Functional Selectivity: A Novel Approach for CNS Drug Discovery

DESCRIPTION (provided by applicant): The overall goal of this project is to test the hypothesis that functionally-selective D2-dopamine receptor agonists with extreme signaling bias for the canonical and non-canonical signaling pathways will represent novel treatments for schizophrenia and related disorders. This U19 represents a collaboration between investigators at the University of North Carolina Chapel Hill, Duke University and Pfizer Pharmaceuticals. To achieve this overall goal we have the following three main projects: Project #1: Will deliver beta-arrestin-biased agonist clinical candidates of dopamine D2 receptors (D2R) for the treatment of schizophrenia and related disorders, and create novel D2R ligands with a wide range of unprecedented patterns of functional selectivity (including Gi-biased full and partial agonists) as chemical probes for elucidating the key signaling pathways essential for antipsychotic efficacy and side-effects. Project #2: Will provide novel animal models to validate compounds delivered in Project 1 in order to demonstrate functional selectivity in vivo. Project #3: Will provide ADMETsupport and additional in vivo and in vitro testing to support advancement of compounds identified in Projects 1 and 2 for proof-of-concept clinical trials The three interconnected and synergistic projects will be supported by three cores: 1. Administrative Core: which will provide administrative support for various teams of investigators and scheduling of Scientific Advisory Board meetings for periodic feedback. 2. Screening Core: which will provide all of the in vitro screening and profiling required to advance compounds. This core will be assisted by the National Institute of Mental Health Psychoactive Drug Screening Program at the University of North Carolina Chapel Hill Medical School. 3. Behavioral Core: will provide the essential in vivo validation required to demonstrate antipsychotic drug like activity as well as activity against bot positive and negative symptomatology using appropriate animal models.