Conjugation Reactions In Drug Metabolism: An Integrated Approach

Conjugation reactions in drug metabolism: An integrated approach

Conjugation reactions in drug metabolism: An integrated approach Substrates, co-substrates, enzymes and their interactions in vivo and in vitro

Edited by

Gerard J.Mulder Center for Bio-Pharmaceutical Sciences, University of Leiden, The Netherlands

1990 Taylor & Francis London • New York • Philadelphia

UK Taylor & Francis Ltd, 4 John St, London WC1N 2ET USA Taylor & Francis Inc., 1900 Frost Road, Suite 101, Bristol, PA 19007 This edition published in the Taylor & Francis e-Library, 2005. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” Copyright © G.J.Mulder, 1990 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, electrostatic, magnetic tape, mechanical, photocopying, recording or otherwise, without the prior permission of the copyright owner and the publisher. British Library Cataloguing in Publication Data Conjugation reactions in drug metabolism. 1. Drugs. Action. Role of conjugation reactions I.Mulder, Gerard J. 615’.7 ISBN 0-203-48999-3 Master e-book ISBN

ISBN 0-203-79823-6 (Adobe eReader Format) ISBN 0 85066 738.0 (Print Edition) Library of Congress Cataloguing in Publication Data is available

Contents

Preface

v

Contributors

vii

1.

Introduction G.J.Mulder

1

2.

Kinetics of conjugation reactions in eliminating organs K.S.Pang

4

3.

Competition between conjugations for the same substrate G.J.Mulder

39

4.

Glucuronidation G.J.Mulder, M.W.H.Coughtrie and B.Burchell

49

5.

Sulfation G.J.Mulder and W.B.Jakoby

106

6.

Acetylation W.W.Weber, G.N.Levy and D.W.Hein

162

7.

O-Methylation D.R.Thakker and C.R.Creveling

191

8.

N-Methyltransferases S.S.Ansher and W.B.Jakoby

231

9.

S-Methylation J.L.Stevens and J.E.Bakke

249

10.

Amino acid conjugation A.J.Hutt and J.Caldwell

272

11.

Glutathione conjugation B.Ketterer and G.J.Mulder

306

12.

Epoxide hydrolase T.M.Guenthner

365

Preface

‘The conjugations may well be the most important drug biotransformation reactions.’ Thus reads the first sentence in Chapter 1 of this book; and indeed, this may be little realized, if one compares the overwhelming attention paid to cytochrome P-450-mediated biotransformation with what is published on the conjugations. Yet, oxidative metabolism of xenobiotics is usually followed by conjugation of the group created by oxidation. Only then can these compounds be readily eliminated from the organism. In addition, xenobiotics carry many groups which are already acceptor groups for conjugation. This volume summarizes the state of the art for the main conjugations. It should fill the gap between comprehensive monographs of single conjugations on one hand, and the more general reviews of drug metabolism, which often devote only a few pages to the conjugations (often considered to be just detoxication reactions) on the other. The chapters on the various conjugations are the result of a collaborative effort of authors who are familiar with the biochemical aspect of the conjugation and those whose expertise is on the biotransformation in vivo. Therefore, the conjugation is treated as a whole, reflecting the importance of enzymology for the biotransformation of xenobiotics in vivo, in perfusions or in isolated cells. Obviously, the conjugations are involved in the elimination of compounds present in the natural environment, for instance in food. In addition, and this is in fact the most studied aspect, they metabolize xenobiotics made by man, such as medicinal drugs, insecticides, etc. Moreover, many endogenous compounds, such as steroid hormones or prostaglandin derivatives, are substrates for certain forms of the transferases, so that these also play an important role in the homeostasis of the organism. The chapters present an overview, without giving all the details. Also, most chapters contain a brief section on methodology to facilitate the choice of methods for experimental work. The aim of this book is to provide a convenient source of information for both workers in the field of conjugation and those working in related areas. For those

vi

who need all the details, due reference is made to more extensive reviews on specialized subjects. G.J.MULDER February, 1989

Contributors

Sherry S.Ansher

Center for Biologs Evaluation and Research, Food and Drug Administration, Bethesda, MD 20982 (USA) Jerome E.Bakke Metabolism and Radiation Research Laboratory, Agricultural Research Service, USDA, Fargo, ND 58105 (USA) Brian Burchell Department of Biochemical Medicine, Ninewells Hospital and Medical School, Dundee DD1 9SY, Scotland (UK) John Caldwell Department of Pharmacology and Toxicology, St. Mary’s Hospital Medical School, Norfolk Place, London W2 1PG (UK) Michael W.H.Coughtrie Department of Biochemical Medicine, Ninewells Hospital and Medical School, Dundee DD1 9SY, Scotland (UK) Cyrus R.Creveling Laboratory of Bioorganic Chemistry, NIDDK, National Institutes of Health, Bethesda, MD 20892 (USA) Thomas M.Guenthner Department of Pharmacology, University of Illinois College of Medicine, Chicago, IL 60612 (USA) David W.Hein Department of Pharmacology, University of North Dakota School of Medicine, Grand Forks, ND 58201 (USA) Andrew J.Hutt Department of Pharmacy, Brighton Polytechnic, Brighton BN2 4GJ East Sussex (UK) William B.Jakoby Laboratory of Biochemistry and Metabolism, NIDDK, National Institutes of Health, Bethesda, MD 20892 (USA)

