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Screening approach by a combination of computational and in vitro experiments: identification of fluvastatin sodium as a potential SIRT2 inhibitor.

Authors :
Yang, Jin
Wang, Hanxun
Liu, Jiale
Ma, Enlong
Jin, Xinxin
Li, Yanchun
Ma, Chao
Source :
Journal of Molecular Modeling. Jun2024, Vol. 30 Issue 6, p1-15. 15p.
Publication Year :
2024

Abstract

Background: Sirtuins (SIRTs) are NAD+-dependent deacetylases that play various roles in numerous pathophysiological processes, holding promise as therapeutic targets worthy of further investigation. Among them, the SIRT2 subtype is closely associated with tumorigenesis and malignancies. Dysregulation of SIRT2 activation can regulate the expression levels of related genes in cancer cells, leading to tumor occurrence and metastasis. Methods: In this study, we used computer simulations to screen for novel SIRT2 inhibitors from the FDA database, based on which 10 compounds with high docking scores and good interactions were selected for in vitro anti-pancreatic cancer metastasis testing and enzyme binding inhibition experiments. The results showed that fluvastatin sodium may possess inhibitory activity against SIRT2. Subsequently, fluvastatin sodium was subjected to molecular docking experiments with various SIRT isoforms, and the combined results from Western blotting experiments indicated its potential as a SIRT2 inhibitor. Next, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were performed, revealing the binding mode of fluvastatin sodium at the SIRT2 active site, further validating the stability and interaction of the ligand–protein complex under physiological conditions. Results: Overall, this study provides a systematic virtual screening workflow for the discovery of SIRT2 activity inhibitors, identifies the potential inhibitory effect of fluvastatin sodium as a lead compound on SIRT2, and opens up a new direction for developing highly active and selectively targeted SIRT2 inhibitors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16102940
Volume :
30
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Molecular Modeling
Publication Type :
Academic Journal
Accession number :
178027296
Full Text :
https://doi.org/10.1007/s00894-024-05988-z