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Title: Predicting Drug Interactions with Human Equilibrative Nucleoside Transporters 1 and 2 Using Functional Knockout Cell Lines and Bayesian Modeling.

Authors: Miller, Siennah R; Zhang, Xiaohong; Hau, Raymond K; Jilek, Joseph L; Jennings, Erin Q; Galligan, James J; Foil, Daniel H; Zorn, Kimberley M; Ekins, Sean; Wright, Stephen H; Cherrington, Nathan J

Published In Mol Pharmacol, (2021 02)

Abstract: Equilibrative nucleoside transporters (ENTs) 1 and 2 facilitate nucleoside transport across the blood-testis barrier (BTB). Improving drug entry into the testes with drugs that use endogenous transport pathways may lead to more effective treatments for diseases within the reproductive tract. In this study, CRISPR/CRISPR-associated protein 9 was used to generate HeLa cell lines in which ENT expression was limited to ENT1 or ENT2. We characterized uridine transport in these cell lines and generated Bayesian models to predict interactions with the ENTs. Quantification of [3H]uridine uptake in the presence of the ENT-specific inhibitor S-(4-nitrobenzyl)-6-thioinosine (NBMPR) demonstrated functional loss of each transporter. Nine nucleoside reverse-transcriptase inhibitors and 37 nucleoside/heterocycle analogs were evaluated to identify ENT interactions. Twenty-one compounds inhibited uridine uptake and abacavir, nevirapine, ticagrelor, and uridine triacetate had different IC50 values for ENT1 and ENT2. Total accumulation of four identified inhibitors was measured with and without NBMPR to determine whether there was ENT-mediated transport. Clofarabine and cladribine were ENT1 and ENT2 substrates, whereas nevirapine and lexibulin were ENT1 and ENT2 nontransported inhibitors. Bayesian models generated using Assay Central machine learning software yielded reasonably high internal validation performance (receiver operator characteristic > 0.7). ENT1 IC50-based models were generated from ChEMBL; subvalidations using this training data set correctly predicted 58% of inhibitors when analyzing activity by percent uptake and 63% when using estimated-IC50 values. Determining drug interactions with these transporters can be useful in identifying and predicting compounds that are ENT1 and ENT2 substrates and can thereby circumvent the BTB through this transepithelial transport pathway in Sertoli cells. SIGNIFICANCE STATEMENT: This study is the first to predict drug interactions with equilibrative nucleoside transporter (ENT) 1 and ENT2 using Bayesian modeling. Novel CRISPR/CRISPR-associated protein 9 functional knockouts of ENT1 and ENT2 in HeLa S3 cells were generated and characterized. Determining drug interactions with these transporters can be useful in identifying and predicting compounds that are ENT1 and ENT2 substrates and can circumvent the blood-testis barrier through this transepithelial transport pathway in Sertoli cells.

PubMed ID: 33262250 Exiting the NIEHS site

MeSH Terms: Acetates/pharmacology*; Bayes Theorem; Biological Transport; CRISPR-Cas Systems; Cell Line; Dideoxynucleosides/pharmacology*; Drug Interactions; Equilibrative Nucleoside Transporter 1/genetics*; Equilibrative Nucleoside Transporter 1/metabolism; Equilibrative-Nucleoside Transporter 2/genetics*; Equilibrative-Nucleoside Transporter 2/metabolism; Gene Knockout Techniques; HeLa Cells; Humans; Machine Learning; Nevirapine/pharmacology*; Thioinosine/analogs & derivatives; Thioinosine/pharmacology; Ticagrelor/pharmacology*; Uridine/analogs & derivatives*; Uridine/metabolism*; Uridine/pharmacology

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