Computational approach for building QSAR models for inhibition of HIF-1A

Abstract

QSAR modelling based on several computational approaches has been effectively executed in the fields of pharmaceutical, eco-toxicity of industrial chemicals and materials science, etc. In this article a single optimal descriptor based QSAR models have been built. The therapeutic activity of a set of 105 molecules as inhibitors to HIF-1A (Hypoxia-inducible factor 1-alpha) were analyzed, as HIF is an important enzyme in promoting tumor growth and metastasis. Molecular docking was also implemented to estimate the binding capability of the studied molecules. QSAR model validation parameters and the docking results helped to identify the ligands that have high inhibition capability against HIF-1A. The molecular docking results exhibited that the ligand-105 showed better inhibition for Cα atoms of HIF-1A with a binding energy of −40.1664 kJ/mol. Molecular dynamics (MD) simulations over 50 ns were used to investigate the dynamic behaviour of the apo form and complex form of ligand-105 with HIF-1A. The binding free energy determined from the MD simulation trajectory using the MM/PBSA technique was −94.010+/-19.462 kJ/mol.