viii

Brian Ketterer

Gerald N.Levy

Gerard J.Mulder

K.Sandy Pang James L.Stevens Dhiren R.Thakker

Wendell W.Weber

Biochemistry Department, University College and Middlesex School of Medicine, London W1P 6DB (UK) Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI 48109 (USA) Division of Toxicology, Center for BioPharmaceutical Sciences, University of Leiden, 2300 RA Leiden (The Netherlands) Faculty of Pharmacy, University of Toronto, Toronto, Ontario M5S 1A1 (Canada) W.Alton Jones Cell Science Center, 10 Old Barn Road, Lake Placid, NY 12946 (USA) Department of Drug Metabolism, Glaxo Research Laboratories, Research Triangle Park, NC 27709 (USA) Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI 48109 (USA)

Conjugation reactions in drug metabolism Edited by G.J.Mulder © 1990 Taylor & Francis Ltd

CHAPTER 1 Introduction Gerard J.Mulder Division of Toxicology, Center for Bio-Pharmaceutical Sciences, University of Leiden, 2300 RA Leiden, The Netherlands.

1.1.

DISCOVERY OF THE CONJUGATIONS

1

1.2.

TRANSFERASES AND CO-SUBSTRATES: BIOCHEMISTRY

2

1.3.

MOLECULAR BIOLOGY OF THE TRANSFERASES

2

The conjugations may well be the most important drug biotransformation reactions. The major reason is that xenobiotics that enter the body are usually lipid soluble and therefore are only slowly excreted in urine, the major excretory pathway in most species. Only after biotransformation in which a hydrophilic moiety has been added, such as the sulfate or glucuronic acid group, is water solubility increased and lipid solubility decreased enough to make urinary excretion possible. Usually, therefore, the major proportion of the administered drug dose is excreted as conjugates in urine and bile. Often conjugation is preceded by Phase I metabolic reactions such as hydrolysis or oxidation. The cytochrome P-450 system plays a major role in the latter. However, for compounds that already have a group available for conjugation when they enter the body, such as paracetamol (acetaminophen), conjugation alone is usually the major fate. 1.1. Discovery of the conjugations Most of the conjugations were discovered in the 19th century, when various compounds were fed to animals or human volunteers and the products in urine were analysed. In spite of the relatively primitive analytical methodology available at that time, glucuronidation, sulfation and formation of

2 CONJUGATION REACTIONS IN DRUG METABOLISM

mercapturates and hippurates were discovered. Of course it was very helpful that the compounds used could be administered in large doses to facilitate analysis, which usually required crystallization and elemental analysis. More systematic research was initiated in the 1930s, in particular byR. T.Williams and his collaborators, when the biotransformation of related series of compounds was investigated. Dose dependence of metabolism, biotransformation in various species, metabolite patterns for sometimes very complex structures and excretory pathways were explored; many of the ‘rules’ were discovered during this time. Nowadays it has become feasible to make certain predictions of the metabolism of a new compound based on its chemical structure, the test species as well as the dose level and the route of administration. 1.2. Transferases and co-substrates: biochemistry Once the metabolites of certain structural elements were known, interest shifted to how they were formed. The biotransformation enzymes thus became a subject of study and purification. First, however, the co-substrates for the conjugations had to be known in order to study the properties of the enzyme in vitro. Thus, the chemical structures of ‘active sulfate’, UDP glucuronate and S-adenosylmethionine were discovered. The enzymes could be purified, although in several cases this turned out to be rather difficult, notably because some enzymes were membrane bound and tended to lose activity when solubilized from the membrane. As the transferases were purified it became clear that invariably each was composed of a family of separate forms with more or less overlapping substrate specificity. It is possible to separate these forms and study their properties in pure form; however, the unavoidable problem of purified enzymes is that the properties of the pure enzyme may be quite different from those of the enzyme in vivo. This certainly applies to an enzyme like UDP glucuronosyltransferase, which has to be solubilized from its normal membrane environment in order to purify it. 1.3. Molecular biology of the transferases As the biochemistry of the transferase systems became known, the main emphasis in this area shifted to molecular biological aspects of these enzymes. Using c-DNA libraries the various enzyme forms can be separately expressed, the control of their transcription can be studied, and their primary structure can be determined. This type of work has, understandably, moved away from more

INTRODUCTION 3

traditional drug metabolism research with a more pharmacological or toxicological perspective. However, it has its impact on our insight in regulation of drug metabolism in vivo. In the present work, an attempt is made to combine the biochemistry of the transferases with the more classical drug metabolism work in vivo or in perfused organ and isolated cell studies.

Conjugation reactions in drug metabolism Edited by G.J.Mulder © 1990 Taylor & Francis Ltd

CHAPTER 2 Kinetics of conjugation reactions in eliminating organs K.Sandy Pang Faculty of Pharmacy, University of Toronto, Toronto, Ontario M5S 1A1, Canada

2.1.

INTRODUCTION

5

2.2.

COMPETING CONJUGATION PATHWAYS IN LIVER

8

Kinetic modeling of conjugation pathways

2.3.

