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Updated: Jul 26, 2025

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
Published on: May 20, 2020
Computational identification of new TKI as potential noncovalent reversible EGFRL858R/T790M inhibitors: VHTS,
Dorra Abdelmalek1, Fahmi Smaoui2, Fakher Frikha1
1Laboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Abstract:
The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. In this study, we employed a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 50.000 Erlotinib-derived compounds as noncovalent reversible EGFRL858R/T790M inhibitors. Our HTVS work flow leverages include HTVS, SP (Standard Precision) and XP (Extra Precision) docking protocol along with its relative binding free energy calculation, cluster analysis study and ADMET properties. Then we used multiple ns-time scale molecular dynamics (MD) simulations and density functional theory (DFT) precise calculation techniques to elucidate how the bound ligand interact with the complexes conformational states involving motions both proximal and distal to the binding site. Based on glide score and protein-ligand interactions, the highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. A hyperfine analysis of DFT based refinement strategy highly supported their stability by strong intermolecular interactions. Together, our results demonstrate that the virtually screened top retained molecules present the best moieties introduced to Erlotinib. They exhibit interesting pharmacokinetic properties that can act as potent antitumor drug candidates than the lead compound drug and in some extent tackling the drug resistance problem which offer a springboard for further therapeutic experiments and applications.Communicated by Ramaswamy H. Sarma.
Insights
This study screened over 50,000 Erlotinib-derived compounds to find new non-small cell lung cancer treatments. The best candidates show promise as potent antitumor drugs, potentially overcoming drug resistance.
Area of Science:
- Medicinal Chemistry
- Computational Drug Discovery
- Oncology
Background:
- Non-small cell lung cancer (NSCLC) treatment often involves targeting the epidermal growth factor receptor (EGFR) tyrosine kinase.
- Drug resistance, particularly mutations like EGFRL858R/T790M, presents a significant challenge in NSCLC therapy.
Purpose of the Study:
- To identify novel noncovalent reversible EGFRL858R/T790M inhibitors using a high-throughput virtual screening (HTVS) framework.
- To evaluate the potential of Erlotinib-derived compounds as improved antitumor drug candidates for NSCLC.
Main Methods:
- Employed a scalable HTVS framework with a library of over 50,000 Erlotinib-derived compounds.
- Utilized Standard Precision (SP) and Extra Precision (XP) docking, binding free energy calculations, cluster analysis, and ADMET property prediction.
- Performed molecular dynamics (MD) simulations and density functional theory (DFT) calculations to analyze protein-ligand interactions and conformational stability.
Main Results:
- Identified top-scoring molecules with enhanced moieties compared to Erlotinib.
- Selected the highest-scoring molecule for MD simulations, revealing conformational stability and strong intermolecular interactions.
- Demonstrated that screened compounds possess favorable pharmacokinetic properties.
Conclusions:
- Virtually screened compounds exhibit potential as potent antitumor drug candidates for NSCLC.
- These novel inhibitors may offer a strategy to overcome existing drug resistance mechanisms.
- The findings provide a foundation for further therapeutic development and experimental validation.
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