In Silico Prediction of Potent Pan-Janus Kinase (JAK3) and CYP3A4 Inhibitors Using 2-Imidazopyridine and 2-Aminopyridone Purinones via Computer-Aided Drug Design

Abstract

Abstract In this study, a 3D-QSAR analysis was performed using field-based and atom-based methods with a pharmacophore hypothesis approach to understand and identify the most important features that are associated with the inhibitory activity of JAK3/STAT and CYP3A4. The results for both field-based and atom-based methods showed good performance with R2 values of 0.93 and 0.94, R2 CV values of 0.51 and 0.47 and Q2 values of 0.87 and 0.86, respectively. Additionally, a pharmacophore DHRRR model was developed with a survival score of 5.88 to guide the design of new molecules. This study employed ADMET to predict the pharmacokinetic and pharmaceutical properties of candidate ligands, including solubility, permeability, and metabolic stability, which are critical for drug efficacy and pharmacokinetics. The present investigation aimed to explore the phenomenon of covalent binding between Janus Kinase (JAK3) and ligands, specifically targeting cysteine 909 (Cys909), a crucial player in the treatment of rheumatoid conditions. The findings of this study demonstrate that the establishment of covalent bonds between the ligands and Cys909 significantly enhances the inhibitory activity of JAK3/STAT, thus highlighting the potential therapeutic benefits in the context of rheumatoid treatment. Using molecular dynamics (MD) simulations and MM-GBSA calculations, potentially potent molecules were identified for selective JAK3/STAT inhibition. Finally, retrosynthesis was used to facilitate the synthetic pathway. These findings demonstrate the effectiveness of this computational approach in identifying promising new compounds for the development of JAK3/STAT drugs.