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Quantum evaluation and therapeutic activity of (E)-N-(4-methoxyphenyl)-2-(4-(3-oxo-3-phenylprop-1-en-1-yl) phenoxy)acetamide and its modified derivatives against EGFR and VEGFR-2 in the treatment of triple-negative cancer via in silico approach

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Abstract

The most dangerous subtype of breast cancer, triple-negative breast cancer (TNBC), accounts for 25% of all breast cancer-related deaths and 15% of all breast cancer cases. TNBC is distinguished by the lack of immunohistochemical expression of HER2, progesterone receptors, or oestrogen receptors. Although it has been reported that upregulation of EGFR and VEGFR-2 is associated with TNBC progression, no proven effective targeted therapy exists at this time. We used structural bioinformatics methods, including density functional theory, molecular docking, molecular dynamic simulation, pharmacokinetic and drug-likeness models, to identify promising EGFR/VEGFR-2 inhibitors from N-(4-methoxyphenyl)-2-[4-(3-oxo-3-phenylprop-1-en-1-yl) phenoxy] acetamide and six of its modified derivatives in light of the lack of effective targets inhibitor Version 14 of Spartan software was used to analyse density functional theory. The Schrodinger software suite 2018’s Maestro interface was used for the molecular docking analysis, and the admetSAR and swissADME servers were used for drug-likeness and absorption, distribution, metabolism, excretion, and toxicity. All of the compounds showed strong electronic characteristics. Additionally, all of the tested compounds met the ADMET and drug-likeness requirements without a single instance of Lipinski’s rule of five violations. Additionally, the molecules’ levels of affinity for the target proteins varied. The highest binding affinities were demonstrated by the MOLb-VEGFR-2 complex (− 9.925 kcal/mol) and the MOLg-EGFR complex (− 5.032 kcal/mol). The interaction of the molecules in the domain of the EGFR and VEGFR-2 receptors was also better understood through molecular dynamic simulation of the complex.

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Authors and Affiliations

  1. Theoretical and Computational Chemistry Unit, Department of Chemical Sciences, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria

    Nureni Ipinloju & Oluwatoba Emmanuel Oyeneyin

  2. Department of Biochemistry and Molecular Biology, Usmanu Danfodiyo University, Sokoto, Nigeria

    Abdulwasiu Ibrahim

  3. Institute of Education, Science and Technology of Para (IFPA), Campus Abaetetuba, Abaetetuba, Para, Brazil

    Renato Araujo da Costa

  4. GWATAVRI Research and Biotechnology Nigeria Limited, Lagos, Nigeria

    Tawakalit Boluwatife Adigun

  5. Department of Biochemistry, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria

    Samuel Olawale Olubode

  6. Faculty of Medical Laboratory Science, Usmanu DanFodiyo University, Sokoto, Nigeria

    Kehinde Joan Abayomi

  7. Biology Unit, Department of Biological Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria

    Abdulsamad Omotayo Aiyelabegan

  8. Department of Chemical Sciences, Bamidele Olumilua University of Education Science and Technology, Ikere-Ekiti, Ekiti State, Nigeria

    Timothy Oluwaseun Esan

  9. Department of Biochemistry and Molecular Biology, Usmanu Danfodiyo University, Sokoto, Nigeria

    Suleiman Alhaji Muhammad

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  1. Nureni Ipinloju
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Contributions

Conceptualization: N.I and A.I. Introduction and methodology: N.I., A.I., R.A.d.C., A.O.A. and T.B.A. Formal analysis: N.I., A.I., R.A.d.C., T.O.E. and S.O.O. Data curation: N.I., A.I., R.a.d.C., S.O.O. and K.J.A. Writing original draft preparation: N.I., A.I., R.A.d.C., S.O.O. and A.O.A. Writing review and editing: T.O.E., S.A.M. and O.E.O. Supervision: S.A.M. and O.E.O. All authors read and approve the final manuscript.

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Correspondence to Nureni Ipinloju, Abdulwasiu Ibrahim or Oluwatoba Emmanuel Oyeneyin.

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Ipinloju, N., Ibrahim, A., da Costa, R.A. et al. Quantum evaluation and therapeutic activity of (E)-N-(4-methoxyphenyl)-2-(4-(3-oxo-3-phenylprop-1-en-1-yl) phenoxy)acetamide and its modified derivatives against EGFR and VEGFR-2 in the treatment of triple-negative cancer via in silico approach. J Mol Model 29, 159 (2023). https://doi.org/10.1007/s00894-023-05543-2

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