A Combination of 3D-QSAR Modeling and Molecular Docking Approach for the Discovery of Potential HIF Prolyl Hydroxylase Inhibitors

Mahesh      Kumar Teli; Rajanikant      Golgodu Krishnamurthy

Abstract

Suppression of HIF prolyl hydroxylase (PHD) activity by small molecule inhibitors leads to the stabilization of HIF and offers a potential therapeutic option for treating ischemic disorders. In this study, pharmacophore based QSAR modeling, virtual screening and molecular docking approaches were concurrently used to identify target-specific PHD inhibitors with better ADME properties and to readily minimize false positives and false negatives. A 3D-QSAR based method was used to generate a pharmacophore hypothesis (AAAN). The obtained 3D-QSAR model has an excellent correlation coefficient value (r2 = 0.99), Fisher ratio (F = 386) and exhibited good predictive power (q2 = 0.64). The hypothesis was validated and utilized for chemical database screening and the retrieved compounds were subjected to molecular docking for further refinement. Quantitative AAAN hypothesis comprised three H-bond accepter and one negative ionizable group feature and it give good predictive ability because all the QSAR information it was providing matched with the active site information. The hypothesis was validated and used as a 3D query for database screening. After manual selection, molecular docking and further refinement, based on the molecular interactions of inhibitors with the essential amino acids residues, 12 candidates with good ADME and blood brain barrier permeability values were selected as potential PHD inhibitors.

Keywords: Docking, Pharmacophore model, QSAR, Prolyl hydroxylase inhibitor, Virtual screening, enzymes, iron, oxygen, proline, hypoxia