Back to Search Start Over

Discovery of Two GSK3β Inhibitors from Sophora flavescens Ait. using Structure-based Virtual Screening and Bioactivity Evaluation.

Authors :
Pan D
Zeng Y
Jiang D
Zhang Y
Wu M
Huang Y
Han M
Jin XJ
Source :
Current computer-aided drug design [Curr Comput Aided Drug Des] 2024 Oct 25. Date of Electronic Publication: 2024 Oct 25.
Publication Year :
2024
Publisher :
Ahead of Print

Abstract

Objective: Kushen (Sophora flavescens Ait.) has a long history of medicinal use in China due to its medicinal values, such as antibacterial, antiviral, and anti-inflammatory. Rapid discovery of the components and the medicinal effects exerted by Kushen will help elucidate the science of Kushen in curing diseases. GSK3β (glycogen synthase kinase-3 beta) is a protein kinase with a wide range of physiological functions, such as antibacterial, antiviral, and anti-inflammatory. The discovery of inhibitors targeting GSK3β from Kushen was not only helpful for the rapid discovery of the components responsible for the efficacy of Kushen but also important for the development of novel drugs.<br />Methods: In this study, the chemical composition of Kushen was extracted from the TMSCP database. Molecular docking, GSK3β enzyme assay, and molecular dynamics simulations were used to discover the GSK3β inhibitors from the chemical composition of Kushen.<br />Results: A total of 113 chemical compositions of Kushen were extracted from the TMSCP database. Molecular docking indicated that 15 chemical compositions of Kushen scored better than -8 kcal/mol against GSK3β. GSK3β enzyme assay demonstrated several inhibitory activities of kushenol I and kushenol F with IC50 values of 7.53 ± 2.55 μM and 4.96 ± 1.29 μM, respectively. Molecular dynamics simulations were used to reveal the interactions of kushenol I and kushenol F with GSK3β from structural and energetic perspectives.<br />Conclusion: Kushenol I and kushenol F could be the material basis for the antibacterial, antiviral, and anti-inflammatory properties of Kushen.<br /> (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Details

Language :
English
ISSN :
1875-6697
Database :
MEDLINE
Journal :
Current computer-aided drug design
Publication Type :
Academic Journal
Accession number :
39473112
Full Text :
https://doi.org/10.2174/0115734099321878241011104241