Exhaustive 3D-QSAR analyses as a computational tool to explore the potency and selectivity profiles of thieno[3,2-d]pyrimidin-4(3H)-one derivatives as PDE7 inhibitors

Abstract

The development of selective ligands binding to specific PDE isoforms represents an urgent need in medicinal chemistry, being a necessary strategy to identify many more drug-like compounds, to be investigated for several therapies. Concerning inflammation, rational design of selective PDE7 inhibitors over PDE4 could lead to derivatives endowed with a better safety profile, showing limited side-effects. In this context, thieno[3,2-d]pyrimidin-4(3H)-one-based compounds have been recently studied as a series of potent phosphodiesterase type 7 (PDE7) inhibitors, most of them being selective over other PDE enzymes, such as PDE4B. This work describes a computational study based on docking calculations followed by Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA), in order to better elucidate the pharmacophore features of this series of PDE7 inhibitors. The results reveal the ligand-based approach as a promising strategy to better investigate the potency and selectivity issues of PDE7 inhibitors. In addition, the results also allowed robust statistical models able to predict the potency and selectivity trend of new analogues prior to synthesis to be obtained.