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International Journal of Zoology and Applied Biosciences Research Article
Predictive QSAR modeling and ligand-based design of novel EGFR kinase inhibitors
Jothi Nagamani M, Cyril Allen Jonathan Winslow, B Devasena, Sowmiya B and Jenifer E
Year : 2025 | Pages: 505-508
Received on: 27/09/2025
Revised on: 22/10/2025
Accepted on: 25/11/2025
Published on: 01/12/2025
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Jothi Nagamani M, Cyril Allen Jonathan Winslow, B Devasena, Sowmiya B and Jenifer E( 2025).
Predictive QSAR modeling and ligand-based design of novel EGFR kinase inhibitors
. International Journal of Zoology and Applied Biosciences, 10( 6), 505-508.
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Abstract
Epidermal growth factor receptor (EGFR) is a clinically validated target for several epithelial cancers, including lung, colorectal, and breast malignancies. However, drug resistance and reduced sensitivity to existing EGFR inhibitors highlight the need for improved chemical scaffolds with enhanced potency. This study integrates ligand-based quantitative structure–activity relationship (QSAR) modeling with in silico screening to design novel EGFR inhibitors. A dataset of 40 reported EGFR tyrosine kinase inhibitors was compiled and evaluated using multiple linear regression (MLR), partial least squares (PLS), and principal component regression (PCR) methods. Descriptor selection was conducted using genetic algorithm (GA) and correlation filtering. Molecular docking was performed to validate binding affinity and interaction patterns within the ATP-binding pocket of EGFR (PDB: 1M17). The final QSAR model exhibited strong statistical performance (R² = 0.89; Q² = 0.84; RMSE = 0.162), indicating high predictive ability. Designed analogues demonstrated superior predicted pIC?? values and displayed stable docking interactions with key residues such as Met793, Thr854, and Asp855. The findings suggest that the ligand-based modeling approach can efficiently guide the design of potent EGFR inhibitors for further optimization and preclinical testing.
Keywords
EGFR kinase, QSAR modeling, Molecular docking, Ligand-based design, Tyrosine kinase inhibitors.
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© The Author(s) 2025. This article is published by International Journal of Zoology and Applied Biosciences under the terms of the Creative Commons Attribution 4.0 International License (creativecommons.org), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
