Identification of Selisistat Derivatives as SIRT1-3 Inhibitors by in Silico Virtual Screening.

Abstract

Sirtuins family are a Nicotinamide Adenine Dinucleotide (NAD+) dependent histone deacetylase enzyme. Sirtuins have been implicated in the pathogenesis of various diseases including cancer, neurological disorders and metabolic syndromes, hence sirtuins appointed as a promising therapeutic target for diseases, by regulating of its activity by small molecules modulators. The indole containing selisistat (EX-527) and its derivatives set as the most potent and selective SIRT1 inhibitors. Selisistat showed an effective sirtuin inhibition on various cancer cell line, and has reached the clinical trials for endometriosis and Huntington’s disease. In this study a set of selisistat derivatives were designed and virtually studied by means of molecular docking, ADMET, and molecular dynamics (MD) simulations. Two molecules were showed promising virtual binding affinity on the SIRT1-3 proteins. Compound 1 exhibits stronger in silico SIRT1 and SIRT2 affinities than EX-527, whereas compound 8 prefers SIRT3 binding. The ADMET analysis of the virtually active molecules demonstrated an acceptable drug-like profile and desirable pharmacokinetics properties. The MD simulation analysis revealed that compound 1 had significantly better alignment with SIRT1 and SIRT2 proteins than EX-527 according to Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) data, while compound 8 had a perfect alignment and fitting with SIRT3 protein than EX-527.