PT - JOURNAL ARTICLE AU - Dallas Bednarczyk AU - Sean Ekins AU - James H. Wikel AU - Stephen H. Wright TI - Influence of Molecular Structure on Substrate Binding to the Human Organic Cation Transporter, hOCT1 AID - 10.1124/mol.63.3.489 DP - 2003 Mar 01 TA - Molecular Pharmacology PG - 489--498 VI - 63 IP - 3 4099 - http://molpharm.aspetjournals.org/content/63/3/489.short 4100 - http://molpharm.aspetjournals.org/content/63/3/489.full SO - Mol Pharmacol2003 Mar 01; 63 AB - Organic cation transporters play a critical role in the elimination of therapeutic compounds in the liver and the kidney. We used computational quantitative structure activity approaches to predict molecular features that influence interaction with the human ortholog of the organic cation transporter (hOCT1). [3H]tetraethylammonium uptake in HeLa cells stably expressing hOCT1 was inhibited to varying extents by a diverse set of 30 molecules. A subset of 22 of these was used to produce, using Catalyst, a pharmacophore that consisted of three hydrophobic features and a positive ionizable feature. The correlation coefficient of observed versus predicted IC50 was 0.86 for this training set, which was superior to calculated logP alone (r= 0.73) as a predictor of hOCT1 inhibition. A descriptor-based quantitative structure-activity relationship study using Cerius2 resulted in an equation relating five molecular descriptors to log IC50 with a correlation coefficient of 0.95. Furthermore, a group of phenylpyridinium and quinolinium compounds were used to investigate the spatial limitations of the hOCT1 binding site. The affinity for hOCT was higher for 4-phenylpyridiniums > 3-phenylpyridiniums > quinolinium, indicating that substrate affinity was influenced by the distribution of hydrophobic mass. In addition, supraplanar hydrophobic mass was found to increase the affinity for binding hOCT1. These results indicate how a combination of computational and in vitro approaches may yield insight into the binding affinity of transporters and may be applicable to predicting these properties for new therapeutics.