Non-small cell lung cancer (NSCLC) has extreme mortality and morbidity rates compared to colon, prostate, and breast cancer. Presently, available medications for NSCLC have failed to provide the desired therapeutic outcome. Therefore, there is a need to speed up the drug development process, cost-effectively. New chemical entities such as EAI045 and EAI001 and a few small molecules allosterically inhibit epidermal growth factor receptor (EGFR) by binding to the allosteric domain to form a stable protein-ligand complex. This discovery is a milestone in inhibiting the EGFR-mutations such as L858R/T790M/C797S and L858R/T790M point alteration in lung cancer cells. Hence, our study aimed to identify and repurpose available drugs for treating NSCLC by targeting the EGFR allosteric region. A homology model was developed as the available protein structure had missing loops and amino acid sequences. Food and Drug Administration (FDA)-approved drugs (~2800) were docked with the validated homology protein using Schrodinger® Maestro software. Two docking methods were used, consensual docking and normal docking, for the comparative study of the hit compounds to increase the probability of identifying the most potent compound for the EGFR allosteric site. Molecular dynamic simulations were performed on the shortlisted compounds to check the potency. The best hits, such as polydatin, ezetimibe, methotrexate, and arbutamine, were identified based on the root mean square deviation of protein−ligand interaction, ligand stability, and bond interactions between the ligand and protein. The study highlights the potential FDA-approved drugs that can be repurposed for NSCLC treatment.
Maity S, Vithalkar MP, Baby KP, Nayak UY, Pai KSR, Nayak Y. In silico drug repurposing in non-small cell lung cancer by docking and molecular dynamic simulations for epidermal growth factor receptor allosteric site inhibition. J Appl Pharm Sci. 2025: Article in Press. http://doi.org/10.7324/JAPS.2025.242311
1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin. 2021;71:7–33. doi: https://doi.org/10.3322/caac.21654
2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7–30. doi: https://doi.org/10.3322/caac.21590
3. Carcereny E, Morán T, Capdevila L, Cros S, Vilà L, de los Llanos Gil M, et al. The epidermal growth factor receptor (EGRF) in lung cancer. Transl Respir Med. 2015;3:1–8. doi: https://doi.org/10.1186/s40247-015-0013-z
4. Sullivan I, Planchard D. Next-generation EGFR tyrosine kinase inhibitors for treating EGFR-mutant lung cancer beyond first line. Front Med. 2016;3:1–13. doi: https://doi.org/10.3389/fmed.2016.00076
5. Roskoski RJr. Classification of small molecule protein kinase inhibitors based upon the structures of their drug-enzyme complexes. Pharmacol Res. 2016;103:26–48. doi: https://doi.org/10.1016/j.phrs.2015.10.021
6. Maity S, Pai KSR, Nayak Y. Advances in targeting EGFR allosteric site as anti-NSCLC therapy to overcome the drug resistance. Pharmacol Rep. 2020;72:799–813. doi: https://doi.org/10.1007/s43440-020-00131-0
7. Purba E, Saita E, Maruyama I. Activation of the EGF Receptor by ligand binding and oncogenic mutations: the “Rotation Model.” Cells. 2017;6:13. doi: https://doi.org/10.3390/cells6020013
8. Ling Y, Jing M, Wang X dong. Allosteric therapies for lung cancer. Cancer Metastasis Rev. 2015;34:303–12. doi: https://doi.org/10.1007/s10555-015-9567-z
9. Jia Y, Yun CH, Park E, Ercan D, Manuia M, Juarez J, et al. Overcoming EGFR(T790M) and EGFR(C797S) resistance with mutant-selective allosteric inhibitors. Nature. 2016;534:129–32. doi: https://doi.org/10.1038/nature17960
10. Zhao P, Yao MY, Zhu SJ, Chen JY, Yun CH. Crystal structure of EGFR T790M/C797S/V948R in complex with EAI045. Biochem Biophys Res Commun. 2018;502:332–7. doi: https://doi.org/10.1016/j.bbrc.2018.05.154
11. Wang S, Song Y, Liu D. EAI045: the fourth-generation EGFR inhibitor overcoming T790M and C797S resistance. Cancer Lett. 2017;385:51–4. doi: https://doi.org/10.1016/j.canlet.2016.11.008