9

Influence of kinetic constants

12

Influence of enzymic distributions

14

CONJUGATION OF PHENOLIC SUBSTRATES IN LIVER

15

Substrate concentration and competing pathways

15

Inhibition of sulfation on competing conjugative pathways

16

Estimations of kinetic parameters

18

Uneven distribution of enzymic activities

19

Kinetic modeling of metabolic data

22

Conjugations mediated by the same isoenzyme

23

Sequential conjugation

25

2.4.

CO-SUBSTRATE

27

2.5.

DIFFUSIONAL BARRIERS FOR CONJUGATES

29

2.6.

Liver

29

Kidney

30

FLOW

30

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 5

2.7.

2.8.

EXTRAHEPATIC CONJUGATION

31

Intestinal conjugation relative to liver conjugation

31

Kidney

30

CONCLUDING REMARKS

34

ABBREVIATIONS

34

REFERENCES

35

2.1. Introduction Conjugations are ubiquitous among drug-eliminating organs and require the presence of both the transferases and co-substrates. Generally speaking, the liver is the most important organ involved in the conjugation of xenobiotics, though demonstrable lung (Cassidy and Houston, 1984), intestine (Barr and Riegelman, 1970; Dollery et al., 1971; Bock and Winne, 1975; Pinkus et al., 1977; Shibasaki et al., 1981), kidney (Tremaine et al., 1984) and skin (Pannather et al., 1978) conjugation abilities have also been reported. To adequately address the topic of conjugation kinetics in any eliminating organ, consideration must be given to the factors which influence drug and metabolite clearances. These include the blood perfusion rate to the organ, the transport process for the conjugate and its precursor, the extent of binding to blood (red cell and plasma proteins) components, availability of conjugative enzymes and co-substrate, the enzymic parameters and attendant zonal heterogeneity, the presence of other competing pathways and whether the formed metabolite is subject to further metabolism (Pang and Xu, 1988). The functional heterogeneities of the organ (Gumucio and Miller, 1978), notably, zonation of enzymes, is the most prominent factor. Much is known about the functional metabolic heterogeneity of the liver, the major organ for conjugation. Hepatic drug conjugation is emphasized in this chapter to illustrate the various rate-determining factors: flow, enzyme, cosubstrate availability that control the rate of conjugation within an intact organ. The concepts developed throughout this chapter on the competition between sulfation and glucuronidation for common phenolic substrates within the singlepass perfused liver are extended to other organs, e.g. the intestine and liver (Pang, 1986; Xu et al., 1989a) and can be applied to other competing pathways, e.g. amino acid conjugation versus glucuronidation of arylcarboxylic acids (Chapter 10).

6 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.1. Blood supply of the simple liver acinus and the zonal arrangement of cells. The terminal afferent vessels, hepatic arterioles, and distributing portal veins leave the large portal space (P.S.). Zones 1, 2 and 3 represent areas supplied with blood of first, second, and third quality with regard to oxygen and nutrient contents. Zones 1, 2 and 3 designate the corresponding areas in an acinar unit. Blood from each micro-circulatory unit is collected by at least two terminal hepatic venules (T.h.v.). The perivenous area is formed by the most peripheral portions of Zone 3 of several adjacent acini (reproduced from Rappaport et al., 1954).

For the description of conjugation kinetics in the liver, the structure of the organ and microcirculation must be taken into consideration. The smallest functional unit of the liver is known as the acinus (Rappaport et al., 1954; Rappaport, 1958), which consists of a terminal portal venule and hepatic arteriole, a bile duct, lymph vessels, and nerves. There is a zonal relationship between the cells constituting the acinus and the blood supply. The hepatocytes situated close to the portal space are first supplied with fresh blood (rich in oxygen and nutrients), and these cells are called Zone 1 cells. In contrast, cells located close to the perihepatic venules are poorly supplied by blood in terms of oxygen and are classified as Zone 3 hepatocytes. Cells in between are called Zone 2 cells. These zones are virtually synonymous with the periportal, midzonal and perihepatic venous (pericentral) regions and differ significantly in drug uptake and metabolic activities (Figure 2.1). Upon entry into the liver, a substrate is carried along the direction of flow from the inlet to outlet of the liver. A substrate gains access to the metabolic machinery along the direction of flow into the Disse Space, an interstitium which allows equilibrative exchange with the hepatocytes. Following substrate

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 7

Figure 2.2. The distributed-in-space phenomenon in drug processing. A schematic representation of uneven distribution of drug metabolizing enzymes in the liver, Systems I and II which are either involved in parallel, competing, or sequential metabolic pathways. Drug processing, occurring along the direction of flow of substrate, occurs from left to right, in a distributed-in-space fashion. The enzymic distributions of Systems I and II are described by the median distances, the distance from the inlet of the liver to the median (plane which divides the amount of enzyme into equal halves). As shown, System I is anteriorly localized relative to System II along the direction of flow of substrate.

