Skip to content
2000
image of Integrated Computational and Experimental Discovery of a Promising Xanthine Derivative with Anticancer Potential Targeting EGFR

Abstract

Introduction

Epidermal Growth Factor Receptor (EGFR) is a well-established therapeutic target in cancer treatment. In this study, a novel N-phenylacetamide derivative of theobromine, designated as T-1-PA, was designed as a potential semisynthetic EGFR inhibitor.

Methods

The 3D structure, stability, and electronic reactivity of T-1-PA were determined using Density Functional Theory (DFT) analyses. Molecular docking, molecular dynamics (MD) simulations, Molecular Mechanics Generalized Born Surface Area (MM-GBSA), Protein–Ligand Interaction Profiler (PLIP), and Principal Component Analysis of Trajectories (PCAT) were employed to evaluate the binding affinity and inhibitory potential of T-1-PA against EGFR. Computational ADMET profiling was conducted to predict drug-likeness and safety. Subsequently, T-1-PA was semisynthesized and subjected to in vitro biological evaluation.

Results

Computational analyses demonstrated a strong binding affinity of T-1-PA to EGFR. The compound exhibited favorable ADMET properties. In vitro assays revealed potent EGFR inhibition with an IC of 0.736 ± 0.005 μM. T-1-PA also inhibited the proliferation of HepG2 and MCF7 cancer cell lines with IC values of 0.88 ± 0.01 μM and 1.13 ± 0.01 μM, respectively. Flow cytometry analysis indicated induction of apoptosis and G1 phase cell cycle arrest in HepG2 cells. Additionally, T-1-PA significantly impaired HepG2 cell migration and wound-healing capacity.

Discussion

The results validate the computational predictions and highlight the anticancer potential of T-1-PA through EGFR inhibition and antiproliferative activity. The compound's favorable pharmacokinetic and safety profiles further support its therapeutic promise.

Conclusion

T-1-PA is a promising semisynthetic compound with selective antiproliferative activity mediated via EGFR inhibition. These findings encourage further preclinical investigation of T-1-PA as a novel candidate for EGFR-targeted cancer therapy.

Loading

Article metrics loading...

/content/journals/ccdt/10.2174/0115680096363027250731042338
2025-10-01
2025-12-24
Loading full text...

Full text loading...

