Integrated computational approaches for identification of potent pyrazole-based glycogen synthase kinase-3β (GSK-3β) inhibitors: 3D-QSAR, virtual screening, docking, MM/GBSA, EC, MD simulation studies.

Abstract

Glycogen synthase kinase-3β (GSK-3β) has emerged as a crucial target due to its substantial contribution in various cellular processes. Dysfunctional GSK-3β activity can lead to ion channel disturbances, sustain abnormal excitability, and contribute to the pathogenesis of epilepsy and other GSK-3β-related disorders. A set of 82 pyrazole analogs was utilized to study its structural features using a three-dimensional quantitative structure-activity relationship (3D-QSAR), virtual screening, molecular docking, and molecular dynamics. The QSAR model, validated using internal and external methods, demonstrated robustness with a high correlation coefficient r²_training = 0.99, cross-validation coefficient q² = 0.79, r²_test = 0.69, and r²_external = 0.74. The "Average of Actives" in the Activity Atlas model identified 17 molecules as active. Subsequent pharmacophore-based virtual screening of 17 actives yielded 70 compounds, which were selected as the prediction set to determine the potential GSK-3β inhibitors. Docking studies pinpointed compound P66 as the promising lead compound, with a docking score of - 10.555 kcal/mol. These findings were further supported by electrostatic potential (ESP), electrostatic complementarity (EC), and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analyses. Furthermore, a 500 ns molecular dynamics (MD) simulation confirmed the structural and conformational stability of the lead complex throughout the simulation period. As a result, this study suggests that compound P66 holds the potential to be a potent lead candidate for the inhibition of GSK-3β, offering a novel therapeutic approach for GSK-3β related disorders, including epilepsy.