12. Caporuscio F, Tinivella A, Restelli V, Semrau MS, Pinzi L, Storici P, et al. Identification of small-molecule EGFR allosteric inhibitors by high-Throughput docking. Fut Med Chem. 2018;10:1545–53. doi: https://doi.org/10.4155/fmc-2018-0063
13. Saipriya DS, Prakash A, Kini SG, Bhatt GV, Ranganath Pai KS, Biswas S, et al. Design, synthesis, antioxidant and anticancer activity of novel schiff’s bases of 2-amino benzothiazole. Indian J Pharm Educ Res. 2018;52:S333–42. doi: https://doi.org/10.5530/ijper.52.4s.114
14. Chen IJ, Foloppe N. Drug-like bioactive structures and conformational coverage with the ligprep/confgen suite: comparison to programs MOE and catalyst. J Chem Inf Model. 2010;50:822–39. doi: https://doi.org/10.1021/ci100026x
15. Roos K, Wu C, Damm W, Reboul M, Stevenson JM, Lu C, et al. OPLS3e: Extending force field coverage for drug-like small molecules. J Chem Theory Comput. 2019;15:1863–74. doi: https://doi.org/10.1021/acs.jctc.8b01026
16. Sastry GM, Adzhigirey M, Day T, Annabhimoju R, Sherman W. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J Computer-Aided Mol Design. 2013;27:221–34. doi: https://doi.org/10.1007/s10822-013-9644-8
17. Rostkowski M, Olsson MH, Søndergaard CR, Jensen JH. Graphical analysis of pH-dependent properties of proteins predicted using PROPKA. BMC Structural Biol. 2011;11:6. doi: https://doi.org/10.1186/1472-6807-11-6
18. Subhani S, Jayaraman A, Jamil K. Homology modelling and molecular docking of MDR1 with chemotherapeutic agents in non-small cell lung cancer. Biomed Pharmacother. 2015;71:37–45. doi: https://doi.org/10.1016/j.biopha.2015.02.009
19. Jacobson MP, Pincus DL, Rapp CS, Day TJF, Honig B, Shaw DE, et al. A hierarchical approach to all-atom protein loop prediction. Proteins: Struct Funct Bioinf. 2004;55:351–67. doi: https://doi.org/10.1002/prot.10613
20. Ramachandran GN, Ramakrishnan C, Sasisekharan V. Stereochemistry of polypeptide chain configurations. J Mol Biol. 1963;7:95–9. doi: https://doi.org/10.1016/S0022-2836(63)80023-6
21. Isa AS, Uzairu A, Umar UM, Ibrahim MT, Umar AB, Tabti K, et al. In silico exploration of novel EGFR-targeting compounds: integrative molecular modeling, docking, pharmacokinetics, and MD simulations for advancing anti-cervical cancer therapeutics. Sci Rep. 2025;15:7334. doi: https://doi.org/10.1038/s41598-025-91135-4
22. Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, et al. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem. 2004;47:1750–9. doi: https://doi.org/10.1021/jm030644s
23. Damm-Ganamet KL, Arora N, Becart S, Edwards JP, Lebsack AD, McAllister HM, et al. Accelerating lead identification by high throughput virtual screening: prospective case studies from the pharmaceutical industry. J Chem Inf Model. 2019;59:2046–62. doi: https://doi.org/10.1021/acs.jcim.8b00941
24. Akash S, Islam MR, Bhuiyan AA, Islam MN, Bay?l I, Saleem RM, et al. In silico evaluation of anti-colorectal cancer inhibitors by Resveratrol derivatives targeting Armadillo repeats domain of APC: molecular docking and molecular dynamics simulation. Front Oncol. 2024;14:1360745. doi: https://doi.org/10.3389/fonc.2024.1360745
25. Baby K, Maity S, Mehta CH, Suresh A, Nayak UY, Nayak Y. Targeting SARS-CoV-2 RNA-dependent RNA polymerase: an in silico drug repurposing for COVID-19. F1000Res. 2020;9:1166. doi: https://doi.org/10.12688/f1000research.26359.1
26. Yu H, Dalby PA. Coupled molecular dynamics mediate long-and short-range epistasis between mutations that affect stability and aggregation kinetics. Proc Natl Acad Sci. 2018;115:E11043–52. doi: https://doi.org/10.1073/pnas.1810324115
27. Passaro A, Bestvina C, Velez Velez M, Garassino MC, Garon E, Peters S. Severity of COVID-19 in patients with lung cancer: evidence and challenges. J Immunother Cancer. 2021;9(3):e002266. doi: https://doi.org/10.1136/jitc-2020-002266