References

  1. Yang Z. Gu J.M. Ma Q.Y. Xue N. Shi X.W. Wang L. Zhang K. Wang Y.B. Cao D.Y. Guo R. Xing R.J. Design, synthesis and antitumor activity of aromatic urea-quinazolines. Future Med. Chem. 2019 11 21 2821 2830 10.4155/fmc‑2019‑0220 31510797
    [Google Scholar]
  2. Hausman D.M. What Is Cancer? Perspect. Biol. Med. 2019 62 4 778 784 10.1353/pbm.2019.0046 31761807
    [Google Scholar]
  3. El-Sayed M.A.A. El-Husseiny W.M. Abdel-Aziz N.I. El-Azab A.S. Abuelizz H.A. Abdel-Aziz A.A.M. Synthesis and biological evaluation of 2-styrylquinolines as antitumour agents and EGFR kinase inhibitors: Molecular docking study. J. Enzyme Inhib. Med. Chem. 2018 33 1 199 209 10.1080/14756366.2017.1407926 29251017
    [Google Scholar]
  4. Lee Y.T. Tan Y.J. Oon C.E. Molecular targeted therapy: Treating cancer with specificity. Eur. J. Pharmacol. 2018 834 188 196 10.1016/j.ejphar.2018.07.034 30031797
    [Google Scholar]
  5. Harari P.M. Epidermal growth factor receptor inhibition strategies in oncology. Endocr. Relat. Cancer 2004 11 4 689 708 10.1677/erc.1.00600 15613446
    [Google Scholar]
  6. Zhang Y. Zheng G. Fu T. Hong J. Li F. Yao X. Xue W. Zhu F. The binding mode of vilazodone in the human serotonin transporter elucidated by ligand docking and molecular dynamics simulations. Phys. Chem. Chem. Phys. 2020 22 9 5132 5144 10.1039/C9CP05764A 32073004
    [Google Scholar]
  7. Normanno N. De Luca A. Bianco C. Strizzi L. Mancino M. Maiello M.R. Carotenuto A. De Feo G. Caponigro F. Salomon D.S. Epidermal growth factor receptor (EGFR) signaling in cancer. Gene 2006 366 1 2 16 10.1016/j.gene.2005.10.018 16377102
    [Google Scholar]
  8. Ayati A. Moghimi S. Salarinejad S. Safavi M. Pouramiri B. Foroumadi A. A review on progression of epidermal growth factor receptor (EGFR) inhibitors as an efficient approach in cancer targeted therapy. Bioorg. Chem. 2020 99 103811 10.1016/j.bioorg.2020.103811 32278207
    [Google Scholar]
  9. Wheeler D.L. Dunn E.F. Harari P.M. Understanding resistance to EGFR inhibitors—impact on future treatment strategies. Nat. Rev. Clin. Oncol. 2010 7 9 493 507 10.1038/nrclinonc.2010.97 20551942
    [Google Scholar]
  10. Kapri A. Pant S. Gupta N. Nain S. Recent advances in the biological significance of xanthine and its derivatives: a review. Pharm. Chem. J. 2022 56 4 461 474 10.1007/s11094‑022‑02661‑8
    [Google Scholar]
  11. Kapri A. Gupta N. Nain S. Recent advances in the synthesis of xanthines: A short review. Scientifica (Cairo) 2022 2022 1 24 10.1155/2022/8239931 36398136
    [Google Scholar]
  12. Singh N. Shreshtha A.K. Thakur M.S. Patra S. Xanthine scaffold: Scope and potential in drug development. Heliyon 2018 4 10 e00829 10.1016/j.heliyon.2018.e00829 30302410
    [Google Scholar]
  13. Smit H.J. Theobromine and the pharmacology of cocoa. Handb. Exp. Pharmacol. 2011 200 200 201 234 10.1007/978‑3‑642‑13443‑2_7 20859797
    [Google Scholar]
  14. Beaudoin M.S. Graham T.E. Methylxanthines and human health: Epidemiological and experimental evidence. Handb. Exp. Pharmacol. 2011 200 200 509 548 10.1007/978‑3‑642‑13443‑2_21 20859811
    [Google Scholar]
  15. Sugimoto N. Miwa S. Hitomi Y. Nakamura H. Tsuchiya H. Yachie A. Theobromine, the primary methylxanthine found in Theobroma cacao, prevents malignant glioblastoma proliferation by negatively regulating phosphodiesterase-4, extracellular signal-regulated kinase, Akt/mammalian target of rapamycin kinase, and nuclear factor-kappa B. Nutr. Cancer 2014 66 3 419 423 10.1080/01635581.2013.877497 24547961
    [Google Scholar]
  16. Barcz E. Sommer E. Sokolnicka I. Gawrychowski K. Roszkowska-Purska K. Janik P. Skopinska-Rَzewska, E. The influence of theobromine on angiogenic activity and proangiogenic cytokines production of human ovarian cancer cells. Oncol. Rep. 1998 5 2 517 520 10.3892/or.5.2.517 9468592
