Evaluation of a new series of pyrazole derivatives as a potent epidermal growth factor receptor inhibitory activity: QSAR modeling using quantum-chemical descriptors

Pyrazole derivatives correspond to a family of heterocycle molecules with important pharmacological and physiological applications. At present, we perform a density functional theory (DFT) calculations and a quantitative structure-activity relationship (QSAR) evaluation on a series of 1-(4,5-dihydro-1H-pyrazol-1-yl) ethan-1-one and 4,5-dihydro-1H-pyrazole-1-carbothioamide derivatives as an epidermal growth factor receptor (EGFR) inhibitory activity. We thus propose a virtual screening protocol based on a machine-learning study. This theoretical model relates the studied compounds' biological activity to their calculated physicochemical descriptors. Moreover, the linear regression function is used to validate the model via the evaluation of Q²_ext and Q²_cv parameters for external and internal validations, respectively. Our QSAR model shows a good correlation between observed activities IC₅₀ and predicted ones. Our model allows us to mitigate time-consuming problems and waste chemical and biological products in the preclinical phases.