Molecular docking and network pharmacology analysis of the interactions of curcumin and curcumin-like molecules with GSK3-β
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.
Authors
- Nigar Kantarci-Carsibasi (ORCID: https://orcid.org/0000-0003-1013-6668)
- Onur Mert Ünaldı (ORCID: https://orcid.org/0009-0008-9258-7262)
- Elanur Güzenge (ORCID: https://orcid.org/0009-0009-7255-5500)
- Belkıs Atasever-Arslan
- Ceren Yıldırım (ORCID: https://orcid.org/0009-0005-8710-9221)
Institutions
- Üsküdar University (TR)
Publication Details
- Journal
- Archives of Physiology and Biochemistry
- Published
- 2026-10-29
- DOI
- https://doi.org/10.1080/13813455.2026.2752269
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00