    [Google Scholar]
  17. Abou-Zied H.A. Youssif B.G.M. Mohamed M.F.A. Hayallah A.M. Abdel-Aziz M. EGFR inhibitors and apoptotic inducers: Design, synthesis, anticancer activity and docking studies of novel xanthine derivatives carrying chalcone moiety as hybrid molecules. Bioorg. Chem. 2019 89 102997 10.1016/j.bioorg.2019.102997 31136902
    [Google Scholar]
  18. Hisham M. Youssif B.G.M. Osman E.E.A. Hayallah A.M. Abdel-Aziz M. Synthesis and biological evaluation of novel xanthine derivatives as potential apoptotic antitumor agents. Eur. J. Med. Chem. 2019 176 117 128 10.1016/j.ejmech.2019.05.015 31108261
    [Google Scholar]
  19. Elkaeed E.B. Elkady H. Khattab A.M. Yousef R.G. Al-ghulikah H.A. Husein D.Z. Ibrahim I.M. Elkady M.A. Metwaly A.M. Eissa I.H. Integrated in silico and in vitro exploration of the anti-VEGFR-2 activities of a semisynthetic xanthine alkaloid inhibiting breast cancer. PLoS One 2025 20 1 e0316146 10.1371/journal.pone.0316146 39869618
    [Google Scholar]
  20. Gandin V. Ferrarese A. Dalla Via M. Marzano C. Chilin A. Marzaro G. Targeting kinases with anilinopyrimidines: Discovery of N-phenyl-N’-[4-(pyrimidin-4-ylamino)phenyl]urea derivatives as selective inhibitors of class III receptor tyrosine kinase subfamily. Sci. Rep. 2015 5 1 16750 10.1038/srep16750 26568452
    [Google Scholar]
  21. Liu Y. Gray N.S. Rational design of inhibitors that bind to inactive kinase conformations. Nat. Chem. Biol. 2006 2 7 358 364 10.1038/nchembio799 16783341
    [Google Scholar]
  22. Sobh E.A. Dahab M.A. Elkaeed E.B. Alsfouk B.A. Ibrahim I.M. Metwaly A.M. Eissa I.H. A novel thieno[2,3‐ d]pyrimidine derivative inhibiting vascular endothelial growth factor receptor‐2: A story of computer‐aided drug discovery. Drug Dev. Res. 2023 84 6 1247 1265 10.1002/ddr.22083 37232504
    [Google Scholar]
  23. Eissa I.H. Yousef R.G. Elkady H. Alsfouk A.A. Alsfouk B.A. Husein D.Z. Ibrahim I.M. Elkaeed E.B. Metwaly A.M. A New anticancer semisynthetic theobromine derivative targeting egfr protein: CADDD study. Life (Basel) 2023 13 1 191 10.3390/life13010191 36676140
    [Google Scholar]
  24. Eissa I.H. Yousef R.G. Elkady H. Elkaeed E.B. Alsfouk A.A. Husein D.Z. Ibrahim I.M. Radwan M.M. Metwaly A.M. A theobromine derivative with anticancer properties targeting vegfr‐2: emisynthesis, in silico and in vitro studies. ChemistryOpen 2023 12 10 e202300066 10.1002/open.202300066 37803417
    [Google Scholar]
  25. Eissa I.H. Yousef R.G. Elkaeed E.B. Alsfouk A.A. Husein D.Z. Ibrahim I.M. El-Mahdy H.A. Elkady H. Metwaly A.M. Computer-assisted drug discovery of a novel theobromine derivative as an egfr protein-targeted apoptosis inducer. Evol. Bioinform. Online 2023 19 11769343231217916 10.1177/11769343231217916 38046652
    [Google Scholar]
  26. Eissa I.H. New apoptotic anti-triple-negative breast cancer theobromine derivative inhibiting EGFRWT and EGFR(T790M): in silico and in vitro evaluation. Mol. Divers. 2023
    [Google Scholar]
  27. Eissa I.H. Yousef G. A new anticancer derivative of the natural alkaloid, theobromine, as an EGFR inhibitor and apoptosis inducer. Theor. Chem. Acc. 2023 143 1 1 10.1007/s00214‑023‑03071‑z
    [Google Scholar]
  28. Eissa I.H. Yousef R.G. Elkady H. Elkaeed E.B. Husein D.Z. Ibrahim I.M. Alsfouk B.A. Doghish A.S. El-Mahdy H.A. Kenawy A.M. El-Deeb N. Metwaly A.M. New theobromine derivative as apoptotic anti-triple-negative breast cancer targeting EGFR protein: CADD story. J. Mol. Struct. 2023 1294 136336 10.1016/j.molstruc.2023.136336
    [Google Scholar]
  29. Eissa I.H. Yousef R.G. Elkaeed E.B. Alsfouk A.A. Husein D.Z. Ibrahim I.M. Alesawy M.S. Elkady H. Metwaly A.M. Anticancer derivative of the natural alkaloid, theobromine, inhibiting EGFR protein: Computer-aided drug discovery approach. PLoS One 2023 18 3 e0282586 10.1371/journal.pone.0282586 36893122
