Comprehensive structure-based virtual screening of natural products enabling the discovery of new activators of SIRT1

Background and purpose: Sirtuin 1 (SIRT1), a class III histone deacetylase, regulates key signaling pathways associated with health and longevity. Age-related decline in SIRT1 contributes to metabolic, inflammatory, cardiovascular, and neurodegenerative diseases. Although SIRT1-activating compounds (STACs) represent a promising therapeutic strategy, currently available activators show limited potency. This study aimed to identify novel natural SIRT1 activators using hierarchical virtual screening. Experimental approach: The crystal structure of the SIRT1-resveratrol (RSV) complex was utilized to screen 46,797 natural products from the ZINC database against allosteric binding sites. Top-ranked hits were further evaluated by drug-likeness/ADMET filtering, induced-fit docking, MM-GBSA binding free energy calculations, 50 ns molecular dynamics (MD) simulations, extended 100 ns MD simulations, trajectory-based MM-GBSA analyses, and residue scanning. Findings/Results: Eight hits showed better docking scores than RSV. Four candidates, ZINC000005158607, ZINC000014762741, ZINC000014762739, and ZINC000005639632, exhibited stable backbone RMSD profiles (average ≤ 3.5 Å) during the initial MD simulations. Extended 100 ns simulations demonstrated stable RMSD, RMSF, and Rg profiles, together with persistent interactions involving key allosteric residues and residues of the p53-AMC peptide substrate. Trajectory-based MM-GBSA analysis identified ZINC000005158607 as the most favorable candidate (ΔG bind = -44.14 and -34.68 kcal.mol -1 for site 1 and site 2, respectively), followed by ZINC000014762741 and ZINC000014762739. Residue scanning further supported ligand selectivity by confirming the energetic importance of key allosteric residues. Conclusion and implications: ZINC000005158607, ZINC000014762741, and ZINC000014762739 represent promising scaffolds for developing novel SIRT1 activators and warrant further experimental validation for treating age-related diseases.

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Journal
Research in Pharmaceutical Sciences
Published
2026-10-26
DOI
https://doi.org/10.4103/rps.rps_232_25
Primary Topic
Computational Drug Discovery Methods
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article
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article

Comprehensive structure-based virtual screening of natural products enabling the discovery of new activators of SIRT1

Vincenzo Calderone, Hajar Sirous, Simone Brogi, Morteza Pourfarzam et al.
Research in Pharmaceutical Sciences
Computational Drug Discovery Methods
article

Comprehensive structure-based virtual screening of natural products enabling the discovery of new activators of SIRT1

Vincenzo Calderone, Hajar Sirous, Simone Brogi, Morteza Pourfarzam, Kourosh Eslami, Arman Bigham
article en

Abstract

Background and purpose: Sirtuin 1 (SIRT1), a class III histone deacetylase, regulates key signaling pathways associated with health and longevity. Age-related decline in SIRT1 contributes to metabolic, inflammatory, cardiovascular, and neurodegenerative diseases. Although SIRT1-activating compounds (STACs) represent a promising therapeutic strategy, currently available activators show limited potency. This study aimed to identify novel natural SIRT1 activators using hierarchical virtual screening. Experimental approach: The crystal structure of the SIRT1-resveratrol (RSV) complex was utilized to screen 46,797 natural products from the ZINC database against allosteric binding sites. Top-ranked hits were further evaluated by drug-likeness/ADMET filtering, induced-fit docking, MM-GBSA binding free energy calculations, 50 ns molecular dynamics (MD) simulations, extended 100 ns MD simulations, trajectory-based MM-GBSA analyses, and residue scanning. Findings/Results: Eight hits showed better docking scores than RSV. Four candidates, ZINC000005158607, ZINC000014762741, ZINC000014762739, and ZINC000005639632, exhibited stable backbone RMSD profiles (average ≤ 3.5 Å) during the initial MD simulations. Extended 100 ns simulations demonstrated stable RMSD, RMSF, and Rg profiles, together with persistent interactions involving key allosteric residues and residues of the p53-AMC peptide substrate. Trajectory-based MM-GBSA analysis identified ZINC000005158607 as the most favorable candidate (ΔG bind = -44.14 and -34.68 kcal.mol -1 for site 1 and site 2, respectively), followed by ZINC000014762741 and ZINC000014762739. Residue scanning further supported ligand selectivity by confirming the energetic importance of key allosteric residues. Conclusion and implications: ZINC000005158607, ZINC000014762741, and ZINC000014762739 represent promising scaffolds for developing novel SIRT1 activators and warrant further experimental validation for treating age-related diseases.

Research in Pharmaceutical SciencesVol. 21(6)
University of Pisa (IT), Isfahan University of Medical Sciences (IR)
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
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