Objectives: Numerous tiny Receptor Tyrosine Kinase Inhibitors have been reported as anticancer medications over the past ten years. However, a lot of them lack effectiveness in vivo, selectivity, or don't last long before developing resistance.
Methods: We used molecular modelling research to improve the pharmacophore in order to get beyond these limitations. For the purpose of linking the chemical makeup of pyrazolyl thiazolinone analogues with their anticancer activity, quantitative structure activity relationship (QSAR) investigations in two dimensions (2D) and three dimensions (3D) were carried out. Pyrazolyl thiazolinone pharmacophore's stearic, electronic, and hydrophobic requirements were calculated using 3D QSAR.
Results: By leveraging the findings of QSAR investigations, the pharmacophore was refined and new chemical entities (NCEs) were generated. The r2 and q2 values obtained for the best model No. 4 of 2D QSAR were 0.9244 and 0.8701, respectively. A drug-like pharmacokinetic profile was ensured by studying the binding affinities of proposed NCEs on EGFR-TK using docking studies and estimating their distribution, metabolism, absorption, and excretion (ADME) features.
Conclusion: When statistical significance is closely examined, predictability of the model and its residuals (actual activity minus predicted activity) are found to be close to zero, leading us to draw the conclusion that the logic behind the design of new chemical entities was determined to be sound