access into the cells, substrate conversion, biliary excretion or efflux back to the sinusoid occurs. The successive uptake of substrate along the direction of flow may be defined as a distributed-in-space phenomenon (Goresky et al., 1973), inasmuch as transport, recruitment of enzymic activities, excretion, and consumption of co-substrates commensurate with substrate flow (Figure 2.2). A substrate delivered into the liver will first arrive at the anteriorly-located enzyme system (System I) and generate the corresponding metabolites; formation of metabolites by a posteriorly-located enzyme system (System II) occurs when residual substrate arrives downstream for recruitment of such metabolic activities. For these two systems, the relative locations of each system may be described with respect to its median (or centre) of enzymic distribution, the plane which divides total enzymic activity into halves. The median or the median distance serves to interrelate the distance between inlet of the liver and the bulk of the enzyme. System I is an anterior pathway in relation to System II, since its median (or centre) of distribution precedes that for System II (Figure 2.2). The concentration of substrate at any point x is influenced by events at x or preceding x due to removal of substrate and consequently modulating the intrahepatic substrate concentration gradient. At low or intermediate substrate concentrations (relative to the Kms), a greater substrate concentration gradient is found in comparison to higher input substrate concentrations. Model-

8 CONJUGATION REACTIONS IN DRUG METABOLISM

Table 2.1. Known heterogeneities on intercellular distributions of drug metabolizing activities in the liver.

dependent sensitivity is high at these low input concentrations. At higher concentrations, the intrahepatic concentration gradient is much decreased, and all enzymic systems (anterior and posterior) will be recruited by the substrate, rendering the influence of enzymic heterogeneity unimportant. Metabolic zonation of enzyme system(s) within the liver lobule has been well studied within the past few years. Direct and indirect techniques have shown an enriched presence of the cytochrome P-450s, epoxide hydrolase, glutathione Stransferases and UDP glucuronosyltransferases in the perivenous region (Zone 3), and sulfotransferases in the periportal region of the liver (Table 2.1). Elimination of a substrate/metabolite occurs only when it is present along the sinusoid and if it gains access into hepatocytes. Given the marked enzymic heterogeneities noted for Phase I and Phase II reactions, the nature and proportion of conjugates formed as primary or secondary metabolites arising from parallel or sequential pathways is expected to differ. 2.2. Competing conjugation pathways in liver Sulfation and glucuronidation are competing pathways of phenolic substrates. The studies on conjugation of phenols in isolated rat hepatocytes showed that the avid sulfation was eventually taken over by glucuronidation at increasing concentrations of the substrate (see Chapters 4 and 5). This response has been attributed to a detergent-like effect of substrates on the latency of membranebound UDP glucuronosyltransferases. In reality, these differences are readily explained solely on the basis of the differences in Km and Vmax of the

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 9

conjugative systems. By virtue of its high affinity, sulfation is ordinarily the dominant pathway and is prone to saturation upon substrate loading. The latter occurrence creates a substrate-sparing effect and allows for disproportionate increases in glucuronidation rates relative to those seen ordinarily at low substrate concentration, consequently giving a false impression of activation of the glucuronidation system. Within the intact liver, the same phenomenon exists, albeit in a distributedinspace fashion, and drug processing occurs along the direction of flow and according to the zonal enrichments of the drug metabolizing enzyme systems. This topic has been explored quite extensively both theoretically and experimentally (Pang et al., 1983; Morris and Pang, 1987; Pang et al., 1987; Morris et al., 1988a, 1988b; Xu and Pang, 1989a; Xu et al., 1989b). Let us assume for now, that co-substrate within cells and substrate entry into the hepatocytes are not rate-limiting. Kinetic modeling of conjugation pathways An understanding of the kinetics of conjugation has been approached by theoretical modeling of the liver with various enzymic distribution patterns and kinetic constants. The liver can be viewed simplistically as a series of parallel units or sinusoids of length L, each receiving an equal fraction of blood flow and surrounded by single sheets of hepatocytes, one cell thick, on either side. Enzymic activity within any cell located at the same point x, or Vmax, x, cell, may be summed for all hepatocytes at point x, such that a distribution of the overall Vmax, x results for the whole liver (Figure 2.3). The overall metabolic activities (Vmax) is expressed as

Analogously, the distribution pattern of another enzyme system (either for drug removal or metabolite transformation) may be similarly constructed. It is recognized that this assumption describes a slightly lower Vmax than the actual constant due to a lack of consideration of the capillary transit time (Goresky et al., 1973; Pang et al., 1988a). The Km for the metabolic pathway is considered constant for the same system. Steady-state mass balanced rate equations may be written for the change of sinusoidal drug or metabolite concentrations at any point x due to processing of drug and formation of the metabolite(s) upon a single passage of drug through the liver (similar to the single-pass rat liver perfusion). If the metabolite undergoes sequential metabolism, then mass balance equations incorporating such pathways would be included, and the rate of metabolite formation is represented by the sum of the efflux rates (into hepatic vein and in bile) of the

10 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.3. A schematic representation of extreme distribution patterns for sulfation (horizontal lines) and glucuronidation (vertical lines) activities (Models A, B, and C) in liver. The same amounts of enzymes for sulfation and glucuronidation are present for each model (reproduced from Pang et al., 1987).

