Discovery of Novel-Scaffold Monoamine Transporter Ligands via in Silico Screening with the S1 Pocket of the Serotonin Transporter

Abstract

Discovery of new inhibitors of the plasmalemmal monoamine transporters (MATs) continues to provide pharmacotherapeutic options for depression, addiction, attention deficit disorders, psychosis, narcolepsy, and Parkinson’s disease. The windfall of high-resolution MAT structural information afforded by X-ray crystallography has enabled the construction of credible computational models. Elucidation of lead compounds, creation of compound structure–activity series, and pharmacologic testing are staggering expenses that could be reduced by using a MAT computational model for virtual screening (VS) of structural libraries containing millions of compounds. Here, VS of the PubChem small molecule structural database using the S1 (primary substrate) ligand pocket of a serotonin transporter homology model yielded 19 prominent “hit” compounds. In vitro pharmacology of these VS hits revealed four structurally unique MAT substrate uptake inhibitors with high nanomolar affinity at one or more of the three MATs. In vivo characterization of three of these hits revealed significant activity in a mouse model of acute depression at doses that did not elicit untoward locomotor effects. This constitutes the first report of MAT inhibitor discovery using exclusively the primary substrate pocket as a VS tool. Novel-scaffold MAT inhibitors offer hope of new medications that lack the many classic adverse effects of existing antidepressant drugs.

Properties of an Inward-Facing State of LeuT: Conformational Stability and Substrate Release

“…Computational studies of the bacterial transporters (5,(8)(9)(10)(11)(12)(13)(14)(15) along with homology models of the human transporters (16)(17)(18)(19) have led to a better understanding of how these transporters function (20). The high similarity (21) between the binding mode of the inhibitor bound in the recent dDAT structure (7) and a computational model of a similar inhibitor bound to the serotonin transporter (22) also demonstrate that reliable results can be obtained from computational studies of this family of transporters.…”

HTMD: High-Throughput Molecular Dynamics for Molecular Discovery

“…Protein folding, protein–ligand binding, and protein–protein interactions are some of the most studied phenomena in biophysics. If understood, these phenomena can lead to the development of novel drugs as well as an improved understanding of cellular function. − There are several methodologies for investigating these problems including experimental, such as NMR, fluorescence, and X-ray, but we believe that simulation-based discovery is going to reach a prime spot in the long term due to the exponential growth of information technologies…”

Designing modulators of monoamine transporters using virtual screening techniques

“…The S1 pocket (Figure 1 ) is lined by residues N21, A22, G24, L25, G26, Y108, I359, F253, S256, F259, S355 in the LeuT crystal structure bound to Leucine (pdb code: 3F3E; Singh et al, 2008 ). Virtual screening techniques using receptor pharmacophore models of the SERT S1 pocket has led to the design of novel SSRIs and antidepressant molecules ( Nolan et al, 2011 , 2014 ). A study by Schlessinger et al (2011) utilized molecular docking and virtual screening techniques to screen the KEGG DRUGs ( Kanehisa et al, 2010 ) database to design novel NET ligands binding to the S1 site of the transporter.…”