Identification of Novel Inhibitors of Organic Anion Transporting Polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) Using a Consensus Vote of Six Classification Models

Abstract

Organic anion transporting polypeptides 1B1 and 1B3 are transporters selectively expressed on the basolateral membrane of the hepatocyte. Several studies reveal that they are involved in drug–drug interactions, cancer, and hyperbilirubinemia. In this study, we developed a set of classification models for OATP1B1 and 1B3 inhibition based on more than 1700 carefully curated compounds from literature, which were validated via cross-validation and by use of an external test set. After combining several sets of descriptors and classifiers, the 6 best models were selected according to their statistical performance and were used for virtual screening of DrugBank. Consensus scoring of the screened compounds resulted in the selection and purchase of nine compounds as potential dual inhibitors and of one compound as potential selective OATP1B3 inhibitor. Biological testing of the compounds confirmed the validity of the models, yielding an accuracy of 90% for OATP1B1 and 80% for OATP1B3, respectively. Moreover, at least half of the new identified inhibitors are associated with hyperbilirubinemia or hepatotoxicity, implying a relationship between OATP inhibition and these severe side effects.

Glycyrrhizin has a high likelihood to be a victim of drug–drug interactions mediated by hepatic organic anion‐transporting polypeptide 1B1/1B3

“…For dual substrates of OATP1B1 and OATP1B3, these two transporters normally can compensate for the lack of each other. Therefore, coadministration with a selective inhibitor of OATP1B1 (such as saquinavir, amprenavir, atorvastatin, lapatinib and trametinib) or OATP1B3 (such as ginsenosides of protopanaxadiol type and gliquidone) may not result in significant changes in level of systemic exposure to glycyrrhizin (Karlgren et al, 2012;De Bruyn et al, 2013;Jiang et al, 2015;Kotsampasakou et al, 2015). Because the disease state is also an important regulating factor of these OATP1B transporters (Talal et al, 2017), a clinical drug-drug interaction study for i.v.…”

Vienna LiverTox Workspace—A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies

“…The data were cleaned by using an in-house system combining the molecular operating environment (MOE 2014.09) (Molecular Operating Environment, 2014) wash option and the Atkinson Standardiser (https://github.com/flatkinson/ standardiser). This approach was used for some of the datasets and for others the cleaning procedure of already published papers were used (Pinto et al, 2012;Kotsampasakou et al, 2015). In general, duplicates were removed from the dataset, including pairs of stereoisomers.…”

Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science

“…From a ligand's perspective, modeling studies are strongly impeded by the inconsistent and mostly insufficient number of high-quality bioactivity data which is spread over different data sources in the open domain. For LB studies on uptake transporters, single-point percentage inhibition data has often become the only source for QSAR modeling [ 1 , 14 , 19 , 55 , 58 , 60 , 122 ]. Such models trained on single-point inhibition data can achieve high accuracies, particularly if the measurements were retrieved following the same experimental protocols, as demonstrated by e.g.…”