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Rat Organic Cation Transporter 1 Contains Three Binding Sites for Substrate 1-Methyl-4-phenylpyridinium per Monomer.

Molecular pharmacology (2018-11-10)
Thorsten Keller, Valentin Gorboulev, Thomas D Mueller, Volker Dötsch, Frank Bernhard, Hermann Koepsell
RESUMEN

Organic cation transporters OCT1 (SLC22A1) and OCT2 (SLC22A2) are critically involved in absorption and excretion of diverse cationic drugs. Because drug-drug interactions at these transporters may induce adverse drug effects in patients, in vitro testing during drug development for interaction with the human transporters is mandatory. Recent data performed with rat OCT1 (rOCT1) suggest that currently performed in vitro tests assuming one polyspecific binding site are insufficient. Here we measured the binding and transport of model substrate 1-methyl-4-phenylpyridinium+ (MPP+) by cell-free-expressed fusion proteins of rOCT1 and rOCT1 mutants with green fluorescent protein that had been reconstituted into nanodiscs or proteoliposomes. The nanodiscs were formed with major scaffold protein (MSP) and different phospholipids, whereas the proteoliposomes were formed with a mixture of cholesterol, phosphatidylserine, and phosphatidylcholine. In nanodiscs formed with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine or cholesterol, phosphatidylserine, and phosphatidylcholine, two low-affinity MPP+ binding sites and one high-affinity MPP+ binding site per transporter monomer were determined. Mutagenesis revealed that tryptophan 218 and aspartate 475 in neighboring positions in the modeled outward-open cleft contribute to one low-affinity binding site, whereas arginine 440 located distantly in the cleft is critical for MPP+ binding to another low-affinity site. Comparing MPP+ binding with MPP+ transport suggests that the low-affinity sites are involved in MPP+ transport, whereas high-affinity MPP+ binding influences transport allosterically. The data will be helpful in the interpretation of future crystal structures and provides a rationale for future in vitro testing that is more sophisticated and reliable, leading to the generation of pharmacophore models with high predictive power.