Abstract. With the breakthrough crystallization of the bacterial leucine transporter protein LeuT, the first available X-ray structure for the neurotransmitter/sodium symporter family, development of 3-D computational models is suddenly essential for structure-function studies on the plasmalemmal monoamine transporters (MATs). LeuT-based MAT models have been used to guide elucidation of substrate and inhibitor binding pockets, and molecular dynamics simulations using these models are providing insight into conformations involved in the substrate translocation cycle. With credible MAT models finally in hand, structure-based virtual screening for novel ligands is yielding lead compounds toward the development of new medications for psychostimulant dependence, attention deficit hyperactivity, depression, anxiety, schizophrenia, and other disorders associated with dopamine, norepinephrine, or serotonin dysregulation.
Ligand virtual screening (VS) using the vestibular binding pocket of a 3-D monoamine transporter (MAT) computational model followed by in vitro pharmacology led to the identification of a human serotonin transporter (hSERT) inhibitor with modest affinity (hSERT Ki = 284 nM). Structural comparison of this VS-elucidated compound, denoted MI-17, to known SERT ligands led to the rational design and synthesis of DJLDU-3-79, a molecular hybrid of MI-17 and dual SERT/5-HT1A receptor antagonist SSA-426. Relative to MI-17, DJLDU-3-79 displayed 7-fold improvement in hSERT binding affinity and a 3-fold increase in [3H]-serotonin uptake inhibition potency at hSERT/HEK cells. This hybrid compound displayed a hSERT:hDAT selectivity ratio of 50:1, and a hSERT:hNET (human norepinephrine transporter) ratio of >200:1. In mice, DJLDU-3-79 decreased immobility in the tail suspension test comparable to the SSRI fluvoxamine, suggesting that DJLDU-3-79 may possess antidepressant properties. This proof of concept study highlights MAT virtual screening as a powerful tool for identifying novel inhibitor chemotypes and chemical fragments for rational inhibitor design.
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