Involvement of Human Multidrug and Toxic Compound Extrusion (MATE) Transporters in Testosterone Transport

Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models

Renal secretion plays an important role in excretion of drug from the kidney. Two major transporters known to be highly involved in renal secretion are MATE1/2 K and OCT2, the former of which is highly related to drug-drug interactions. Among published in silico models for MATE inhibitors, a previous model obtained a ROC-AUC value of 0.78 using high throughput percentage inhibition data [J. Med. Chem. 2013, 56(3), 781-795] which we aimed to improve upon here using a combined fingerprint and physics-based approach. To this end, we collected 225 publicly available compounds with pIC50 values against MATE1. Subsequently, on the one hand, we performed a physics-based approach using an Alpha-Fold protein structure, from which we obtained MM-GB/SA scores for those compounds. On the other hand, we built Random Forest (RF) and message passing neural network models using extended-connectivity fingerprints with radius 4 (ECFP4) and chemical structures as graphs, respectively, which also included MM-GB/SA scores as input variables. In a five-fold cross-validation with a separate test set, we found that the best predictivity for the hold-out test was observed in the RF model (including ECFP4 and MM-GB/SA data) with an ROC-AUC of 0.833 ± 0.036; while that of the MM-GB/SA regression model was 0.742. However, the MM-GB/SA model did not show a dependency of the performance on the particular chemical space being predicted. Additionally, via structural interaction fingerprint analysis, we identified interacting residues with inhibitor as identical for those with noninhibitors, including substrates, such as Gln49, Trp274, Tyr277, Tyr299, Ile303, and Tyr306. The similar binding modes are consistent with the observed similar IC50 value inhibitor when using different substrates experimentally, and practically, this can release the experimental scientists from bothering of selecting substrates for MATE1. Hence, we were able to build highly predictive classification models for MATE1 inhibitory activity with both ECFP4 and MM-GB/SA score as input features, which is fit-for-purpose for use in the drug discovery process.

Amiloride is a suitable fluorescent substrate for the study of the drug transporter human multidrug and toxin extrusion 1 (MATE1)

Human multidrug and toxin extrusion 1 (MATE1; SLC47A1) is highly expressed in the kidneys and the liver. It plays a significant role in drug and endogenous compound disposition, and therefore, a rapid evaluation of its inhibition is important for drug development and for the understanding of renal and hepatic physiology. Amiloride is a potassium-sparing diuretic used for treating hypertension; it also demonstrates strong fluorescence in organic solvent or detergent solutions. In this study, we investigated the transport characteristics of amiloride by human MATE1. Cellular accumulation of amiloride was evaluated in control vector- or MATE1-transfected HEK293 cells. Cells were lysed with 1% sodium dodecyl sulfate, and fluorescence was measured using a microplate reader at wavelengths of 364_ex and 409_em. With ammonium prepulse-induced intracellular acidification, MATE1 transported amiloride at an extracellular pH of 7.4. The uptake demonstrated an overshoot phenomenon and saturated, with the K_m and V_max being 23.5 μM and 1.01 nmol/mg/min, respectively. MATE1-mediated amiloride transport also presented with a bell-shaped pH profile that reached a maximum pH value of 7.4. The inhibitor sensitivity of MATE1-facilitated amiloride transport was similar to those of known substrates, such as tetraethylammonium and metformin. Among the tested inhibitors, pyrimethamine demonstrated the most potent inhibition with an IC₅₀ value of 0.266 μM. Furthermore, MATE1 was found to be inhibited by fampridine, which was previously considered to be a non-inhibitor of MATE1. This study demonstrates that amiloride is a suitable fluorescent substrate for the in vitro study of the transport activity of MATE1.

Drug Transporters in the Kidney: Perspectives on Species Differences, Disease Status, and Molecular Docking

The kidneys are a pair of important organs that excretes endogenous waste and exogenous biological agents from the body. Numerous transporters are involved in the excretion process. The levels of these transporters could affect the pharmacokinetics of many drugs, such as organic anion drugs, organic cationic drugs, and peptide drugs. Eleven drug transporters in the kidney (OAT1, OAT3, OATP4C1, OCT2, MDR1, BCRP, MATE1, MATE2-K, OAT4, MRP2, and MRP4) have become necessary research items in the development of innovative drugs. However, the levels of these transporters vary between different species, sex-genders, ages, and disease statuses, which may lead to different pharmacokinetics of drugs. Here, we review the differences of the important transports in the mentioned conditions, in order to help clinicians to improve clinical prescriptions for patients. To predict drug-drug interactions (DDIs) caused by renal drug transporters, the molecular docking method is used for rapid screening of substrates or inhibitors of the drug transporters. Here, we review a large number of natural products that represent potential substrates and/or inhibitors of transporters by the molecular docking method.