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Identification of EGFR inhibitors as potential agents for cancer therapy: pharmacophore-based modeling, molecular docking, and molecular dynamics investigations

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Abstract

Context

As a member of a large family of proteins that together regulate various aspects of cell growth and development, the epidermal growth factor receptor (EGFR) is a validated target for the development of new drugs. Herein, we compiled a library of 62 compounds from the PubChem database with similar pharmacophores as osimertinib, which to our knowledge represents the only drug capable of overcoming EGFR-T790M-mutated NSCLC until date. Subsequently, we launched a docking-based virtual screening campaign against the EGFR kinase with the compiled chemical entities. The virtual screen identified 3 hit candidates (CID_126667097, CID_137660592, and CID_137659061) with lower binding energy/higher affinity (− 8.7 kcal/mol, − 8.6 kcal/mol, and − 8.5 kcal/mol, respectively) than the standard osimertinib (− 8.4 kcal/mol). Molecular dynamics metrics such as RMSD, RMSF, ROG, and intermolecular H-bond were used to substantiate the stability of the promising drug candidates at the binding pocket of EGFR after 100,000 ps production run. Overall, our molecular modeling study portrayed CID_126667097, CID_137660592, and CID_137659061 as lead-like drug candidates that may be further developed for the treatment of EGFR-associated cancer disease.

Methods

Molecular docking was conducted with Autodock Vina. A total of 62 compounds were compiled for the docking screen, which were then downloaded in SMILE format and converted to Protein Data Bank (PDB) format using the Openbabel online server. Finally, Gromacs 2022.3 was used to perform MD simulation to substantiate the stability of the hit candidates.

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Authors and Affiliations

  1. Department of Chemical Sciences, Biochemistry Unit, College of Natural and Applied Sciences, Fountain University, Osogbo, Osun State, Nigeria

    Mojeed Ayoola Ashiru & Quadri Kolawole Adisa

  2. Faculty of Basic Medical Sciences, Department of Biochemistry, College of Medicine, University of Lagos, Lagos, Lagos State, Nigeria

    Sherif Olabisi Ogunyemi, Abosede Christina Ajibare, Nsikak Cicerella Cicero-Mfon, Ogechi Augustina Ihekuna, Latifatu Abdulmumin, Musa Oladayo Babalola & Ibrahim Tope Abdulrasaq

  3. Department of Medical Laboratory Technology, Lagos State College of Health Technology, Lagos, Lagos State, Nigeria

    Oluwakemi Rita Temionu, Monsurat Olatoun Jagun & Ayodeji Oluwadamilare Adeyemi

  4. Faculty of Science, Department of Pure & Applied Chemistry, Osun State University, Osogbo, Osun State, Nigeria

    Yemisi Elizabeth Asibor

  5. Faculty of Basic Medical Science, Department of Physiology, University of Lagos, Lagos, Nigeria

    Latifat Bukola Salau

  6. Faculty of Basic Medical Sciences, Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria

    Mariam Omowumi Lawal, Idayat Omotolani Olatunji, Memunat Alake Bankole & Abibat Bisola Daud

  7. Faculty of Physical Sciences, Department of Pure & Industrial Chemistry, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

    Chika Joseph Okorie

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  1. Mojeed Ayoola Ashiru
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Contributions

M.A.A: conceptualization, supervision of laboratory work, writing of draft manuscript, and interpretation of results (review and editing). S.O.O and O.R.T: writing of manuscript (original draft), investigation, and formal analysis. A.C.A and N.C.C: editing of manuscript, investigation, and formal analysis. O.A.I, M.O.J, and L.A: investigation and formal analysis. Q.K.A, Y.E.A, and C.J.O: data curation, software, and visualization. M.O.L, M.O.B, and I.T.A: review and editing of manuscript. L.B.S, I.O.O, M.A.B, and A.B.D: prepared Figs. 1, 2, 3, 4, 5, and 6, writing of manuscript, and software and visualization. A.O.A: review of manuscript, project supervision, editing of final manuscript.

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Correspondence to Ayodeji Oluwadamilare Adeyemi.

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Ashiru, M.A., Ogunyemi, S.O., Temionu, O.R. et al. Identification of EGFR inhibitors as potential agents for cancer therapy: pharmacophore-based modeling, molecular docking, and molecular dynamics investigations. J Mol Model 29, 128 (2023). https://doi.org/10.1007/s00894-023-05531-6

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