Semisynthetic Flavonoids as GSK-3β Inhibitors: Computational Methods and Enzymatic Assay

Glycogen synthase kinase-3 beta (GSK-3β) plays a crucial role in multiple cellular processes and is implicated in different types of cancers and neurological disorders, including Alzheimer’s disease. Despite extensive efforts to develop novel GSK-3β inhibitors, the discovery of potent and selective lead compounds remains a challenge. In this study, we evaluated the GSK-3β inhibitory potential of semisynthetic flavonoid derivatives, which exhibited sub-micromolar activity. To gain further insights, we employed molecular docking, molecular dynamics simulations, and pharmacokinetic profile predictions. The docking studies revealed that the most potent inhibitor, compound 10, establishes key interactions with the ATP-binding site. Molecular dynamics simulations further confirmed that compound 10 maintains stable interactions with GSK-3β throughout the simulation. Additionally, pharmacokinetic predictions identified compound 3 as a promising candidate for Alzheimer’s disease therapy due to its ability to cross the blood–brain barrier. These findings suggest that, within the studied flavonoid derivatives, these compounds (particularly 10 and 3) hold potential as lead compounds for GSK-3β inhibition. The combination of strong enzymatic inhibition, stable binding interactions, and favorable pharmacokinetic properties highlights their promise for further development in cancer and neurodegenerative disease research.

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Publication Details

Journal
Targets
Published
2025-04-15
DOI
https://doi.org/10.3390/targets3020013
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

Semisynthetic Flavonoids as GSK-3β Inhibitors: Computational Methods and Enzymatic Assay

Pedro Alves Bezerra Morais, J. Silva, Heberth de Paula, Lara Chaves de Freitas Ferreira et al.
1 citations
Targets
Computational Drug Discovery Methods
1.50
article

Semisynthetic Flavonoids as GSK-3β Inhibitors: Computational Methods and Enzymatic Assay

Pedro Alves Bezerra Morais, J. Silva, Heberth de Paula, Lara Chaves de Freitas Ferreira, Juliana F. Vilachã, Valdemar Lacerda, Flávio da Silva Emery, Rayssa Ribeiro, Fernanda Timm Seabra Souza
article en
1 citations

Abstract

Glycogen synthase kinase-3 beta (GSK-3β) plays a crucial role in multiple cellular processes and is implicated in different types of cancers and neurological disorders, including Alzheimer’s disease. Despite extensive efforts to develop novel GSK-3β inhibitors, the discovery of potent and selective lead compounds remains a challenge. In this study, we evaluated the GSK-3β inhibitory potential of semisynthetic flavonoid derivatives, which exhibited sub-micromolar activity. To gain further insights, we employed molecular docking, molecular dynamics simulations, and pharmacokinetic profile predictions. The docking studies revealed that the most potent inhibitor, compound 10, establishes key interactions with the ATP-binding site. Molecular dynamics simulations further confirmed that compound 10 maintains stable interactions with GSK-3β throughout the simulation. Additionally, pharmacokinetic predictions identified compound 3 as a promising candidate for Alzheimer’s disease therapy due to its ability to cross the blood–brain barrier. These findings suggest that, within the studied flavonoid derivatives, these compounds (particularly 10 and 3) hold potential as lead compounds for GSK-3β inhibition. The combination of strong enzymatic inhibition, stable binding interactions, and favorable pharmacokinetic properties highlights their promise for further development in cancer and neurodegenerative disease research.

TargetsVol. 3(2)
Universidade de São Paulo (BR), University of Warwick (GB), Universidade Federal do Espírito Santo (BR), Universidade Federal do ABC (BR)
University of Warwick, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa e Inovação do Espírito Santo
Openalex Percentile: Top 18%
Computational Drug Discovery Methods
1.50
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