Ligand and structure-based approaches for the identification of SIRT1 activators

Abstract

SIRT1 is a NAD+-dependent deacetylase that involved in various important metabolic pathways. Combined ligand and structure-based approach was utilized for identification of SIRT1 activators. Pharmacophore models were developed using DISCOtech and refined with GASP module of Sybyl X software. Pharmacophore models were composed of two hydrogen bond acceptor (HBA) atoms, two hydrogen bond donor (HBD) sites and one hydrophobic (HY) feature. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner–Henry (GH) scoring methods. Model-2 was selected as best model among the model 1–3, based on ROC and GH score value, and found reliable in identification of SIRT1 activators. Model-2 (3D search query) was searched against Zinc database. Several compounds with different chemical scaffold were retrieved as hits. Currently, there is no experimental SIRT1 3D structure available, therefore, we modeled SIRT1 protein structure using homology modeling. Compounds with Qfit value of more than 86 were selected for docking study into the SIRT1 homology model to explore the binding mode of retrieved hits in the active allosteric site. Finally, in silico ADMET prediction study was performed with two best docked compounds. Combination of ligand and structurebased modeling methods identified active hits, which may be good lead compounds to develop novel SIRT1 activators.