metabolite and its subsequent metabolites. Variables such as input concentration of drug and direction of flow are used as perturbations to provide simulated data. As an illustration of this simulation procedure, a compound, with a constant unbound fraction in blood (fB) and which undergoes sulfation and glucuronidation, is used (Figure 2.3). Three extreme situations of enzymic distribution patterns are presented: even distribution for both enzymes (Model A); an exclusive anteriorly-located sulfation but a posteriorly-distributed glucuronidation system (Model B); and the reversed distribution of the Model B (Model C). The sulfation system (I) is assigned as the pathway with higher affinity but lower capacity relative to glucuronidation (II). This is true for many phenolic compounds, including harmol (Pang et al., 1981; Pang et al., 1983) salicylamide (Koike et al., 1981; Xu and Pang, 1989a; Xu et al., 1989b), and acetaminophen (Watari et al., 1983). Based on mass balance considerations, the rate of change of drug (dCx) and conjugates and , respectively, for the sulfate and glucuronide conjugates) over a small increment of length, dx, in a single-pass design across the liver preparations are described by following Michaelis-Menten equations

(2.1)

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 11

(2.2) and respectively denote the rates of sulfation and glucuronidation where at point x. At the outlet of the liver , these concentrations represent the output concentrations. Drug disappearance at steady state during a single passage of drug is denoted by the extraction ratio, E

where CIn and COut are the steady-state input and output drug concentrations, respectively. The length-averaged, steady-state, metabolite formation rate, , is estimated by flow, Q, multiplied by the output concentration of conjugate/ metabolite ; biliary excretion of conjugate/ metabolite is treated as zero for the sake of simplicity. Experimentally, the rate of conjugate formation is found by summing the rates of efflux of metabolite in hepatic venous blood and in bile

Upon assignments of Km and Vmax and the enzymic distribution patterns, E and the steady-state rates of sulfation (S) and glucuronidation (G) may be simulated by numerical approximation or by simple FORTRAN programs for a microcomputer. The distribution (Vmax at any point x, Vmax, x), together with the Km for these two systems, dictate the rates of metabolite formation at given inlet substrate concentrations. From Table 2.2, it can be shown that for the assigned constants, the drug is highly extracted (0·996) at low input concentration (0·1 µM) and the values are identical for all three models, indicating that the clearance of the compound is flow-limited. However, the proportion of conjugates formed is highly modeldependent. Model B generates the highest proportion of sulfate conjugate (S) but the smallest proportion of glucuronidate conjugate (G); Model C gives the opposite results of Model B; and Model A predicts intermediate S and G. At 50 µM input substrate concentration (which exceeds but not ), differences in E are observed among three models: Model C predicts the highest value; Model B is the least efficient system; and Model A, again, is intermediate. When input concentration exceeds both and (400 µM), saturation of all metabolic pathways is found: E is decreased to 0·28 for all models and no difference is observed on S and G from different models. Predictions from models of intermediate distributions may be inferred from those of Models B and C serving as extreme distributions and Model A for mean values. A distinct pattern for S and G is found for Models A and B where sulfation activity is distributed identically or is located exclusively anterior to glucuronidation activity, respectively. In these cases, the rate of glucuronidation

12 CONJUGATION REACTIONS IN DRUG METABOLISM

Table 2.2. Simulated substrate removal and conjugation rates for a high-affinity , low-capacity sulfation system and a lowaffinity , high-capacity glucuronidation system for the three enzyme-distributed models (taken from Pang et al., 1987).

a

E is the steady-state hepatic extraction ratio; S is the steady-state rate of sulfation, expressed as a fraction of the input rate; c G is the steady-state rate of glucuronidation, expressed as a fraction of the input rate. b

(a low-affinity system) displays disproportionate increases upon saturation of sulfation at high substrate concentrations (Figure 2.4). The modulation of intrahepatic substrate concentration due to the high-affinity sulfation pathway is the explanation. At high substrate concentration, the concentration gradient is much decreased, whence all enzymic systems (anterior and posterior) are fully recruited by the substrate, and all sulfation and glucuronidation rates are identical regardless of enzyme heterogeneity. Results from the simulation procedure, therefore, can demonstrate how enzymic distributions and the enzymic constants influence metabolite formation relative to the input substrate concentration. Sequential metabolism of one of the generated metabolites may be incorporated in the above equations (eqns. 2.1 or 2.2). Moreover, if the unbound fraction changes during the single passage of drug through the liver, the above equations may be readily modified such that the rate of elimination is based on the unbound moiety (Xu et al., 1989b). Influence of kinetic constants The influence of enzymic parameters of Km and Vmax has also been shown by the same simulation technique. Upon decreasing the Km (Figure 2.4) or increasing the Vmax for glucuronidation (Figure 2.5), the efficiency in glucuronidation is improved and hence the rate of glucuronidation for Models A and B displays even more marked compensatory increases upon saturation of sulfation (Morris and Pang, 1987; Pang et al., 1987). Conversely, when the Km is increased or the Vmax is decreased for glucuronidation, the apparent compensatory effect

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 13

Figure 2.4. The influence of Km on the rates of glucuronidation for Models A to C (Figure 2.3). The parameters for simulation were: the enzymic constants: , nmol min−1 for sulfation and nmol min−1 for glucuronidation. The Km for glucuronidation was (A) 5 µM; (B) 50 µM; (C) 200 µM; and (D) 500 µM (from Morris and Pang, 1987).

