Nonlinear protein binding and enzyme heterogeneity: effects on hepatic drug removal.

The kinetics of substrate removal by the liver and the resulting nonlinear changes in unbound fraction along the flow path at varying input drug concentrations were examined by a model simulation study. Specifically, we varied the binding association constant, KA, and the Michaelis-Menten constants (Km and Vmax) to examine the steady state drug removal (expressed as hepatic extraction ratio E) and changes in drug binding for (i) unienzyme systems and (ii) simple, parallel metabolic pathways; zonal metabolic heterogeneity was also added as a variable. At low KA, E declined with increasing input drug concentration, due primarily to saturation of enzymes; only small differences in binding were present across the liver. At high KA, a parabolic profile for E with concentration was observed; changes in unbound fraction between the inlet and the outlet of the liver followed in parallel fashion. Protein binding was the rate-determining step at low input drug concentrations, whereas enzyme saturation was the rate-controlling factor at high input drug concentration. Heterogeneous enzymic distribution modulated changes in unbound fraction within the liver and at the outlet. Despite marked changes in unbound fraction occurring within the liver for different enzymic distributions, the overall transhepatic differences were relatively small. We then investigated the logarithmic average unbound concentration and the length averaged concentration as estimates of substrate concentration in liver in the presence of nonlinear drug binding. Fitting of simulated data, with and without assigned random error (10%), to the Michaelis-Menten equation was performed; fitting was repeated for simulated data obtained with presence of a specific inhibitor of the high-affinity, anteriorly distributed pathway. Results were similar for both concentration terms: accurate estimates were obtained for anterior, high affinity pathways; an overestimation of parameters was observed for the lower affinity posteriorly distributed pathways. Improved estimations were found for posteriorly distributed pathways upon inhibition with specific inhibitors; with added random error, however, the improvement was much decreased. We applied the method for fitting of several sets of metabolic data obtained from rat liver perfusion studies performed with salicylamide (SAM) (i) without and (ii) with the presence of 2,6-dichloro-4-nitrophenol (DCNP), a SAM sulfation inhibitor. The fitted results showed that SAM sulfation was a high-affinity high-capacity pathway; SAM glucuronidation was of lower affinity but comparable capacity as the sulfation pathway, whereas SAM hydroxylation was of lower affinity and lower capacity.