., Keith, T.A., Kobayashi, R., Normand, J., Raghavachari, K., Rendell, A.P., Burant, J.C., Iyengar, S.S., Tomasi, J., Cossi, M., Millam, J.M., Klene, M., Adamo, C., Cammi, R., Ochterski, J.W., Martin, R.L., Morokuma, K., Farkas, O., Foresman, J.B., and Fox, D.J., 2016, Gaussian 16, Revision C.02, Gaussian, Inc., Wallingford CT.

[25] Dassault Systèmes BIOVIA, 2019, Discovery Studio Visualizer v., Dassault Systèmes, San Diego, USA.

[26] Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., and Ferrin, T.E., 2004, UCSF Chimera–a visualization system for exploratory research and analysis, J Comput Chem., 25 (13), 1605–1612.

[27] Case, D.A., Betz, R.M., Botello-Smith, W., Cerutti, D.S., Cheatham, 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., Swails, J., Walker, R.C., Wang, J., Wolf, R.M., Wu, X., Xiao, L., York, D.M., and Kollman, P.A., 2016, AMBER 2016, University of California, San Francisco.

[28] Humprey, W., Dalke, A., and Schulten, K., 1996, VMD: Visual molecular dynamics, J. Mol. Graphics, 14, 33–38.

[29] Wang, J., 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.

[30] Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., and Klein, M.L., 1983, Comparison of simple potential functions for simulating liquid water, J. Chem. Phys., 79 (2), 926–935.

[31] Mustafa, M., Mirza, A., and Kannan, N., 2011, Conformational regulation of the EGFR kinase core by the juxtamembrane and C‐terminal tail: A molecular dynamics study, Proteins Struct. Funct. Bioinf., 79 (1), 99–114.

[32] Liu, B., Bernard, B., and Wu, J.H., 2006, Impact of EGFR point mutations on the sensitivity to gefitinib: Insights from comparative structural analyses and molecular dynamics simulations, Proteins, 65 (2), 346, 331–346.

[33] 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.

[34] Miller, B.R., McGee, T.D., Swails, J.M., Homeyer, N., Gohlke, H., and Roitberg, A.E., 2012, An efficient program for end-state free energy calculations, J. Chem. Theory Comput., 8 (9), 3314–3321.

[35] Patel, H., Pawara, R., Ansari, A., and Surana, S., 2017, Recent updates on third generation EGFR inhibitors and emergence of fourth generation EGFR inhibitors to combat C797S resistance, Eur. J. Med. Chem., 142, 32–47.

[36] Stamos, J., Sliwkowski, M.X., and Eigenbrot, C., 2002, Structure of the epidermal growth factor receptor kinase domain alone and in complex with a 4-anilinoquinazoline inhibitor, J. Biol. Chem., 277 (48), 46265–46272.

[37] Hou, T., Zhu, L., Chen, L., and Xu, X., 2003, Mapping the binding site of a large set of quinazoline type EGF-R inhibitors using molecular field analyses and molecular docking studies, J. Chem. Inf. Comput. Sci., 43 (1), 273–283.

[38] Rabindran, S.K., Discafani, C.M., Rosfjord, E.C., Baxter, M., Floyd, M.B., Golas, J., Hallett, W.A., Johnson, B.D., Nilakantan, R., Overbeek, E., Reich, M.F., Shen, R., Shi, X., Tsou, H.R., Wang, Y.F., and Wissner, A., 2004, Antitumor activity of HKI-272, an orally active, irreversible inhibitor of the HER-2 tyrosine kinase, Cancer Res., 64 (11), 3958–3965.

[39] Eskens, F.A.L.M., Mom, C.H., Planting, A.S.T., Gietema, J.A., Amelsberg, A., Huisman, H., van Doorn, L., Burger, H., Stopfer, P., Verweij, J., and de Vries, E.G.E., 2008, A phase I dose escalation study of BIBW 2992, an irreversible dual inhibitor of epidermal growth factor receptor 1 (EGFR) and 2 (HER2) tyrosine kinase in a 2-week on, 2-week off schedule in patients with advanced solid tumours, Br. J. Cancer, 98 (1), 80–85.


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