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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecular docking and network pharmacology analysis of the interactions of curcumin and curcumin-like molecules with GSK3-β

Nigar Kantarci-Carsibasi, Onur Mert Ünaldı, Elanur Güzenge, Belkıs Atasever-Arslan et al.
3 links
Archives of Physiology and Biochemistry
Computational Drug Discovery Methods
article

Molecular docking and network pharmacology analysis of the interactions of curcumin and curcumin-like molecules with GSK3-β

Nigar Kantarci-Carsibasi, Onur Mert Ünaldı, Elanur Güzenge, Belkıs Atasever-Arslan, Ceren Yıldırım
article en

Abstract

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.

Archives of Physiology and Biochemistry
Üsküdar University (TR)
Good health and well-being
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon