Towards identification of novel inhibitors of EGFR mutants through In- silico approach.

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This study employed molecular docking techniques to identify potential inhibitors against wild-type EGFR and its clinically relevant mutations, including the exon 19 deletion and T790M/L858R resistance mutations. Nine compounds, comprising five irreversible tyrosine kinase inhibitors (TKIs) and four small molecule natural compounds, were systematically screened using CB-dock2 computational tool. The drug-likeness and toxicity of these molecules were also examined based on their ADMET and Toxicity Prediction profiles. Among the tested compounds, Tetrandrine, Dauricine, and Olmutinib exhibited robust binding affinities across both wild-type and mutant EGFR configurations, highlighting their potential as effective inhibitors. These findings align with existing literature, reinforcing the importance of natural compounds and targeted inhibitors in combating EGFR-driven cancers. The integrated approach of combining molecular docking using CB-dock2, ADMET profiling, and Lipinski's rule of five provides a robust framework for preliminary drug candidate screening, potentially accelerating the development of more precise and effective EGFR-targeted therapies. The findings contribute to the growing body of research exploring alternative and more nuanced strategies for inhibiting EGFR-driven oncogenic mechanisms, highlighting the importance of computational methods in identifying novel molecular targets with improved specificity and reduced side effects.

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