Hepatic modeling of metabolite kinetics in sequential and parallel pathways: Salicylamide and gentisamide metabolism in perfused rat liver

Abstract

Previous data on salicylamide (SAM) metabolism in the perfused rat liver had indicated that SAM was metabolized by three parallel (competing) pathways: sulfation, glucuronidation, and hydroxylation, whereas sequential metabolism of the hydroxylated metabolite, gentisamide (GAM), was solely via 5-glucuronidation to form GAM-5G. However, under comparable conditions, preformed GAM formed mainly two monosulfate conjugates at the 2- and 5-positions (GAM-2S and GAM-5S); 5-glucuronidation was a minor pathway. In the present study, the techniques of normal (N) and retrograde (R) rat liver perfusion with SAM and mathematic modeling on SAM and GAM metabolism were used to explore the role of enzymic distributions in determining the dissimilar fates of GAM, as a generated metabolite of SAM or as preformed GAM. Changes in the steady-state extraction ratio of SAM (E) and metabolite formation ratios between N and R perfusions were used as indices of the uneven distribution of enzyme activities. Two SAM concentrations (134 and 295 μM) were used for single-pass perfusion: the lower SAM concentration exceeded the apparent K_m for SAM sulfation but was less than those for SAM glucuronidation and hydroxylation; the higher concentration exceeded the apparent K_m 's for SAM sulfation and glucuronidation but was less than the K_m for hydroxylation. Simulation of SAM metabolism data was carried out with various enzyme distribution patterns and extended to include GAM metabolism. At both input concentrations, E washigh (0.94 at 134 μMand 0.7 at 295 μM) and unchanged during N and R, with SAM-sulfate (SAM-S) as the major metabolite and GAM-5G as the only detectable metabolite of GAM. Saturation of SAM sulfation occurred at the higher input SAM concentration as shown by a decrease in Eand a proportionally less increase in sulfation rates and proportionally more than expected increases in SAM hydroxylation and glucuronidation rates. At both SAM concentrations, the steady-state ratio of metabolite formation rates for SAM-S/SAM-G decreased when flow direction changed from N to R. An insignificant decrease in SAM-S/SAM-OH was observed at the low input SAM concentration, due to the small amount of SAM-OH formed and hence large variation in the ratio among the preparations, whereas at the high input SAM concentration, the decrease in SAM-S/SAM-OH with a change in flow direction from N to R was evident. The metabolite formation ratio, SAM-G/SAM-OH, however, was unchanged at both input concentrations and flow directions. The observed data suggest an anterior SAM sulfation system in relation to the glucuronidation and hydroxylation systems, which are distributed similarly. When the observations were compared to predictions from the enzyme-distributed models, the best prediction on SAM metabolism was given by a model which described sulfation activities anteriorly, glucuronidation activities evenly, and hydroxylation activities posteriorly (perivenous). When the model was used to predict data for SAM and GAM metabolism in once-through perfused rat livers at different input SAM concentrations, in the absence or presence of the sulfation inhibitor, 2,6-dichloro-4-nitrophenol (DCNP), the predictions were in close agreement with previously observed SAM data but failed to predict the exclusive formation of GAM-SG; rather, GAM-2S and GAM-5S were predicted as major sequential metabolites of SAM. The poor correlation for GAM metabolic data may be explained on the basis of subcellular enzyme localizations: the cytochromes P-450 and UDP-glucuronyltransferases, being membrane-bound enzymes, are more coupled for GAM formation and glucuronidation, when GAM was generated intracellularly. The present study suggests that subcompartmentalization of enzymes may need to be considered in hepatic modeling for better prediction of metabolic events.