Designing novel inhibitors of epigenetic target — SIRT1
Utilizing Receptor.AI’s hit identification workflow to
target multifunctional nuclear protein
3.2M
compounds
screened
94
hit candidates
selected
5
potent compounds
identified
90 nM
IC50 of the best
compound
01/ Background
- The target is Human Silent Mating Type Information Regulation 2 Homolog 1 (SIRT1).
- SIRT1 deacetylates histones and various other proteins, which are involved in multiple signaling pathways.
02/ Methodology
- 3.2M compounds were prefiltered from 8M stock library based on 16 psychem/druglike filters.
- Using target’s protein data, compounds were subjected to
semi-ligand DTI model scoring. - Evaluated the most relevant ADMET endpoints.
- Performed proteome-wide selectivity scoring.
- ~50K ligands subjected to ArtiDock AI docking and AI rescoring.
- 94 compounds selected for in vitro validation from 1000 best using AI-guided hit candidates selection.
- Experimental validation was performed using a
differential scanning fluorimetry assay.
03/ Results
- 4 compounds demonstrated a significant binding effect.
- 1 hit compound shown 3x selectivity against off-targets.
- This hit was subjected to dose-response test in SIRT-Glo assay.
*Difference between SIRT1-control and
SIRT1-ligand complex melting temperatures
SIRT1-ligand complex melting temperatures
04/ Best Compound
- This compound has shown outstanding nanomolar activity
(IC50 = 90 nM) measured by a functional assay based on the release of the fluorophore probe from acetylated p53-AFC. - This makes it de facto a lead compound.