    [Google Scholar]
  30. Husein D.Z. Hassanien R. Khamis M.J.R.a. Cadmium oxide nanoparticles/graphene composite: Synthesis, theoretical insights into reactivity and adsorption study. RSC Adv. 2021 11 43 27027 27041 10.1039/D1RA04754J
    [Google Scholar]
  31. Suleimen Y.M. Jose R.A. Mamytbekova G.K. Suleimen R.N. Ishmuratova M.Y. Dehaen W. Alsfouk B.A. Elkaeed E.B. Eissa I.H. Metwaly A.M. Isolation and in silico inhibitory potential against SARS-COV-2 rna polymerase of the rare kaempferol 3-O-(6″-O-acetyl)-Glucoside from Calligonum tetrapterum. Plants 2022 11 15 2072 10.3390/plants11152072 35956550
    [Google Scholar]
  32. Abraham M.J. Murtola T. Schulz R. Pلll, S.; Smith, J. C.; Hess, B.; Lindahl, E. J. S. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015 1–2 19 25 10.1016/j.softx.2015.06.001
    [Google Scholar]
  33. Valdés-Tresanco M.S. Valdés-Tresanco M.E. Valiente P.A. Moreno E. gmx_MMPBSA: A new tool to perform end-state free energy calculations with GROMACS. J. Chem. Theory Comput. 2021 17 10 6281 6291 10.1021/acs.jctc.1c00645 34586825
    [Google Scholar]
  34. Amadei A. Linssen A.B.M. Berendsen H.J.C. Essential dynamics of proteins. Proteins 1993 17 4 412 425 10.1002/prot.340170408 8108382
    [Google Scholar]
  35. Papaleo E. Mereghetti P. Fantucci P. Grandori R. De Gioia L. Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: The myoglobin case. J. Mol. Graph. Model. 2009 27 8 889 899 10.1016/j.jmgm.2009.01.006 19264523
    [Google Scholar]
  36. Metwaly A.M. Elwan A. El-Attar A.A.M.M. Al-Rashood S.T. Eissa I.H. Structure-based virtual screening, docking, admet, molecular dynamics, and mm-pbsa calculations for the discovery of potential natural SARS-CoV-2 helicase inhibitors from the traditional chinese medicine. J. Chem. 2022 2022 1 23 10.1155/2022/7270094
    [Google Scholar]
  37. Mohamed A.R. Georgey H.H. George R.F. El-Eraky W.I. Saleh D.O. Abdel Gawad N.M. Identification of some novel xanthine-based derivatives with bronchodilator activity. Future Med. Chem. 2017 9 15 1731 1747 10.4155/fmc‑2017‑0092 28871831
    [Google Scholar]
  38. Eissa I.H. El-Helby A.G.A. Mahdy H.A. Khalifa M.M. Elnagar H.A. Mehany A.B.M. Metwaly A.M. Elhendawy M.A. Radwan M.M. ElSohly M.A. El-Adl K. Discovery of new quinazolin-4(3H)-ones as VEGFR-2 inhibitors: Design, synthesis, and anti-proliferative evaluation. Bioorg. Chem. 2020 105 104380 10.1016/j.bioorg.2020.104380 33128967
    [Google Scholar]
  39. Alley M.C. Scudiero D.A. Monks A. Hursey M.L. Czerwinski M.J. Fine D.L. Abbott B.J. Mayo J.G. Shoemaker R.H. Boyd M.R. Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay. Cancer Res. 1988 48 3 589 601 3335022
    [Google Scholar]
  40. Metwaly A. M. Abd-El-Azim H. Zewail M. Alsfouk A. A. Elkaeed E. B. Eissa I. H. Chitosomal encapsulation enhances the anticancer efficacy of a theobromine analogue: An integrated in sil-ico and in vitro study. J. Computat Biophys. Chem. 2025 10.1142/S2737416524500716
    [Google Scholar]
  41. Wlodkowic D. Skommer J. Darzynkiewicz Z. Flow cytometry-based apoptosis detection. Methods Mol. Biol. 2009 559 19 32 10.1007/978‑1‑60327‑017‑5_2 19609746
    [Google Scholar]
  42. Rodriguez L.G. Wu X. Guan J.L. Wound-healing assay. Methods Mol. Biol. 2005 294 23 29 15576902
    [Google Scholar]
  43. Zhu J.Y. Liu Q. Jiang X.N. Zheng X.H. Wang L. Hao Q. Wang C.S. From bonds to interactions: Comprehensive molecular characterization via polarizable bond-dipole approach. Phys. Chem. Chem. Phys. 2023 25 43 29867 29880 10.1039/D3CP04060G 37888898
    [Google Scholar]
  44. Franco-Pérez M. Gلzquez, J.L. Electronegativities of pauling and mulliken in density functional theory. J. Phys. Chem. A 2019 123 46 10065 10071 10.1021/acs.jpca.9b07468 31670960
