Unraveling potential EGFR kinase inhibitors: Computational screening, molecular dynamics insights, and MMPBSA analysis for targeted cancer therapy development
Muhammad Naseem Khan, Umar Farooq, Aneela Khushal, Tanveer A. Wani, Seema Zargar, Sara Khan
Abstract
EGFR is critical for tumor angiogenesis and cancer progression, but existing treatments like erlotinib face limitations such as acquired resistance and side effects. To address these issues, this study employs structure-based drug design techniques including virtual screening, molecular docking, and molecular dynamics simulations to identify new small molecule inhibitors targeting the EGFR kinase domain.
Introduction
Targeted therapies, in addition to conventional cancer treatments, have gained significant interest in the recent past [1–3]. These therapies mainly focus on important biomolecules that are crucial either for the normal physiological cellular functioning, replication, or tumor development. They have the tendency to bring cytostatic and/or cytotoxic effects on affected cells while reducing the non-specific toxicities linked to radiation or chemotherapy [4].
Materials and method
Protein and small molecule preparation
The three-dimensional crystal structures of the EGFR proteins (PDB ID: 1M17 for the active form and PDB ID: 1XKK for the inactive form) were retrieved from the RCSB Protein Data Bank (https://www.rcsb.org) and opened in Discovery Studio visualizer tool. Upon examination, it was noted that the structures exhibited disruptions attributable to the absence of certain amino acid residues. To rectify this, the structures underwent repair or reconstruction using the SwissModel web tool (https://swissmodel.expasy.org) regarding self-templates. Subsequently, the models were opened in the Discovery Studio visualizer (DSV), where small molecules such as water, and any additional ligand entries occupying EGFR binding sites were removed.
Results and discussion
Preparation of the molecules and molecular docking analysis
The active (PDB ID: 1M17) and inactive (PDB ID: 1XKK) structures of EGFR proteins were retrieved from the protein data bank and visualized using the Discovery Studio Visualizer tool. It was observed that the structures exhibited fractures due to the absence of certain amino acid residues. Subsequently, the structures were repaired or reconstructed using the SwissModel online tool with a self-template.
Acknowledgments
The authors thank the department of Chemistry at COMSATS University Islamabad, Abbottabad Campus for providing lab facilities.
Citation: Khan MN, Farooq U, Khushal A, Wani TA, Zargar S, Khan S (2025) Unraveling potential EGFR kinase inhibitors: Computational screening, molecular dynamics insights, and MMPBSA analysis for targeted cancer therapy development. PLoS One 20(5): e0321500. https://doi.org/10.1371/journal.pone.0321500
Editor: Ahmed A. Al-Karmalawy, University of Mashreq, IRAQ
Received: November 26, 2024; Accepted: March 6, 2025; Published: May 9, 2025
Copyright: © 2025 Khan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This study was financially supported by the Research Supporting Project of King Saud University, Riyadh, Saudi Arabia (grant number RSP2025R357). No additional external funding was received for this study.
Competing interests: The authors have declared that no competing interests exist.
