Identification of Novel Scaffolds Against GSK-3β for Targeting Alzheimer’s Disease Through Molecular Modeling Techniques

Alzheimer's disease (AD) is one of the most common causes of dementia in elderly populations. A multifactorial and complex etiology has hindered the establishment of successful disease-modifying and retarding treatments. An important molecular target that has a close link with the disease's pathophysiology is glycogen synthase kinase 3β (GSK-3β). GSK-3β is thought to be an important bridge between amyloid and tau pathologies, the two principle pathogenic hallmarks of the disease. In particular, its kinase activity is thought to be a contributing factor for initiating aberrant tau hyperphosphorylation toward neurodegenerative progression. To identify potential inhibitors for GSK-3β, a pharmacophore-based virtual screening was used on the VITAS-M Lab database, a large database of small molecules. A co-crystal ligand employed as the template allowed the screening of roughly 200,000 compounds. Compounds successfully screened were selected on the basis of the Phase screen score combining vector alignments, volume scores, and site matching parameters. Using a cutoff score of 1.7, 174 compounds were docked using the Glide tool for molecular docking to further identify potential high-affinity binding ligands. Finally, four chemicals with the best binding scores (cutoff Glide GScore values of - 8 kcal/mol) were identified. Among these, 3-(2-oxo-2H-chromen-3-yl)-N-(4-sulfamoylphenyl) benzamide (VL-1) and trimethylsilyl trifluoromethanesulfonate (VL-2) showed strong and stable binding interactions, as evidenced by molecular dynamics simulation (MDS). The results suggest that VL-1 and VL-2 may serve as promising lead compounds for GSK-3β-based anti-AD therapeutics. However, further in vivo mechanistic validation is warrantied to confirm their therapeutic applicability.

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Publication Details

Journal
Cellular and Molecular Neurobiology
Published
2025-08-04
DOI
https://doi.org/10.1007/s10571-025-01568-8
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

Identification of Novel Scaffolds Against GSK-3β for Targeting Alzheimer’s Disease Through Molecular Modeling Techniques

Mohd Wahid, Shafiul Haque, Darin Mansor Mathkor, Faraz Ahmad et al.
1 citations
Cellular and Molecular Neurobiology
Computational Drug Discovery Methods
1.50
article

Identification of Novel Scaffolds Against GSK-3β for Targeting Alzheimer’s Disease Through Molecular Modeling Techniques

Mohd Wahid, Shafiul Haque, Darin Mansor Mathkor, Faraz Ahmad, Harshika Suri
article en
1 citations

Abstract

Alzheimer's disease (AD) is one of the most common causes of dementia in elderly populations. A multifactorial and complex etiology has hindered the establishment of successful disease-modifying and retarding treatments. An important molecular target that has a close link with the disease's pathophysiology is glycogen synthase kinase 3β (GSK-3β). GSK-3β is thought to be an important bridge between amyloid and tau pathologies, the two principle pathogenic hallmarks of the disease. In particular, its kinase activity is thought to be a contributing factor for initiating aberrant tau hyperphosphorylation toward neurodegenerative progression. To identify potential inhibitors for GSK-3β, a pharmacophore-based virtual screening was used on the VITAS-M Lab database, a large database of small molecules. A co-crystal ligand employed as the template allowed the screening of roughly 200,000 compounds. Compounds successfully screened were selected on the basis of the Phase screen score combining vector alignments, volume scores, and site matching parameters. Using a cutoff score of 1.7, 174 compounds were docked using the Glide tool for molecular docking to further identify potential high-affinity binding ligands. Finally, four chemicals with the best binding scores (cutoff Glide GScore values of - 8 kcal/mol) were identified. Among these, 3-(2-oxo-2H-chromen-3-yl)-N-(4-sulfamoylphenyl) benzamide (VL-1) and trimethylsilyl trifluoromethanesulfonate (VL-2) showed strong and stable binding interactions, as evidenced by molecular dynamics simulation (MDS). The results suggest that VL-1 and VL-2 may serve as promising lead compounds for GSK-3β-based anti-AD therapeutics. However, further in vivo mechanistic validation is warrantied to confirm their therapeutic applicability.

Cellular and Molecular NeurobiologyVol. 45(1)
Vellore Institute of Technology University (IN), Jazan University (SA)
Jazan University, King Saud University, Università degli Studi di Torino
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
1.50
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