Glucagon and the glucagon receptor are most important molecules control over blood glucose concentrations. These two molecules are very important to studies of type 2 diabetic patients. In literature, several classes of small molecule antagonists of the human glucagon receptor have been reported. Glucagon receptor antagonist could decrease hepatic glucose output and improve glucose control in diabetic patients. In this research, to identify novel and diverse leads for use in potent glucagon receptor antagonist design, a ligand-based pharmacophore modeling, was developed using the best conformations of training set compounds. The best five features pharmacophore model, called Hypo1, includes, hydrogen bond acceptors, two hydrophobic, and positive ionizable features, which has the highest correlation coefficient (0.805), cost difference (64.38), low RMS (2.148), as well as it shows a high goodness of fit and enrichment factor. The generated pharmacophore model has been validated by using a series of similar structures with varying affinities for the glucagon receptor. Then, the developed model has been applied as a search query in different database searching with the main objective of finding novel molecules which have the potential to be be modified into novel lead compounds. As a result, some hit molecules were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. The results from pharmacophore modeling and molecular docking are complementary to each other and could serve as a useful way for the discovery of potent small molecules as glucagon receptor antagonist.
Keywords: Computer Aided Drug Design; Docking; Glucagon Receptor Antagonist; Ligand-Based Pharmacophore Modeling; Virtual Screening.