Abstract
The importance of active drug transport in determining chemical fate is becoming increasingly clear, with efflux transporters such as MDR1, MRP2 and BCRP recognised as key determinants of drug action. The impact have been shown to impact compound bioavailability through first-pass effects; determine target site drug concentrations through affecting drug distribution; and drive drug resistance through their up-regulation following chronic drug exposure. While the role of these transporters is well established, less is known about transporters such as MRP3 and MRP4, which act to move chemicals back into the systemic circulation rather than target them for elimination. In this thesis the hypothesis examined states, “transport and metabolism processes are balanced to allow for efficient handling of both endogenous and xenobiotics substrates into the excreta and systemic circulation”. To examine this hypothesis a portion of the molecular interaction network of active drug transporters, passive transport and drug metabolising enzymes that determines the biological fate of 17β-estradiol in the liver was reconstructed. The model was parameterised using experimentally-derived kinetic and abundance values where available, or biologically realistic estimates. The behaviour of the model was validated against in vitro measurement of estradiol fate in primary human hepatocytes. As such the model represents, to the best of our knowledge, the situation occurring in the liver. Under steady-state conditions and physiologically relevant concentrations of 17β-estradiol robust network behaviour was predicted, with network flux predominantly via passive processes. To examine the role of dietary constituents on network behaviour, the impact of the flavonoid compounds hesperidin and naringin on MRP3 and MRP4-dependent transport was determined experimentally. Inhibitory constants were then applied to the in silico model of estradiol metabolism, predicting a complete loss of basolateral efflux by MRP4 and redirection of estradiol glucuronide transport via apical transporters. In summary, we present a computational approach to examine the relative input of network components in determining drug fate, and the impact of food chemical interactions. Such computational approaches provide novel systems to examine the impact of genetic variation or transporter-specific inhibitors on drug fate and, hence, efficacy.