Background: Glycogen synthase kinase-3β plays a significant role in the regulation of various
pathological pathways relating to the Central Nervous System (CNS). Dysregulation of Glycogen
synthase kinase 3 (GSK-3) activity gives rise to numerous neuroinflammation and neurodegenerative
related disorders that affect the whole central nervous system.
Objective: By the sequential application of in-silico tools, efforts have been attempted to design the
novel GSK-3β inhibitors.
Method: Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop
the quantitative four featured pharmacophore model comprising two Hydrogen Bond Acceptors
(HBA), one Ring Aromatic (RA), and one Hydrophobe (HY), which were further affirmed by costfunction
analysis, rm2 matrices, internal and external test set validation and Guner-Henry (GH) scoring
analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds,
two potential virtual hits were finalized that were on the basis of fit value, estimated activity and
Lipinski’s violation. The chosen compounds were subjected to dock within the active site of GSK-3β.
Result: Four essential features, i.e., two Hydrogen Bond Acceptors (HBA), one Ring Aromatic (RA), and
one Hydrophobe (HY), were subjected to build the pharmacophoric model and showed good correlation
coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model
was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction
with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the
features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site.
Conclusion: In line with the overhead discussion, and through our stepwise computational approaches,
we have identified novel, structurally diverse glycogen synthase kinase inhibitors.