Abstract:
The hierarchical virtual screening (VS) study, consisting of pharmacophore modelling, docking, and VS of the generated focussed virtual library, has been carried out to identify novel high-affinity and selective β3-AR agonists. The best pharmacophore model comprising one H-bond donor, two hydrophobes, one positive ionizable and one negative ionizable features was developed based on a training set of 51 β3-AR agonists using the pharmacophore generation protocol implemented in Discovery Studio. The model was further validated with the test set, external set, and ability of the pharmacophoric features to complement the active site amino acids of the homology modelled β3-AR developed using MODELLER software. The focussed virtual library was generated using the structure-based insights gained from our earlier reported comprehensive study focussing on the structural basis of β-AR subtype selectivity of representative agonists and antagonists. The hierarchical VS with the sequential use of the best pharmacophore model and homology modelled β3-AR in the screening of the generated focussed library has led to the identification of potential virtual leads as novel high-affinity and selective β3-AR agonists.
