Molecular pharmacophore selectivity studies, virtual screening, and in silico ADMET analysis of GPCR antagonists

Abstract

The G protein-coupled receptors (GPCRs), especially amine type, comprise the largest family of proteins targeted by drug discovery. One of the major hurdles in the design of safe and effective drugs targeting GPCRs is finding ligands that are highly selective for a specific receptor subtype. To gain insights into the structural basis of ligand subtype selectivity within the family of amine receptors (D1, D2, D3, D4, Alpha1, 5HT1a, and 5HT2a), we generated 3D selective pharmacophore models of all seven subtypes. The performance of 3D molecular descriptors for rational design to maximize the structural selectivity of amine GPCR antagonists with different selectivity profile is investigated in this publication. Different family- and target-specific 3D pharmacophore models were built and applied for selectivity searching to evaluate their performance in identifying target-selective hits. Five amine antagonists of highly selectivity prediction were obtained as potential hits using virtual screening protocol of selective models in ZINC database. This study of multiple pharmacophore mapping provided deep insight for identifying subtype-selectivity determinants that can be used as novel tool for discovery of selective and potent GPCR amine antagonists which could be used for treatment of different GPCR-linked diseases.