observed for glucuronidation rate versus concentration for Models A and B is reduced. Induction effects within an intact organ must be interpreted with caution, inasmuch as heterogeneities in drug metabolizing activities among competitive pathways exist. The effects of induction and inhibition of two competing pathways on conjugate formation can be reasoned. An equal induction of both anterior and posterior pathways leads to an increased formation rate of metabolite from the anterior pathway but may not readily reveal induction of the posterior system. As complete substrate recruitment by upstream hepatocytes occurs, little substrate is spared for recruitment of downstream activity and a reduction in the formation of metabolite from the posterior pathway is observed, although the pathway is induced (Morris and Pang, 1987). However, inductive effects on the posterior pathway become readily detectable at high inlet substrate concentrations when the anterior pathway becomes saturated.

14 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.5. Influence of on the rates of glucuronidation for Models A to C. The parameters for simulation were identical to those used in Figure 2.4, but was (A) 2000 nmol min−1; (B) 1000 nmol min−1; and (C) 100 nmol min−1 (from Morris and Pang, 1987).

Inhibition of drug metabolism pathways is subject to similar considerations. An inhibited posterior pathway will have little influence on an anterior pathway, whereas inhibition of an anterior pathway may bring about increased formation of metabolites for the posterior pathway (Morris and Pang, 1987), which is unaffected by the inhibitor. Again, the reasoning for this draws upon the availability of substrate for enzyme recruitment. Influence of enzymic distributions The influence of enzymic distributions has been illustrated in the above simulation procedure, that Models A, B, and C provide different metabolites (S and G). Model B is the reverse of Model C in terms of enzymic distributions. At low input substrate concentration, the entire system is flow-limited (see condition for 0·1 µM), the extraction ratio remains high and constant, and the intrahepatic concentration gradient is the steepest. With substrate flow from the portal to hepatic vein, little or no downstream conjugate is formed due to the efficient and almost complete removal by the upstream pathway. With a

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 15

reversal in flow direction (cf. Models B and C), the downstream conjugation pathway becomes upstream in terms of the flow of substrate and receives substrate at the entrance to the organ. The metabolic ratios (S/G) will alter dramatically due to the direction of delivery of substrate. At intermediate concentrations (above but below ), saturation of the sulfation pathway occurs, and both E and S/G would change. At high input substrate concentrations which exceed the Kms (the condition of 400 µM), E and S/G would not be affected due to complete recruitment of all enzymic activities within hepatocytes. This type of kinetic modeling has been used to probe the best substrate concentration for discernment of enzymic distributions in normal and retrograde liver perfusions (to be described later). The intermediate concentration is best as both E and S/G ratios are expected to change (cf. Models B and C at the intermediate concentration, 50 µM, Table 2.2). 2.3. Conjugation of phenolic substrates in liver Substrate concentration and competing pathways Several examples are provided herein to illustrate the concept of substrate recruitment of zonal hepatocyte conjugation activities in single-pass rat liver perfusion studies. Three phenolic substrates are presently used as examples in the perfused rat liver preparation: harmol, which forms sulfate and glucuronide conjugates (Pang et al., 1981); gentisamide (GAM) forms two monosulfates (GAM-2S and GAM-5S) and a monoglucuronide conjugate (GAM-5G) (Morris et al., 1988a); its precursor, salicylamide, forms the sulfate (SAM-S) and glucuronide (SAM-G) as well as GAM in once-through rat liver perfusion studies (Figure 2.6; Xu et al., 1989b). At low inlet concentration of harmol, salicylamide and GAM, sulfation (forming harmol sulfate, SAM-S, and GAM-5S and GAM-2S) was the dominant pathway; glucuronidation/hydroxylation rates were comparatively lower (Figure 2.7). At increasing substrate input, saturation of sulfation for all substrates was being approached and was accompanied by disproportionate increases in glucuronidation/hydroxylation rates. During once-through perfusion, E remained constant for harmol (Pang et al., 1981), gentisamide (Morris et al., 1988a) and salicylamide (Xu et al., 1989b) without constancy in proportions of the conjugates (Figure 2.7). For harmol, rates of formation of harmol glucuronide increased more than anticipated at high input rates. Even for GAM rates of GAM-5G formation displayed non-Michaelis-Menten-like

16 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.6. Metabolic pathways of gentisamide and salicylamide in the rat liver.

characteristics as did harmol glucuronide. The same comment applies to salicylamide glucuronidation and hydroxylation. The higher-than-expected increase in steady-state glucuronidation and hydroxylation rates with concentration may be readily explained purely on the basis that sulfation is the higher-affinity pathway relative to glucuronidation and hydroxylation when enzymes are evenly distributed. The glucuronidation and hydroxylation pathways appear to act as backup systems within this concentration range. These examples illustrate that first-order drug disappearance does not mandate first-order metabolite formation. Rather, the apparent first-order behaviour of the drug may elicit different proportions of metabolites formed. Inhibition of sulfation on competing conjugative pathways When the substrate is spared by an inhibition/suppression of the sulfation pathway with a specific inhibitor such as 2, 6-dichloro-4-nitrophenol (DCNP) (Koster et al., 1982), glucuronidation reveals itself as an effective conjugation pathway of harmol and salicylamide. The competing pathways of sulfation and glucuronidation for harmol ((Pang et al., 1983) and salicylamide) (Xu et al., 1989b) with salicylamide hydroxylation, now display formation patterns conforming to what are expected of simple Michaelis-Menten behaviour