    [Google Scholar]
  45. Pal R. Chattaraj P.K. Chemical reactivity from a conceptual density functional theory perspective. J. Indian Chem. Soc. 2021 98 1 100008 10.1016/j.jics.2021.100008
    [Google Scholar]
  46. dos Santos Nascimento I.J. de Moura R.O. Molecular dynamics simulations in drug discovery. Mini Rev. Med. Chem. 2024 24 11 1061 1062 10.2174/138955752411240402134719 39004837
    [Google Scholar]
  47. De Vivo M. Masetti M. Bottegoni G. Cavalli A. Role of molecular dynamics and related methods in drug discovery. J. Med. Chem. 2016 59 9 4035 4061 10.1021/acs.jmedchem.5b01684 26807648
    [Google Scholar]
  48. Salentin S. Schreiber S. Haupt V.J. Adasme M.F. Schroeder M. PLIP: Fully automated protein–ligand interaction profiler. Nucleic Acids Res. 2015 43 W1 W443 W447 10.1093/nar/gkv315 25873628
    [Google Scholar]
  49. Desdouits N. Nilges M. Blondel A. Principal component analysis reveals correlation of cavities evolution and functional motions in proteins. J. Mol. Graph. Model. 2015 55 13 24 10.1016/j.jmgm.2014.10.011 25424655
    [Google Scholar]
  50. Daidone I. Amadei A. Essential dynamics: Foundation and applications. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2012 2 5 762 770 10.1002/wcms.1099
    [Google Scholar]
  51. David C.C. Jacobs D.J. Principal component analysis: A method for determining the essential dynamics of proteins. Methods Mol. Biol. 2014 1084 193 226 10.1007/978‑1‑62703‑658‑0_11 24061923
    [Google Scholar]
  52. Lipinski C.A. Lombardo F. Dominy B.W. Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1. Adv. Drug Deliv. Rev. 2001 46 1-3 3 26 10.1016/S0169‑409X(00)00129‑0 11259830
    [Google Scholar]
  53. Kruhlak N.L. Benz R.D. Zhou H. Colatsky T.J. (Q)SAR modeling and safety assessment in regulatory review. Clin. Pharmacol. Ther. 2012 91 3 529 534 10.1038/clpt.2011.300 22258468
    [Google Scholar]
  54. Chuang K.V. Gunsalus L.M. Keiser M.J. Learning molecular representations for medicinal chemistry. Miniperspective. J. Med. Chem. 2020 63 16 8705 8722 10.1021/acs.jmedchem.0c00385 32366098
    [Google Scholar]
  55. Idakwo G. Luttrell J. Chen M. Hong H. Zhou Z. Gong P. Zhang C. A review on machine learning methods for in silico> toxicity prediction. J. Environ. Sci. Health Part C Environ. Carcinog. Ecotoxicol. Rev. 2018 36 4 169 191 10.1080/10590501.2018.1537118 30628866
    [Google Scholar]
  56. Graham R.P. Treece A.L. Lindeman N.I. Vasalos P. Shan M. Jennings L.J. Rimm D.L. Worldwide frequency of commonly detected EGFR mutations. Arch. Pathol. Lab. Med. 2018 142 2 163 167 10.5858/arpa.2016‑0579‑CP 29106293
    [Google Scholar]
  57. Kobayashi S. Canepa H.M. Bailey A.S. Nakayama S. Yamaguchi N. Goldstein M.A. Huberman M.S. Costa D.B. Compound EGFR mutations and response to EGFR tyrosine kinase inhibitors. J. Thorac. Oncol. 2013 8 1 118 122 10.1097/JTO.0b013e3182781e35 23242437
    [Google Scholar]
  58. Zaryouh H. De Pauw I. Baysal H. Peeters M. Vermorken J.B. Lardon F. Wouters A. Recent insights in the PI3K/Akt pathway as a promising therapeutic target in combination with EGFR‐targeting agents to treat head and neck squamous cell carcinoma. Med. Res. Rev. 2022 42 1 112 155 10.1002/med.21806 33928670
    [Google Scholar]
  59. Hamilton E. Infante J.R. Targeting CDK4/6 in patients with cancer. Cancer Treat. Rev. 2016 45 129 138 10.1016/j.ctrv.2016.03.002 27017286
    [Google Scholar]
  60. Jonkman J.E.N. Cathcart J.A. Xu F. Bartolini M.E. Amon J.E. Stevens K.M. Colarusso P. An introduction to the wound healing assay using live-cell microscopy. Cell Adhes. Migr. 2014 8 5 440 451 10.4161/cam.36224 25482647
    [Google Scholar]
