ReviewIndian journal of pharmacology2026
Epidermal growth factor receptor as a target enzyme in cancer therapy: Structural and functional insights from crystallography.
Review in Indian journal of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
abstractThe epidermal growth factor receptor (EGFR) is a transmembrane receptor tyrosine kinase that plays a central role in regulating cell growth, differentiation, and survival. In non-small cell lung cancer (NSCLC) and several other malignancies, activating mutations within the EGFR kinase domain lead to persistent receptor activation and uncontrolled downstream signalling. Over the past two decades, X-ray crystallographic studies and structural data deposited in the Protein Data Bank have significantly enhanced our understanding of EGFR activation mechanisms, mutation-driven conformational changes, and inhibitor binding interactions. This review provides a critical evaluation of structural insights obtained from crystal structures of wild-type and mutant EGFR, with particular focus on clinically important mutations such as L858R, T790M, and C797S. These mutations induce specific alterations in activation loop positioning, αC-helix orientation, and ATP-binding pocket architecture, thereby influencing drug binding affinity and therapeutic response. The structural basis for the evolution of EGFR tyrosine kinase inhibitors-from first-generation reversible inhibitors to mutant-selective covalent agents-is discussed in relation to emerging resistance mechanisms. Although structural characterisation has substantially contributed to rational drug design, the ongoing development of resistance mutations highlights the need to integrate crystallographic data with tumour biology and resistance pathways to achieve more durable therapeutic strategies.
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