Receptor-Based Discovery of a Plasmalemmal Monoamine Transporter Inhibitor via High Throughput Docking and Pharmacophore Modeling.

Recognition of psychostimulants such as cocaine and the amphetamines by the dopamine transporter (DAT) protein is principally responsible for the euphoria and addiction associated with these drugs. Using as a template the crystal structure of a distantly related bacterial leucine transporter, 3-D DAT computer molecular models have been generated. Ligand docking to such models has revealed potential substrate and inhibitor binding pockets, subsequently confirmed by in vitro pharmacology. An inhibitor pocket defined by the DAT model to be within the "extracellular vestibule", just to the extracellular side of the external gate of the primary substrate pocket, was used for virtual screening of a structural library of compounds. High-throughput docking and application of pharmacophore constraints within this vestibular inhibitor pocket identified a compound structurally dissimilar to the classic monoamine (dopamine, norepinephrine and serotonin) transporter (MAT) inhibitors. The compound displaced binding of radiolabeled cocaine analogs at all three MATs, usually with nanomolar K(i) values and within two fold of cocaine's affinity at the norepinephrine transporter. Although a very weak dopamine uptake inhibitor itself, this compound reduced by three fold the potency of cocaine in inhibiting DAT-mediated cellular uptake of dopamine. To our knowledge, the present findings are the first to successfully employ "receptor-based" computer modeling to identify moderate-to-high affinity MAT ligands. In silico ligand screening using MAT models provides a rapid, low cost discovery process that should accelerate identification of novel ligand scaffolds and provide lead compounds in combating psychostimulant addiction and in treating other monoamine-related CNS diseases.