Ligand and Structure Based Models for the Identification of Beta 2 Adrenergic Receptor Antagonists.

Abstract

Ligand bound beta 2 adrenergic receptor (β2AR) crystal structures are in use for screening of compound libraries for identifying inducers and blockers. However, in case of G protein coupled receptors (GPCR), docking and binding energy (BE) calculations are not enough to discriminate agonist and antagonists. Absence of a reliable model for discriminating β2AR antagonist is still a major hurdle. Docking of known antagonists and agonists into activated and ground state β2AR revealed several key intermolecular interactions and H-bonding patterns, which in combination, emerged as a model for prediction of antagonists. Present study identifies an alternative binding orientation, within the binding pocket, for blockers and a minimum grid size to lessen the false positive predictions. Cluster analysis revealed structural variability among the antagonists and a conserved pattern in case of agonists. A combination of docking and structure activity relationship (SAR) model reliably discriminated antagonists. Based on key intermolecular interactions, a set of agonists and antagonists useful to SAR, quantitative structure activity relationship (QSAR) and pharmacophore modeling, has also been proposed for identifying antagonists.