Integration of pharmacophore-based virtual screening, molecular docking, ADMET analysis, and MD simulation for targeting EGFR: A comprehensive drug discovery study using commercial databases
Abdullah R. Alanzi, Ashaimaa Y. Moussa, Mohammed S. Alsalhi, Tayyab Nawaz, Ijaz Ali
Abstract
The epidermal growth factor receptor (EGFR), a crucial component of cellular signaling pathways, is frequently dysregulated in a range of cancers. EGFR targeting has become a viable approach in the development of anti-cancer medications. This study employs an integrated approach to drug discovery, combining multiple computational methodologies to identify potential EGFR inhibitors.
Introduction
The transmembrane glycoprotein known as epidermal growth factor receptor (EGFR) has an intracellular tyrosine kinase domain in addition to an external EGF binding region. It governs cellular proliferation and signaling pathways [1]. It has been found that EGFR is overexpressed in a variety of cancer cells, including those from the head and neck, breast, esophagus, and lung.
Materials and method
Pharmacophore Modelling
A pharmacophore model can be described as a chemical template that comprises the essential structural features of biologically active compounds. The structural features of an active compound are utilized to generate pharmacophore model which then processed to conduct the screening of large chemical databases [17]. We developed a ligand-based pharmacophore model using the chemical features of a co-crystal ligand (R85) of Epidermal growth factor receptor (PDB ID: 7AEI) by using the Pharmit server [18,19].
Results
Pharmacophore modelling and virtual screening
The pharmacophoric features of R85 ligand involved in the molecular interactions with EGFR protein were used to develop the pharmacophore query model (Fig 2A). There was a total of six features which were used to generate the query model (Fig 2B). The X, Y, and Z coordinates of the features are shown in Table 1.
Discussion
Despite the initial success of EGFR inhibitors, resistance frequently develops over time, limiting their long-term effectiveness. Cancer cells can adapt through a variety of mechanisms, including secondary mutations in the EGFR gene and alternative signaling pathways. To overcome or delay the development of resistance, novel inhibitors with different mechanisms of action are required [16,33].
Acknowledgments
Authors extend their appreciation to researchers supporting project Number (RSPD2024R885) at King Saud University Riyadh Saudi Arabia for supporting this research.
Citation: Alanzi AR, Moussa AY, Alsalhi MS, Nawaz T, Ali I (2024) Integration of pharmacophore-based virtual screening, molecular docking, ADMET analysis, and MD simulation for targeting EGFR: A comprehensive drug discovery study using commercial databases. PLoS ONE 19(12): e0311527. https://doi.org/10.1371/journal.pone.0311527
Editor: Ahmed A. Al-Karmalawy, University of Mashreq, IRAQ
Received: June 5, 2024; Accepted: September 6, 2024; Published: December 9, 2024
Copyright: © 2024 Alanzi 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 article.
Funding: The authors extend their appreciation to the Researchers Supporting Project (RSPD2024R885) at King Saud University, Riyadh, Saudi Arabia, for funding this research.
Competing interests: The authors have declared that no competing interests exist.