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 17

Figure 2.7. Concentration-dependent elimination of harmol, gentisamide and salicylamide in the single-pass perfused rat liver preparation (10 ml min−1). The steadystate rates of metabolite formation for harmol, gentisamide, and salicylamide were concentration-dependent. At increasing substrate concentrations wherein sulfation was apparently becoming saturated for all three substrates, glucuronidation and hydroxylation (for salicylamide only) rates increased more than proportionately with input concentration (from Pang et al., 1981; Morris et al., 1988a; Xu et al., 1989b).

18 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.8. Inhibition of salicylamide sulfation by DCNP (2, 6-dichloro-4-nitrophenol, 40–50 µM) in the single-pass perfused rat liver preparation. The steady-state sulfation rates were markedly suppressed relative to control livers (Figure 2.7). In an absence of sulfation, glucuronidation surfaced as a dominant pathway for salicylamide; the hydroxylation rates of salicylamide (sum of those for unconjugated and conjugated GAM) were only slightly increased over those for controls. The total represents the sum of all metabolic pathways (from Xu et al., 1989b).

(Figure 2.8). The composite observations on the concentration-dependent formation of conjugates, in an absence (Figure 2.7) and presence (Figure 2.8) of the sulfation inhibitor DCNP may be explained purely on the basis of a lower Km for sulfation when all enzymic systems are evenly distributed in the liver. Estimations of kinetic parameters The presence of a lower Km and Vmax for sulfation and a higher Km and Vmax for glucuronidation has been confirmed by parameter estimations of these enzymic constants in perfused liver studies. The enzymic constants for the intact liver have been routinely estimated by fitting the steady-state rate of formation of the conjugate, v, against the logarithmic average concentration, Ĉ of the substrate. The estimated in this fashion will be slightly underestimated due to a lack of consideration of heterogeneity in capillary transit times (Goresky et al., 1973; Pang et al., 1988a) (2.3) where fB is the unbound fraction of substrate in blood, and Ĉ, the logarithmic average concentration, which relates to the steady-state input and output

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 19

concentrations, CIn and COut, respectively, in single-pass liver perfusions (Goresky et al., 1973; Winkler et al., 1973) (2.4) The appropriateness of the method for multi-enzyme systems has been validated by Morris and Pang (1987) and Xu and Pang (1989a). However, some limitations have been found. Parameter estimations will be close to true values when all enzymic systems are evenly distributed. For unevenly distributed enzymic systems, the estimations will be close to their true values when the Kms of all pathways are of similar orders of magnitude; for vastly different Kms among competing pathways, only the high-affinity system will be correctly estimated (Morris and Pang, 1987). For cases where large differences in Km exist for the conjugative pathways, estimations of enzymic constants for the low-affinity, high-capacity pathway by this method are prone to error. Estimations for enzymic parameters of the low-affinity pathways, therefore, may be obtained by acquiring data upon inhibition of the high-affinity sulfation pathway with selective inhibitors such as DCNP. More precise estimations of these kinetic constants for glucuronidation may then be made from metabolic data in the presence of the sulfation inhibitor with eqn. 2.3. Table 2.3 tabulates the kinetic constants obtained for harmol and salicylamide conjugation and hydroxylation in single-pass rat liver preparations; the glucuronidation and hydroxylation (OH) parameters were obtained in the presence of DCNP since and . Because the kinetic parameters for GAM conjugation are similar, parameter estimations obtained from metabolic data without DCNP in the perfused rat liver would serve as true estimates (Morris et al., 1988a). It must be mentioned that for salicylamide, nonlinear drug protein binding is observed with perfusate and the unbound fraction changes during a single passage of salicylamide through the rat liver. For this reason, the unbound logarithmic average concentration Ĉu was used (similar to eqn. 2.4, expressed in terms of unbound input and output concentrations; Xu and Pang, 1989b). Uneven distribution of enzymic activities For an assignment of relative enzymic distribution patterns, further definition is required. The technique of normal (N) and retrograde (R) once-through liver perfusion (Pang and Terrell, 1981), with perfusate entering the liver from the hepatic vein and leaving via the portal vein, has been used as a tool in the examination of zonal, metabolic heterogeneity (Conway et al., 1982, 1984, 1988; Pang et al., 1983; Morris et al., 1988b; Xu and Pang, 1989a). By employing an identical inlet concentration once through the same liver preparation, a substrate entering the liver from the portal vein will first encounter periportal

20 CONJUGATION REACTIONS IN DRUG METABOLISM

Table 2.3. Kinetic constants for harmol, gentisamide, and salicylamide conjugations.

a The input concentrations of GAM were varied (increased or decreased) stepwise at >35 min to the once-through perfused liver to provide different rates of formation of conjugates. b Estimated in the presence of DCNP (40–50 µM).

