Identification of Novel High-Affinity Substrates of OCT1 Using Machine Learning-Guided Virtual Screening and Experimental Validation

Abstract

OCT1 is the most highly expressed cation transporter in the liver and affects pharmacokinetics and pharmacodynamics. Newly marketed drugs have previously been screened as potential OCT1 substrates and verified by virtual docking. Here, we used machine learning with transport experiment data to predict OCT1 substrates based on classic molecular descriptors, pharmacophore features, and extended-connectivity fingerprints and confirmed them by in vitro uptake experiments. We virtually screened a database of more than 1000 substances. Nineteen predicted substances were chosen for in vitro testing. Sixteen of the 19 newly tested substances (85%) were confirmed as, mostly strong, substrates, including edrophonium, fenpiverinium, ritodrine, and ractopamine. Even without a crystal structure of OCT1, machine learning algorithms predict substrates accurately and may contribute not only to a more focused screening in drug development but also to a better molecular understanding of OCT1 in general.

Overlap and Specificity in the Substrate Spectra of Human Monoamine Transporters and Organic Cation Transporters 1, 2, and 3

“…When using an uptake ratio of 3 as cutoff, the corresponding numbers were 29, 41, 32, 23, 18, and 17 and thus, apparently, OCT2 had by far the broadest substrate spectrum. At least for OCT1, the cutoff of 3 has previously been shown to successfully discriminate compounds as substrates and non-substrates in accordance with transport kinetic parameters [ 42 ]. Overall, the OCTs had a broader substrate spectrum compared with MATs.…”

“…Additionally, and from a more applied clinical perspective, the identification of the substrate overlap between MATs and OCTs is of great interest for the development of selective radiotracers for diagnostics and therapy [ 38 ]. Meta-iodobenzylguanidine (mIBG), a NET tracer used for diagnostics in heart diseases [ 39 ] as well as for diagnostics and therapy in neuroendocrine cancer patients [ 40 ], has relatively recently been proven to be an excellent OCT substrate [ 41 , 42 ]. High affinity towards OCTs explains some difficulties in mIBG diagnostics and treatment that were previously not understood on a molecular level.…”

Effects of Genetic Polymorphism in CYP2D6, CYP2C19, and the Organic Cation Transporter OCT1 on Amitriptyline Pharmacokinetics in Healthy Volunteers and Depressive Disorder Patients

“…A large number of inherited variants in the gene coding for OCT1 with comparatively high population frequencies have been described, and carriers of some of these variants showed greatly reduced or completely deficient transport activity (Seitz et al, 2015). OCT1 polymorphism may thus partially account for interindividual differences in the pharmacokinetics of numerous drugs (Tzvetkov et al, 2011;Tzvetkov et al, 2013;Tzvetkov et al, 2018;Matthaei et al, 2019;Koepsell, 2020;Jensen et al, 2021). The increased plasma concentrations of these drugs in some patients as a result of OCT1 (partial or complete) deficiency may lead to more severe adverse reactions.…”

Transport of Drugs and Endogenous Compounds Mediated by Human OCT1: Studies in Single- and Double-Transfected Cell Models

“…In this study, the molecular volume of a compound was identified as the best descriptor for OCT1 substrates and lipophilicity was identified to be not important (Hendrickx et al, 2013). Recent publications emphasized the use of in silico predictions and machine learning approaches for the identification of new OCT1 substrates and their molecular characteristics (Baidya et al, 2020;Jensen et al, 2021). The OCT1 substrate and/or inhibitor spectrum has intensively been studied by various groups [e.g., (Gorboulev et al, 1997;Ciarimboli et al, 2005;Wenge et al, 2011;Tzvetkov et al, 2013;Knop et al, 2015;Otter et al, 2017;Meyer et al, 2019;Jensen et al, 2020b;Koepsell, 2020)].…”