28. Rogado J, Pangua C, Serrano-Montero G, Obispo B, Marino AM, Pérez-Pérez M, et al. Covid-19 and lung cancer: a greater fatality rate? Lung Cancer. 2020;146:19–22. doi: https://doi.org/10.1016/j.lungcan.2020.05.034
29. Baby K, Maity S, Mehta CH, Suresh A, Nayak UY, Nayak Y. SARS-CoV-2 entry inhibitors by dual targeting TMPRSS2 and ACE2: an in silico drug repurposing study. Eur J Pharmacol. 2021;896:173922. doi: https://doi.org/10.1016/j.ejphar.2021.173922
30. Sutto L, Gervasio FL. Effects of oncogenic mutations on the conformational free-energy landscape of EGFR kinase. Proc Natl Acad Sci U S A 2013;110:10616–21. doi: https://doi.org/10.1073/ pnas.1221953110
31. Kim MK, Yee J, Cho YS, Jang HW, Han JM, Gwak HS. Risk factors for erlotinib-induced hepatotoxicity: a retrospective follow-up study. BMC Cancer. 2018;18:1–7. doi: https://doi.org/10.1186/s12885-018-4891-7
32. Zhang Y, Wang C, Liu Z, Meng Q, Huo X, Liu Q, et al. P-gp is involved in the intestinal absorption and biliary excretion of afatinib in vitro and in rats. Pharmacol Rep. 2018;70:243–50. doi: https://doi.org/10.1016/j.pharep.2017.10.005
33. Fassunke J, Müller F, Keul M, Michels S, Dammert MA, Schmitt A, et al. Overcoming EGFR G724S -mediated osimertinib resistance through unique binding characteristics of second-generation EGFR inhibitors. Nat Commun. 2018;9:4655. doi: https://doi.org/10.1038/s41467-018-07078-0
34. Baby K, Maity S, Mehta CH, Nayak UY, Shenoy GG, Pai KSR, et al. Computational drug repurposing of Akt-1 allosteric inhibitors for non-small cell lung cancer. Sci Rep. 2023;13(1):7947. doi: https://doi.org/10.1038/s41598-023-35122-7
35. Leonetti A, Sharma S, Minari R, Perego P, Giovannetti E, Tiseo M. Resistance mechanisms to osimertinib in EGFR-mutated non-small cell lung cancer. Br J Cancer. 2019;121:725–37. doi: https://doi.org/10.1038/s41416-019-0573-8
36. Gupta EK, Ito MK. Ezetimibe: The first in a novel class of selective cholesterol-absorption inhibitors. Heart Dis. 2002;4:399–409. doi: https://doi.org/10.1097/00132580-200211000-00011
37. Balzer BWR, Loo C, Lewis CR, Trahair TN, Anazodo AC. Adenocarcinoma of the lung in childhood and adolescence: a systematic review. J Thoracic Oncol. 2018;13:1832–41. doi: https://doi.org/10.1016/j.jtho.2018.08.2020
38. Du QH, Peng C, Zhang H. Polydatin: a review of pharmacology and pharmacokinetics. Pharm Biol. 2013;51:1347–54. doi: https://doi.org/10.3109/13880209.2013.792849
39. Bavetta M, Silvaggio D, Campione E, Sollena P, Formica V, Coletta D, et al. The effects of association of topical polydatin improves the preemptive systemic treatment on EGFR inhibitors cutaneous adverse reactions. J Clin Med. 2021;10:1–8. doi: https://doi.org/10.3390/jcm10030466
40. Smyth JF, Ford HT. Methotrexate in the chemotherapy of lung cancer. Cancer Treatment Rep. 1981;65:161–3.
41. Ketteler T, Krahwinkel W, Wolfertz J, Godke J, Hoffmeister T, Scheuble L, et al. Arbutamine stress echocardiography. Eur Heart J. 1997;18:D24–30. doi: https://doi.org/10.1093/eurheartj/18.suppl_d.24
42. Khokhar FM, Jahangir TM, Khuhawar MY, Khaskheli MI, Khokhar LA, Abro MI, et al. Analysis of platinum-based anticancer injections cisplatin and carboplatin in blood serum and urine of cancer patients by photometry, fluorometry, liquid chromatography using a Schiff-base as derivatizing reagent. J Pharm Biomed Anal. 2024;238:115808. Available from: https://www.sciencedirect.com/science/article/pii/S0731708523005770
43. Khokhar FM, Jahangir TM, Khuhawar MY, Qureshi MS, Khaskheli MI, Khokhar LAK. High performance liquid chromatographic separation of platinum (II), gold (III), vanadium (IV), vanadium (V), molybdenum (VI) and analysis of cis-platin as platinum (II) in cis-plasol injection, urine, and blood serum using pyridoxal-4-phenyl-3- thiosemicarbazone as complexing reagent. J Liq Chromatogr Relat Technol. 2020;43(1–2):29–36. Available from: doi: https://doi.org/10.1080/10826076.2019.1645029
Year
Month