Discovery of Potent Natural-Product-Derived SIRT2 Inhibitors Using Structure- Based Exploration of SIRT2 Pharmacophoric Space Coupled With QSAR Analyses

Abstract

Background: SIRT2 belongs to a class III of Histone Deacetylase (HDAC) and has crucial roles in neurodegeneration and malignancy. Objective: The objective of this study is to discover structurally novel natural-product-derived SIRT2 inhibi-tors. Methods: Structure-based pharmacophore modeling integrated with validated QSAR analysis was implemented to discover structurally novel SIRT2 inhibitors from the natural products database. The targeted QSAR model combined molecular descriptors with structure-based pharmacophore capable of explaining bioactivity varia-tion of structurally diverse SIRT2 inhibitors. Manually built pharmacophore model, validated with receiver operating characteristic curve, and selected using the statistically optimum QSAR equation, was applied as a 3D-search query to mine AnalytiCon Discovery database of natural products. Results: Experimental in vitro testing of highest-ranked hits identified asperphenamate and salvianolic acid B as active SIRT2 inhibitors with IC50 values in low micromolar range. Conclusion: New chemical scaffolds of SIRT2 inhibitors have been identified that could serve as a starting point for lead-structure optimization. © 2021 Bentham Science Publishers.