cells and later perihepatic venous cells. Reversing the flow direction, with substrate entering the liver from the hepatic vein, brings about a reversal in the order in which enzymic activities are encountered by the substrate. Upon altering from N to R perfusion, any inherent heterogeneity in metabolic activity will be readily revealed by an increase or decrease in metabolite formation. The basic tenet of this approach is that an equal number of hepatocytes is accessed by the substrate, now in a reverse fashion to that ordinarily seen in the normal direction (portal vein to hepatic vein). Only recently, the multiple indicator dilution technique (St-Pierre et al., 1989) provided evidence that the intracellular water space of the perfused rat liver preparation had remained unaltered when the direction of flow was changed from N to R perfusion. Additionally, the unaltered metabolic recruitment of ethanol (St-Pierre et al., 1989), a substrate which shares the same space as intracellular water (Goresky et al., 1983), for both N and R perfusions strongly supports the use of the technique for investigations of acinar distributions for conjugative enzymes. It should be pointed out that the ratedetermining step of the metabolic reaction (e.g. co-substrate supply, enzyme activity, or presence of a diffusional barrier) is not identified by the NR technique. The overall reaction rate and enzymic parameters, Km and Vmax, sometimes involving a multiplicity of isoenzymes with overlapping specificities, are assessed. This method differs from other direct techniques such as immunohistochemical and staining techniques (Redick et al., 1982; Chowdhury et al., 1985; Knapp et al., 1988) which reveal the presence of isoenzyme(s) but seldom the associated activities. As discussed earlier, the elucidative properties of these NR studies are best at inlet substrate concentration (CIn) far below Km for both systems, or above Km for sulfation and below Km for glucuronidation (Models B versus C, Figure 2.4, Table 2.2). At CIn far below Km, E is expected to remain constant during both N

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 21

Figure 2.9. Normal and retrograde perfusion of 8 µM gentisamide in a single-pass rat liver preparation. The unchanged 2S/5S ratio during both normal and retrograde perfusions suggests an identical distribution for the GAM 2- and 5-sulfoconjugation systems, whereas a decreased 5S/5G ratio during retrograde flow suggests an anterior sulfation system in relation to the glucuronidation system(reproduced from Morris et al., 1988b).

and R as clearance is flow-limited (elimination within cells is limited by supply of substrate). For intermediate CIn (above Km for sulfation and below Km for glucuronidation) changes in E and the S/G ratio upon alteration of flow direction from N to R is expected when the median distances for the enzyme systems differ. If sulfation activities are more anteriorly located in relation to glucuronidation activities, E would increase and the S/G ratio would decrease (Morris and Pang, 1987). This kind of behaviour was observed in perfusion studies with harmol, GAM (Figure 2.9) and salicylamide (Figure 2.10). For harmol, S/G decreased but E increased with R (Pang et al., 1983). For GAM, GAM-2S/GAM-5S remained constant during NR whereas GAM-5S/GAM-5G decreased during R, suggesting an identical distribution for GAM sulfation activities which are of anterior distribution in comparison to glucuronidation activity. For salicylamide, SAM-S/ SAM-OH and SAM-S/SAM-G were decreased during R, suggesting that sulfation activity is upstream in relation to glucuronidation and hydroxylation

22 CONJUGATION REACTIONS IN DRUG METABOLISM

Figure 2.10. Normal and retrograde perfusion of 130 µM salicylamide in the single-pass rat liver. The decreased SAM-S/SAM-G and SAM-S/SAM-OH ratios suggest an anterior salicylamide sulfation system in relation to salicylamide glucuronidation and hydroxylation systems (from Xu and Pang, 1989a).

activities (Figure 2.10). Similar observations have been found for 7hydroxycoumarin conjugation, with drug disappearance being monitored by micro-fluorescence with light guides inserted directly into the periportal and perihepatic venous regions of the liver (Conway et al., 1982; 1988). A periportal abundance of acetaminophen sulfation activities has also been reported for the rat liver (Pang and Terrell, 1981; Pang et al., 1988a). Kinetic modeling of metabolic data Kinetic modeling of the three substrates, harmol, GAM, and SAM, for their competing pathways may be performed as outlined in the previous section. Various simplified metabolic patterns are used to describe the competing processes. Values of E and steady-state metabolic ratios (S/G or GAM-2S/ GAM-5S, GAM-2S/GAM-5G, SAM-S/SAM-G or SAM-S/SAM-OH, where S, G, and OH represent sulfation, glucuronidation, and hydroxylation rates) are simulated based on plausible combinations of the enzymic patterns and compared to observations. The enzyme-distributed model that fits the data best (Figure 2.11) reveals a periportally concentrated sulfation activity, an evenly distributed glucuronidation activity towards harmol, GAM and salicylamide, and an enriched perihepatic venous salicylamide hydroxylation activity (Dawson et al., 1985; Morris et al., 1988b; Xu and Pang, 1989a). The observed

KINETICS OF CONJUGATION REACTIONS IN ELIMINATING ORGANS 23

Figure 2.11. Enzymic distribution patterns for the metabolism of harmol, gentisamide and salicylamide in the perfused rat liver. The sulfation (decreasing from inlet to outlet), glucuronidation (even), and hydroxylation (increasing from inlet to outlet) systems show the rank order of median distances: sulfation