Design of more potent quinazoline derivatives as EGFRWT inhibitors for the treatment of NSCLC: a computational approach

Muhammad Ibrahim1, Adamu Uzairu1, Gideon Adamu Shallangwa1
1Department of Chemistry, Faculty of Physical Science, Ahmadu Bello University, P.M.B 1045, Zaria, Kaduna State, Nigeria

Tóm tắt

Abstract Background Lung cancer remains the leading and deadly type of cancer worldwide. It was estimated to account for about 25% of the 7 million people that died as a result of cancer-related issues/mortality every year in the world. Non-small cell lung cancer (NSCLC) is the lethal/deadly class of lung cancer with nearly 1.5 million reported cases and less than 20% survival rate. Therefore, it becomes necessary to explore more effective NSCLC drugs. Result A computational approach was employed here to design ten new EGFRWT inhibitors using compound 18 as a template for the design identified with the best binding affinity and good pharmacokinetic properties previously reported in our work. The modeled inhibitory activities of these newly designed EGFRWT inhibitors (range from 7.746966 to 11.09261) were better than that of the hit compound with pIC50 of 7.5639 and gefitinib the positive control with pIC50 of 5.879426. The ligand-binding interaction between these newly designed EGFRWT inhibitors and the EGFR tyrosine kinase receptor as shown in Table 3 was investigated and elucidated using molecular docking protocol. Based on the molecular docking results, the binding affinities of these newly designed EGFRWT inhibitors were found to be between − 8.8 and − 9.5 kcal/mol. The designed compound SFD10 has the highest binding affinity of − 9.5 kcal/mol followed by compound SFD8 (with a binding affinity of − 9.3 kcal/mol), then by compound SFD9 and 4 (each with a binding affinity of − 9.3 kcal/mol). None of them was found to have more than one violation of the filtering criterion used in this study thereby showing good ADMET properties. Conclusion The modeled inhibitory activities and binding affinities of these newly designed EGFRWT inhibitors were found to be higher than that of the template compound and the control (gefitinib) used in this research. They were also seen to be non-toxic with good pharmacokinetic properties.

Từ khóa


Tài liệu tham khảo

Chico LK, Van Eldik LJ, Watterson DM (2009) Targeting protein kinases in central nervous system disorders. Nat Rev Drug Discov 8(11):892

Khan I, Garikapati KR, Setti A, Shaik AB, Makani VKK, Shareef MA, Rajpurohit H, Vangara N, Pal-Bhadra M, Kamal A (2019) Design, synthesis, in silico pharmacokinetics prediction and biological evaluation of 1, 4-dihydroindeno [1, 2-c] pyrazole chalcone as EGFR/Akt pathway inhibitors. Eur J Med Chem 163:636–648. https://doi.org/10.1016/j.ejmech.2018.12.011

Gschwind A, Fischer OM, Ullrich A (2004) The discovery of receptor tyrosine kinases: targets for cancer therapy. Nat Rev Cancer 4(5):361–370. https://doi.org/10.1038/nrc1360

Turker S, Sahinli H, Perkin P, Yazilitas D, Koklu NO, Imamoglu GI, Karacin C, Altinbas M (2018) “Squamos cell lung cancer” case applying with dyspepsia complaints. J Oncol Sci 4(3):147–148

Hizal M, Sendur MA, Bilgin B, Akinci MB, Dede DS, Neselioglu S, Erel O, Yalcin B (2018) J Oncol Sci

Zhao B, Xiao Z, Qi J, Luo R, Lan Z, Zhang Y, Hu X, Tang Q, Zheng P, Xu S (2019) Design, synthesis and biological evaluation of AZD9291 derivatives as selective and potent EGFRL858R/T790M inhibitors. Eur J Med Chem 163:367–380. https://doi.org/10.1016/j.ejmech.2018.11.069

Chan BA, Hughes BG (2015) Targeted therapy for non-small cell lung cancer: current standards and the promise of the future. Translat Lung Cancer Res 4(1):36

Zhang Q, Wang Z, Guo J, Liu L, Han X, Li M, Fang S, Bi X, Tang N, Liu Y (2015) Comparison of single-agent chemotherapy and targeted therapy to first-line treatment in patients aged 80 years and older with advanced non-small-cell lung cancer. Onco Targets Ther 8:893

Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, Gemma A, Harada M, Yoshizawa H, Kinoshita I (2010) Gefitinib or chemotherapy for non–small-cell lung cancer with mutated EGFR. N Engl J Med 362(25):2380–2388. https://doi.org/10.1056/NEJMoa0909530

Kobayashi S, Boggon TJ, Dayaram T, Jänne PA, Kocher O, Meyerson M, Johnson BE, Eck MJ, Tenen DG, Halmos B (2005) EGFR mutation and resistance of non–small-cell lung cancer to gefitinib. N Engl J Med 352(8):786–792. https://doi.org/10.1056/NEJMoa044238

Zhou W, Ercan D, Chen L, Yun C-H, Li D, Capelletti M, Cortot AB, Chirieac L, Iacob RE, Padera R (2009) Novel mutant-selective EGFR kinase inhibitors against EGFR T790M. Nature 462(7276):1070–1074. https://doi.org/10.1038/nature08622

Ibrahim MT, Uzairu A, Shallangwa GA, Uba S (2020) Computer-aided molecular modeling studies of some 2, 3-dihydro-[1, 4] dioxino [2, 3-f] quinazoline derivatives as EGFR WT inhibitors. Beni Suef Univ J Basic Appl Sci 9:1–10

Qin X, Li Z, Yang L, Liu P, Hu L, Zeng C, Pan Z (2016) Discovery of new [1, 4] dioxino [2, 3-f] quinazoline-based inhibitors of EGFR including the T790M/L858R mutant. Bioorg Med Chem 24(13):2871–2881. https://doi.org/10.1016/j.bmc.2016.01.003

Mills N (2006) ChemDraw Ultra 10.0 CambridgeSoft, 100 CambridgePark Drive, Cambridge, MA 02140. www. cambridgesoft. com. Commercial Price: 1910fordownload, 2150 for CD-ROM; Academic Price: 710fordownload, 800 for CD-ROM. ACS Publications

Ibrahim MT, Uzairu A, Shallangwa GA, Uba S (2020) Structure-based design and activity modeling of novel epidermal growth factor receptor kinase inhibitors; an in silico approach. Sci Afr:e00503

Ghamali M, Chtita S, Hmamouchi R, Adad A, Bouachrine M, Lakhlifi T (2016) The inhibitory activity of aldose reductase of flavonoid compounds: combining DFT and QSAR calculations. J Taibah Univ Sci 10(4):534–542. https://doi.org/10.1016/j.jtusci.2015.09.006

Ibrahim MT, Uzairu A, Uba S, Shallangwa GA (2020) Computational virtual screening and structure-based design of some epidermal growth factor receptor inhibitors. Fut J Pharm Sci 6(1):1–16

Ibrahim MT, Uzairu A, Shallangwa GA, Uba S (2019) QSAR modelling and docking analysis of some thiazole analogues as⍺-glucosidase inhibitors. J Eng Exact Sci 5(3):0257–0270. https://doi.org/10.18540/jcecvl5iss3pp0257-0270

Ibrahim MT, Uzairu A, Uba S, Shallangwa GA (2020) Computational modeling of novel quinazoline derivatives as potent epidermal growth factor receptor inhibitors. Heliyon 6(2):e03289

Hadni H, Elhallaoui M (2020) 3D-QSAR, docking and ADMET properties of aurone analogues as antimalarial agents. Heliyon 6(4):e03580

Daina A, Michielin O, Zoete V (2017) SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7(1):42717. https://doi.org/10.1038/srep42717

Hosen S, Dash R, Khatun M, Akter R, Bhuiyan MHR, Rezaul M, Karim NJM, Ahamed F, Islam KS, Afrin S (2017) In silico ADME/T and 3D QSAR analysis of KDR inhibitors. J Appl Pharm Sci 7(01):120–128

Veerasamy R, Rajak H, Jain A, Sivadasan S, Varghese CP, Agrawal RK (2011) Validation of QSAR models-strategies and importance. Int J Drug Design Disc 3:511–519