Identifying high affinity ligands for the Plasma Membrane Monoamine Transporter using proteochemometrics
B.J. Bongers1, P. Hartog1, H.J. Sijben1, L.H. Heitman1, A.P. IJzerman1, G.J.P. van Westen1
1Division of Drug Discovery and Safety, Leiden, The Netherlands
Solute Carriers (SLCs) are a relatively underexplored protein family compared to other major protein families such as kinases and G Protein-Coupled Receptors. However, the SLC family has recently received more interest (e.g. the RESOLUTE consortium), and their role in several diseases such as cancer, has become of interest.1,2
One of these SLCs is the Plasma Membrane Monoamine Transporter (PMAT). PMAT (SLC29A4) is a low-affinity, high-capacity transporter for monoamine neurotransmitters such as serotonin and dopamine, and is a member of the equilibrative nucleoside transporters (ENT). PMAT also functions as an efflux transporter for various cationic drugs and neurotoxins in the brain. While the molecular mechanisms are not fully understood yet, PMAT has been related to nephrotoxicity and brain damage.3,4 Moreover, PMAT has been linked to preventing ischemia or as a possible target in cancer treatment, which makes it interesting as a possible drug target.5,6
Currently a good biological assay is lacking to study this SLC. Three inhibitor groups have been identified that affect PMAT, but with an overall low potency. These most potent of these groups were: Decynium-22, Lopinavir and TC-T6000. Most of these inhibitors did have an effect on PMAT, but also affected organic cation transporters (OCT1-3) and the other members of the ENT group.7
The goal of this study was to find structures similar to Decynium-22, with high affinity and better selectivity8. Using data similar to PMAT, the ENT and OCT families, we constructed proteochemometric models that were trained on the ligand and sequence data that was available9. These models were further optimized with a forward backwards feature selection and parameter optimization. Subsequently several predicted small molecules were identified in a virtual screening as novel high-affinity, PMAT inhibitors, with a subset being more selective for PMAT. A potential next step would be experimentally testing these predicted PMAT inhibitors.
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