Background: GSK3-β is a serine/threonine kinase involved in metabolic, inflammatory, oncogenic, and neurological signalling pathways. Methods: This study investigated curcumin and ten structurally similar compounds using an integrated in silico approach combining structural similarity screening, molecular docking, MD simulations, DFT calculations, ADMET/toxicity prediction, and network pharmacology. Results: Molecular docking identified phenothrin (−8.3 kcal/mol), acitretin (−8.0 kcal/mol), and curcumin (−7.5 kcal/mol) as the highest-ranking compounds, which were subsequently subjected to three independent 100-ns MD simulations. MD analyses indicated stable protein–ligand complexes, with acitretin showing a persistent and diverse interaction profile within the GSK3-β binding region. Comparative DFT analysis indicated distinct electronic characteristics among the three compounds, while ADMET profiling highlighted differences in their predicted pharmacokinetic and toxicological properties. Network pharmacology predictions associated acitretin-related targets with PPAR, PI3K-Akt, and other signalling pathways. Conclusion: Overall, acitretin emerged as a computationally prioritised candidate. However, these findings remain computational predictions and require confirmation through experimental GSK3-β inhibition studies.
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Ünaldı et al. (2026) studied this question.
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