ATP-Binding-Cassette Transporters in Biliary Efflux and Drug-Induced Liver Injury

Sammanfattning: 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.