Characterization of β3-adrenergic receptor:: determination of pharmacophore and 3D QSAR model for β3 adrenergic receptor agonism

The beta(3)-adrenoreceptor (beta(3)-AR) has been shown to mediate various pharmacological and physiological effects such as lipolysis, thermogenesis, and intestinal smooth muscle relaxation. It also plays an important role in glucose homeostasis and energy balance. Molecular modeling studies were undertaken to develop predictive pharmacophoric hypothesis and 3D-QSAR model, which may explain variations in beta(3)-AR agonistic activity in terms of chemical features and physicochemical properties. The two softwares, CATALYST for pharmacophoric alignment and APEX-3D for 3D-QSAR modeling were used to establish the structure activity relationships for beta(3)-AR agonistic activity. Among the several statistically significant models, the selection of the best pharmacophore and 3D-QSAR model was based on its ability to estimate the activity of external test sets of similar and different structural types along with the reasonable consistency of the model with the limited information of the active site Of beta(3)-AR. The final 3D-QSAR model was derived using the pharmacophoric alignments from the hypothesis which consisted of four chemical features: basic or positive ionizable feature on the nitrogen of the aryloxypropylamino group, two ring aromatic features corresponding to the phenyl ring of the phenoxide and the benzenesulphonamido groups and a hydrogen-bond donor (HBD) in the vicinity of the nitrogen atom of the benzenesulphonamido group with the most active molecule mapping in an energetically favorable extended conformation. This hypothesis was in agreement with the site directed mutagenesis studies on human beta(3)-AR and correlated well the observed and estimated activity both in, training and both the external test sets. It also mapped reasonably well to Six beta(3)-AR agonists of different structural classes under clinical development and thus this hypothesis may have a universal applicability in providing a powerful template for virtual screening and also for designing new chemical entities (NCEs) as beta(3)-AR agonists.