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Research Article

Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study

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Pages 299-306 | Received 29 Dec 2017, Accepted 23 May 2018, Published online: 11 Sep 2018

References

  • Metro G, Finocchiaro G, Toschi L, et al. Epidermal growth factor receptor (EGFR) targeted therapies in non-small cell lung cancer (NSCLC). Rev Recent Clin Trials. 2006;1:1–13.
  • Milik SN, Lasheen DS, Serya RAT, et al. How to train your inhibitor: design strategies to overcome resistance to epidermal growth factor receptor inhibitors. Eur J Med Chem. 2017;142:131–151.
  • Ke EE, Wu YL. EGFR as a pharmacological target in EGFR-mutant non-small-cell lung cancer: where do we stand now? Trends Pharmacol Sci. 2016;37:887–903.
  • Raghav D, Sharma V, Agarwal SM. Structural investigation of deleterious non-synonymous SNPs of EGFR gene. Interdiscip Sci. 2013;5:60–68.
  • De Castro DG, Clarke PA, Al-Lazikani B, et al. Personalized cancer medicine: molecular diagnostics, predictive biomarkers, and drug resistance. Clin Pharmacol Ther. 2013;93:252–259.
  • Yadav IS, Singh H, Khan I, et al. EGFRIndb: epidermal growth factor receptor inhibitor database. Anticancer Agents Med Chem. 2014;14:928–935.
  • Zhou W, Ercan D, Chen L, et al. Novel mutant-selective EGFR kinase inhibitors against EGFR T790M. Nature 2009;462:1070–1074.
  • Yun C-H, Mengwasser KE, Toms AV, et al. The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP. Proc Natl Acad Sci USA. 2008;105:2070–2075.
  • Patel H, Pawara R, Ansari A, et al. Recent updates on third generation EGFR inhibitors and emergence of fourth generation EGFR inhibitors to combat C797S resistance. Eur J Med Chem. 2017;142:32–47.
  • Engel J, Lategahn J, Rauh D. Hope and disappointment: covalent inhibitors to overcome drug resistance in non-small cell lung cancer. ACS Med Chem Lett. 2016;7:2–5.
  • Juchum M, Günther M, Laufer SA. Fighting cancer drug resistance: opportunities and challenges for mutation-specific EGFR inhibitors. Drug Resist Updat. 2015;20:12–28.
  • Agarwal SM, Pal D, Gupta M, et al. Insight into discovery of next generation reversible TMLR inhibitors targeting EGFR activating and drug resistant T790M mutants. Curr Cancer Drug Targets 2017;17:617–636.
  • Chen L, Fu W, Feng C, et al. Structure-based design and synthesis of 2,4-diaminopyrimidines as EGFR L858R/T790M selective inhibitors for NSCLC. Eur J Med Chem. 2017;140:510–527.
  • Wurz RP, Pettus LH, Ashton K, et al. Oxopyrido[2,3-d]pyrimidines as covalent L858R/T790M/mutant selective epidermal growth factor receptor (EGFR) inhibitors. ACS Med Chem Lett. 2015;6:987–992.
  • Yadav IS, Nandekar PP, Shrivastava S, et al. Ensemble docking and molecular dynamics identify Knoevenagel curcumin derivatives with potent anti-EGFR activity. Gene 2014;539:82–90.
  • Sharma VK, Nandekar PP, Sangamwar A, et al. Structure guided design and binding analysis of EGFR inhibiting analogues of erlotinib and AEE788 using ensemble docking, molecular dynamics and MM-GBSA. RSC Adv. 2016;6:65725–65735.
  • Chauhan JS, Dhanda SK, Singla D, et al. QSAR-based models for designing quinazoline/imidazothiazoles/pyrazolopyrimidines based inhibitors against wild and mutant EGFR. PLoS One. 2014;9:e101079.
  • Singh H, Singh S, Singla D, et al. QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest. Biol Direct. 2015;10:10
  • Dhiman K, Agarwal SM. NPred: QSAR classification model for identifying plant based naturally occurring anti-cancerous inhibitors. RSC Adv. 2016;6:49395–49400.
  • Chan BK, Hanan EJ, Bowman KK, et al. Discovery of a noncovalent, mutant-selective epidermal growth factor receptor inhibitor. J Med Chem. 2016;59:9080–9093.
  • Hanan EJ, Eigenbrot C, Bryan MC, et al. Discovery of selective and noncovalent diaminopyrimidine-based inhibitors of epidermal growth factor receptor containing the T790M resistance mutation. J Med Chem. 2014;57:10176–10191.
  • Heald R, Bowman KK, Bryan MC, et al. Noncovalent mutant selective epidermal growth factor receptor inhibitors: a lead optimization case study. J Med Chem. 2015;58:8877–8895.
  • Golbraikh A, Tropsha A. Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection. Mol Divers 2000;5:231–243.
  • Tropsha A. Best practices for QSAR model development, validation, and exploitation. Mol Inform. 2010;29:476–488.
  • Rücker C, Rücker G, Meringer M. y-Randomization and Its Variants in QSPR/QSAR. J Chem Inf Model. 2007;47:2345–2357.
  • Karki RG, Kulkarni VM. Three-dimensional quantitative structure–activity relationship (3D-QSAR) of 3-aryloxazolidin-2-one antibacterials. Bioorg Med Chem. 2001;9:3153–3160.

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