The objective of this proposal is the discovery of antagonists for the neuropeptide Y (NPY) Y2 subtype of receptor to further define the role of this receptor in mediating the diverse pharmacological properties of NPY. The authors propose and present data in support of a computational approach to drug lead discovery, which involves I) constructing two virtual libraries (VL1 and VL2) (computer models of compounds) from proprietary low affinity Y2 antagonist drugs and structural motifs of known G protein-coupled receptor ligands, and ii) docking molecules which comprise VL1 and VL2 in a Y2 receptor (computer) model (virtual screening) to select compounds which bind the Y2 receptor with high affinity. Validation of the method will be achieved via chemical synthesis and pharmacological evaluation of the molecules which comprise VL1 and VL2 in NPY Y binding and functional assays. Selectivity of preferred compounds will be assessed against Y1, Y4, and Y5 receptors. The authors suggest that their preliminary studies have demonstrated the feasibility of this approach in that they have successfully identified a known Y1 selective antagonist (BIBP3226) as a positive (hit) from virtual screening of a 343 member library against a Y1 receptor model. Phase II goals include the refinement of the computational method and antagonist lead drugs, their exploitation in Y2 target validation and the discovery of Y2 agonists.
Thesaurus Terms:drug design /synthesis /production, inhibitor /antagonist, neuropeptide Y, neuropeptide receptor computer simulation, protein structureNational Institute of Neurological Disorders and Stroke (NINDS)
