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. 2025 Apr 7;22(4):1847-1858.
doi: 10.1021/acs.molpharmaceut.4c00984. Epub 2025 Mar 20.

Computational Approaches for Predicting Drug Interactions with Human Organic Anion Transporter 4 (OAT4)

Lucy Martinez-Guerrero  1 , Patricia A Vignaux  2 , Joshua S Harris  2 , Thomas R Lane  2 , Fabio Urbina  2 , Stephen H Wright  3 , Sean Ekins  2 , Nathan J Cherrington  1
Affiliations

Computational Approaches for Predicting Drug Interactions with Human Organic Anion Transporter 4 (OAT4)

Lucy Martinez-Guerrero et al. Mol Pharm. .

Abstract

Human Organic Anion Transporter 4 (OAT4) is predominantly expressed in the kidneys, particularly in the apical membrane of the proximal tubule cells. This transporter is involved in the renal handling of endogenous and exogenous organic anions (OAs), making it an important transporter for drug-drug interactions (DDIs). To better understand OAT4-compound interactions, we generated single concentration (25 μM) in vitro inhibition data for over 1400 small molecules against the uptake of the fluorescent OA 6-carboxyfluorescein (6-CF) in Chinese hamster ovary (CHO) cells. Several drugs exhibiting higher than 50% inhibition in this initial screen were selected to determine IC50 values against three structurally distinct OAT4 substrates: estrone sulfate (ES), ochratoxin A (OTA), and 6-CF. These IC50 values were then compared to the drug plasma concentration as per the 2020 FDA drug-drug interaction (DDI) guidance. Several screened compounds, including some not previously reported, emerged as novel inhibitors of OAT4. These data were also used to build machine learning classification models to predict the activity of potential OAT4 inhibitors. We compared multiple machine learning algorithms and data cleaning techniques to model these screening data and investigated the utility of conformal predictors to predict OAT4 inhibition of a leave-out set. These experimental and computational approaches allowed us to model diverse and unbalanced data to enable predictions for DDIs mediated by this transporter.

Keywords: Conformal Predictors; Drug Screening; Drug−Drug Interactions (DDIs); Human Organic Anion Transporter 4 (OAT4); Machine Learning; MegaTrans; Organic Anions (OAs); Predictive Modeling.

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Conflict of interest statement

Competing interests

SE is founder and owner of Collaborations Pharmaceuticals, Inc. TRL, FU, JSH and PAV are employees. All other authors have no conflicts of interest.

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