Membrane transport proteins are known to influence the absorption, distribution, metabolism, excretion and toxicity (ADMET) of drugs. At the onset of this thesis work, only a few structure-activity models, in general describing P-glycoprotein (Pgp/ABCB1) interactions, were developed using small datasets with little structural diversity. In this thesis, drug-transport protein interactions were explored using large, diverse datasets representing the chemical space of orally administered registered drugs. Focus was set on the ATP-binding cassette (ABC) transport proteins expressed in the canalicular membrane of human hepatocytes. The inhibition of the ABC transport proteins multidrug-resistance associated protein 2 (MRP2/ABCC2) and bile salt export pump (BSEP/ABCB11) was experimentally investigated using membrane vesicles from cells overexpressing the investigated proteins and sandwich cultured human hepatocytes (SCHH). Several previously unknown inhibitors were identified for both of the proteins and predictive in silico models were developed. Furthermore, a clear association between BSEP inhibition and clinically reported drug induced liver injuries (DILI) was identified. For the first time, an in silico model that described combined inhibition of Pgp, MRP2 and breast cancer resistance protein (BCRP/ABCG2) was developed using a large, structurally diverse dataset. Lipophilic weak bases were more often found to be general ABC inhibitors in comparison to other drugs. In early drug discovery, in silico models can be used as predictive filters in the drug candidate selection process and membrane vesicles as a first experimental screening tool to investigate protein interactions. In summary, the present work has led to an increased understanding of molecular properties important in ABC inhibition as well as the potential influence of ABC proteins in adverse drug reactions. A number of previously unknown ABC inhibitors were identified and predictive computational models were developed.

The liver is the major detoxifying organ, clearing the blood from drugs and other xenobiotics. The extent of hepatic clearance (CL) determines drug exposure and hence, the efficacy and toxicity associated with exposure. Drug-drug interactions (DDIs) that alter the hepatic CL may cause more or less severe outcomes, such as adverse drug reactions. Accurate predictions of drug CL and DDI risk from in vitro data are therefore crucial in drug development. Liver CL depends on several factors including the activities of transporters involved in the hepatic uptake and efflux. The work in this thesis aimed at developing new in vitro and in silico methods to predict hepatic transporter-mediated CL and DDIs in vivo. Particular emphasis was placed on interactions involving the hepatic uptake transporters OATP1B1, OATP1B3, and OATP2B1. These transporters regulate the plasma concentration-time profiles of many drugs including statins. Inhibition of OATP-mediated transport by 225 structurally diverse drugs was investigated in vitro. Several novel inhibitors were identified. The data was used to develop in silico models that could predict OATP inhibitors from molecular structure. Models were developed for static and dynamic predictions of in vivo transporter-mediated drug CL and DDIs. These models rely on a combination of in vitro studies of transport function and mass spectrometry-based quantification of protein expression in the in vitro models and liver tissue. By providing estimations of transporter contributions to the overall hepatic uptake/efflux, the method is expected to improve predictions of transporter-mediated DDIs. Furthermore, proteins of importance for hepatic CL were quantified in liver tissue and isolated hepatocytes. The isolation of hepatocytes from liver tissue was found to be associated with oxidative stress and degradation of transporters and other proteins expressed in the plasma membrane. This has implications for the use of primary hepatocytes as an in vitro model of the liver. Nevertheless, by taking the altered transporter abundance into account using the method developed herein, transport function in hepatocyte experiments can be scaled to the in vivo situation. The concept of protein expression-dependent in vitro-in vivo extrapolations was illustrated using atorvastatin and pitavastatin as model drugs.