Determinants of recognition of ligands binding to benzodiazepine receptor/GABAA receptors initiating sedation

Abstract Complementary behavioral and computational studies of 21 structurally diverse, gamma-amino butyric acid (GABA) A benzodiazepine receptor ligands that influence spontaneous locomotor activity have been performed in this work. This behavioral endpoint is a well-accepted indicator of sedation particularly for GABA A /benzodiazepine receptor ligands. The goal of the work presented here is the identification and assessment of the minimum requirements for ligand recognition of GABA A /benzodiazepine receptors leading to activity at the sedation endpoint embedded in a common 3D pharmacophore for recognition. Using the experimental results, together with a systematic computational procedure developed in our laboratory, a five-component 3D pharmacophore for recognition of the GABA A receptor subtypes associated with the sedative behavioral response has been developed consisting of: two proton-accepting moieties, a hydrophobic region, a ring with polar moieties and an aromatic ring in a common geometric arrangement in all ligands having an effect at the sedation endpoint. To provide further evidence that the 3D pharmacophore developed embodied common requirements for receptor recognition, a pharmacophore analysis was performed for agonists, inverse agonists and antagonists separately. Each of the resulting pharmacophores contained the same five moieties at comparable distances to those found for the pharmacophore generated using all of them together. This result confirms that this pharmacophore constitutes a recognition pharmacophore representing required features in the overlapping portion of their binding sites. The reliability of this 3D pharmacophore was then assessed in several ways. First, it was determined that ligands that had no effect at the sedation endpoint did not comply with the pharmacophore requirements. Second, four benzodiazepine receptor ligands known to have an effect at the sedation endpoint, but not used in the pharmacophore development were found to satisfy the requirements of this pharmacophore. Third, the geometric and chemical requirements embedded in this pharmacophore were used to search 3D databases resulting in the identification of benzodiazepine receptor ligands known to affect sedation, but not included in the pharmacophore development. Finally, a 3D-quantitative structure analysis procedure (QSAR) model was developed based upon the ligands in the training set superimposed at their sedation pharmacophore points. The 3D-QSAR model shows good predictivity for binding of these ligands to receptor subtypes containing α1 but not α5 subunits. The pharmacophore developed for the sedation endpoint thus provides a predictive binding model for diverse ligand binding to α1 containing receptor subtypes.