Integrated Computational Approach for Designing Potent EGFR‐TK Inhibitors: QSAR, Docking, ADMET, and Molecular Dynamics Studies

ABSTRACT The epidermal growth factor receptor (EGFR) regulates cell survival and proliferation, making it a key therapeutic target in cancer. EGFR tyrosine kinase inhibitors (TKIs) block EGFR signaling, preventing uncontrolled cell growth. However, current EGFR‐TKIs face resistance and toxicity issues, necessitating optimized pharmacophores and novel chemical entities (NCEs). This study aimed to develop a 3D quantitative structure–activity relationship (QSAR) model for pharmacophore optimization and to design NCEs with improved properties. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, molecular docking, and molecular dynamics simulations were performed for the NCEs. Methods: Using Schrödinger's Maestro v13.4, QSAR models were built with 42 thiazolyl‐pyrazoline derivatives, yielding a significant model ( R 2 = 0.7880, Q 2 = 0.7341). Forty NCEs with favorable drug‐like properties were selected. The QikProp module assessed ADMET, while Desmond facilitated 100 ns molecular dynamics simulations. NCE 2 emerged as the top candidate with a docking score of –8.178 kcal/mol, showing strong interaction with Leu 788 in the EGFR binding site. Molecular simulations confirmed the stability of the NCE 2–EGFR complex, with root mean square deviation values between 2.4 and 2.8 Å. NCE 2, a novel thiazolyl‐pyrazoline derivative, demonstrated significant EGFR inhibitory activity, stability, and favorable ADMET properties, making it a promising candidate for further development.