Docking and binding free energy calculations of sirtuin inhibitors

• Robust QSAR models were derived for sirtuin inhibitors acting on Sirt1-3.
• MM-GBSA method showed better agreement with the activity data than docking scores.
• The developed MM-GBSA method represents a time-efficient post-docking filter.
• The best overall performance was observed using the igb = 1 solvation model.
• Promising results were obtained using the fairly new igb = 8 solvation model.

Sirtuins form a unique and highly conserved class of NAD+-dependent lysine deacylases. Among these the human subtypes Sirt1-3 has been implicated in the pathogenesis of numerous diseases such as cancer, metabolic syndromes, viral diseases and neurological disorders. Most of the sirtuin inhibitors that have been identified so far show limited potency and/or isoform selectivity. Here, we introduce a promising method to generate protein-inhibitor complexes of human Sirt1, Sirt2 and Sirt3 by means of ligand docking and molecular dynamics simulations. This method highly reduces the complexity of such applications and can be applied to other protein targets beside sirtuins. To the best of our knowledge, we present the first binding free energy method developed by using a validated data set of sirtuin inhibitors, where both a fair number of compounds (33 thieno[3,2-d]pyrimidine-6-carboxamide derivatives) was developed and tested in the same laboratory and also crystal structures in complex with the enzyme have been reported. A significant correlation between binding free energies derived from MM-GBSA calculations and in vitro data was found for all three sirtuin subtypes. The developed MM-GBSA protocol is computationally inexpensive and can be applied as a post-docking filter in virtual screening to find novel Sirt1-3 inhibitors as well as to prioritize compounds with similar chemical structures for further biological characterization.

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