In silico pipeline for GSK 3β inhibitor discovery in Alzheimer’s disease using pharmacophore screening, docking, ADME filtering, and MD validation

Abstract Glycogen synthase kinase-3β (GSK-3β) is a key therapeutic target for Alzheimer’s disease, but identifying safe, brain-penetrant inhibitors remains difficult. This study aimed to discover novel CNS-active GSK-3β inhibitors using a rigorous multi-tier computational pipeline. The workflow combined ligand-based and structure-based pharmacophore modeling, virtual screening of the ZINCPharmer database, AutoDock Vina docking, ADME and blood-brain barrier (BBB) filtering with SwissADME, toxicity prediction using ProTox-3.0, and validation by 100-ns molecular dynamics simulations with MM/GBSA and MM/PBSA free energy calculations. Pharmacophore screening with a ≤ 1.0 Å RMSD cutoff identified 1,085 ligand-based and 36 structure-based hits. After docking and developability filtering, two BBB-permeant candidates were prioritized: SB1 , a structure-based hit (predicted LD 50 = 2500 mg/kg, toxicity class 5), and LB1 , a ligand-based hit (predicted LD 50 = 521 mg/kg, toxicity class 4). Molecular dynamics confirmed stable binding for both compounds. MM/GBSA analysis showed favorable binding free energies for SB1 (-27.68 kcal/mol) and LB1 (-25.74 kcal/mol), both surpassing the co-crystallized reference (-8.75 kcal/mol). These findings identify SB1 and LB1 as promising, safe, and brain-penetrant GSK-3β lead compounds for experimental validation in Alzheimer’s disease.