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Updated: Aug 8, 2025

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
Published on: May 20, 2020
Identifying potential ligand molecules EGFR mediated TNBC targeting the kinase domain-identification of customized
Hima Vyshnavi1, Krishnan Namboori1
1Computational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.
Background And Purpose:
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer in which three hormone receptors are negative. This work aimed at identifying customized potential molecules inhibiting epidermal growth factor receptor (EGFR) by exploring variants using the pharmacogenomics approaches.
Experimental Approach:
The pharmacogenomics approach has been followed to identify the genetic variants across the 1000 genomes continental population. Model proteins for the populations have been designed by including genetic variants in the reported positions. The 3D structures of the mutated proteins have been generated through homology modeling. The kinase domain present in the parent and the model protein molecules has been investigated. The docking study has been performed with the protein molecules against the kinase inhibitors evaluated by the molecular dynamic simulation studies. Molecular evolution has been performed to generate the potential derivatives of these kinase inhibitors suitable for the conserved region of the kinase domain. This study considered variants within the kinase domain as the sensitive region and remaining residues as the conserved region.
Findings/Results:
The results reveal that few kinase inhibitors interact with the sensitive region. Among the derivatives of these kinase inhibitors molecules, the potential kinase inhibitor that interacts with the different population models has been identified.
Conclusions And Implications:
This study encompasses the importance of genetic variants in drug action as well as in the design of customized drugs. This research gives way to designing customized potential molecules inhibiting EGFR by exploring variants using the pharmacogenomics approaches.
Insights
This study used pharmacogenomics to find new drugs targeting epidermal growth factor receptor (EGFR) for triple-negative breast cancer (TNBC). Researchers identified specific drug derivatives that interact with EGFR variants across different populations.
Area of Science:
- Pharmacogenomics
- Computational Biology
- Drug Discovery
Background:
- Triple-negative breast cancer (TNBC) is an aggressive cancer subtype with negative hormone receptor status.
- Targeting the epidermal growth factor receptor (EGFR) is a potential therapeutic strategy for TNBC.
Purpose of the Study:
- To identify customized drug molecules that inhibit EGFR by exploring genetic variants.
- To utilize pharmacogenomics approaches for personalized medicine in TNBC treatment.
Main Methods:
- Identified genetic variants across continental populations using a pharmacogenomics approach.
- Generated 3D protein structures of EGFR variants via homology modeling.
- Performed molecular docking and dynamic simulations of kinase inhibitors against EGFR models.
Main Results:
- Few existing kinase inhibitors effectively interact with the sensitive EGFR variants.
- Identified specific drug derivatives that show promising interaction with EGFR models across diverse populations.
Conclusions:
- Highlights the critical role of genetic variants in drug response and personalized drug design.
- Provides a foundation for developing customized EGFR inhibitors for TNBC patients based on their genetic profiles.
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