title: Structure-based discovery of prescription drugs that interact with the norepinephrine transporter, NET.
abstract: The norepinephrine transporter (NET) transports norepinephrine from the synapse into presynaptic neurons, where norepinephrine regulates signaling pathways associated with cardiovascular effects and behavioral traits via binding to various receptors (e.g., β2-adrenergic receptor). NET is a known target for a variety of prescription drugs, including antidepressants and psychostimulants, and may mediate off-target effects of other prescription drugs. Here, we identify prescription drugs that bind NET, using virtual ligand screening followed by experimental validation of predicted ligands. We began by constructing a comparative structural model of NET based on its alignment to the atomic structure of a prokaryotic NET homolog, the leucine transporter LeuT. The modeled binding site was validated by confirming that known NET ligands can be docked favorably compared to nonbinding molecules. We then computationally screened 6,436 drugs from the Kyoto Encyclopedia of Genes and Genomes (KEGG DRUG) against the NET model. Ten of the 18 high-scoring drugs tested experimentally were found to be NET inhibitors; five of these were chemically novel ligands of NET. These results may rationalize the efficacy of several sympathetic (tuaminoheptane) and antidepressant (tranylcypromine) drugs, as well as side effects of diabetes (phenformin) and Alzheimer's (talsaclidine) drugs. The observations highlight the utility of virtual screening against a comparative model, even when the target shares less than 30% sequence identity with its template structure and no known ligands in the primary binding site.
authors: Department of Bioengineering and Therapeutic Sciences, and California Institute for Quantitative Biosciences, University of California, San Francisco, CA 94158, USA. schles@salilab.org
authors: Avner
authors: A
authors: Schlessinger
authors: Ethan
authors: E
authors: Geier
authors: Hao
authors: H
authors: Fan
authors: John J
authors: JJ
authors: Irwin
authors: Brian K
authors: BK
authors: Shoichet
authors: Kathleen M
authors: KM
authors: Giacomini
authors: Andrej
authors: A
authors: Sali
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001426:Bacterial Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D001665:Binding Sites / Q000235:genetics; D001692:Biological Transport / Q000187:drug effects; D019295:Computational Biology / Q000379:methods; D055808:Drug Discovery / Q000379:methods*; D057809:HEK293 Cells; D006801:Humans; D007700:Kinetics; D008958:Models, Molecular; D008969:Molecular Sequence Data; D015394:Molecular Structure; D009638:Norepinephrine / Q000737:chemistry / Q000378:metabolism / Q000493:pharmacokinetics; D050484:Norepinephrine Plasma Membrane Transport Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D050480:Plasma Membrane Neurotransmitter Transport Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D055553:Prescription Drugs / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D017386:Sequence Homology, Amino Acid
chemical_list: D001426:Bacterial Proteins; D050484:Norepinephrine Plasma Membrane Transport Proteins; D050480:Plasma Membrane Neurotransmitter Transport Proteins; D055553:Prescription Drugs; C419411:SLC6A16 protein, human; C493227:SLC6A2 protein, human; D009638:Norepinephrine