  61. Bruno A. Costantino G. Sartori L. Radi M. The in silico drug discovery toolbox: applications in lead discovery and optimization. Curr. Med. Chem. 2019 26 21 3838 3873 10.2174/0929867324666171107101035 29110597
    [Google Scholar]
  62. Talele T. Khedkar S. Rigby A. Successful applications of computer aided drug discovery: Moving drugs from concept to the clinic. Curr. Top. Med. Chem. 2010 10 1 127 141 10.2174/156802610790232251 19929824
    [Google Scholar]
  63. Shaker B. Ahmad S. Lee J. Jung C. Na D. in silico methods and tools for drug discovery. Comput. Biol. Med. 2021 137 104851 10.1016/j.compbiomed.2021.104851 34520990
    [Google Scholar]
  64. Macalino S.J.Y. Gosu V. Hong S. Choi S. Role of computer-aided drug design in modern drug discovery. Arch. Pharm. Res. 2015 38 9 1686 1701 10.1007/s12272‑015‑0640‑5 26208641
    [Google Scholar]
  65. Metwaly A.M. El-Fakharany E.M. Alsfouk A.A. Ibrahim I.M. Elkaeed E.B. Eissa I.H. Integrated study of Quercetin as a potent SARS-CoV-2 RdRp inhibitor: Binding interactions, MD simulations, and in vitro assays. PLoS One 2024 19 12 e0312866 10.1371/journal.pone.0312866 39625895
    [Google Scholar]
  66. Ahmed M.M. Esmail M.E-F. Aisha A.A. Ibrahim M.I. Eslam B.E. Ibrahim H.E. Integrated in silico and in vitro studies of rutin’s potential against sars-cov-2 through the inhibition of the RNA-dependent RNA Polymerase. Curr. Med. Chem. 2025 32 1 27
    [Google Scholar]
  67. Metwaly A.M. El-Fakharany E.M. Alsfouk A.A. Ibrahim I.M. Mostafa A.E. Elkaeed E.B. Eissa I.H. Comprehensive structural and functional analysis of Patuletin as a potent inhibitor of SARS-CoV-2 targeting the RNA-dependent RNA polymerases. J. Mol. Struct. 2024 1311 138424 10.1016/j.molstruc.2024.138424
    [Google Scholar]
  68. Metwaly A. Saleh M.M. Alsfouk A. Ibrahim I.M. Abd-Elraouf M. Elkaeed E. Elkady H. Eissa I. in silico> and in vitro evaluation of the anti-virulence potential of patuletin, a natural methoxy flavone, against Pseudomonas aeruginosa. PeerJ 2024 12 e16826 10.7717/peerj.16826 38313021
    [Google Scholar]
  69. Metwaly A.M. Saleh M.M. Alsfouk B.A. Ibrahim I.M. Abd-Elraouf M. Elkaeed E.B. Eissa I.H. Anti-virulence potential of patuletin, a natural flavone, against Staphylococcus aureus: in vitro and in silico> investigations. Heliyon 2024 10 2 e24075 10.1016/j.heliyon.2024.e24075 38293404
    [Google Scholar]
  70. Yousef R.G. Elwan A. Gobaara I.M.M. Mehany A.B.M. Eldehna W.M. El-Metwally S.A.A. Alsfouk B. Elkaeed E.B. Metwaly A.M. Eissa I.H. Anti-cancer and immunomodulatory evaluation of new nicotinamide derivatives as potential VEGFR-2 inhibitors and apoptosis inducers: in vitro and in silico> studies. J. Enzyme Inhib. Med. Chem. 2022 37 1 2206 2222 10.1080/14756366.2022.2110868 35980113
    [Google Scholar]
  71. Elkaeed E.B. Yousef R.G. Elkady H. Alsfouk A.A. Husein D.Z. Ibrahim I.M. Metwaly A.M. Eissa I.H. New anticancer theobromine derivative targeting EGFRWT and EGFRT790M: Design, semi-synthesis, in silico, and in vitro anticancer studies. Molecules 2022 27 18 5859 10.3390/molecules27185859 36144596
    [Google Scholar]
  72. Metwaly A.M. Abdel-Raoof A.M. Alattar A.M. El-Zomrawy A.A. Ashmawy A.M. Metwally M.G. Abu-Saied M.A. Lotfy A.M. Alsfouk B.A. Elkaeed E.B. Eissa I.H. Preparation and characterization of patuletin-loaded chitosan nanoparticles with improved selectivity and safety profiles for anticancer applications. J. Chem. 2023 2023 1 11 10.1155/2023/6684015
    [Google Scholar]
/content/journals/ccdt/10.2174/0115680096363027250731042338
Loading
/content/journals/ccdt/10.2174/0115680096363027250731042338
Loading

Data & Media loading...

Supplements


  • Article Type:
    Research Article
Keywords: Xanthine ; Anti-cancer ; EGFR inhibition ; MD simulations ; DFT ; PCAT
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test