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.
Authors
- Vincenzo Calderone (ORCID: https://orcid.org/0000-0002-1441-5421)
- Hajar Sirous (ORCID: https://orcid.org/0000-0003-4311-9952)
- Simone Brogi (ORCID: https://orcid.org/0000-0001-9375-6242)
- Morteza Pourfarzam (ORCID: https://orcid.org/0000-0002-9563-8044)
- Kourosh Eslami
- Arman Bigham
Institutions
- University of Pisa (IT)
- Isfahan University of Medical Sciences (IR)
Publication Details
- 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
- Type
- article
- Field-Weighted Citation Impact
- 0.00