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ORIGINAL ARTICLE
Year : 2023  |  Volume : 18  |  Issue : 2  |  Page : 121-137

Identifying potential ligand molecules EGFR mediated TNBC targeting the kinase domain-identification of customized drugs through in silico methods


Computational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

Correspondence Address:
Krishnan Namboori
Computational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Tel: +422-2685592, Fax: 422-2686274
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1735-5362.367792

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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.


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