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DRUG METABOLISM AND DISPOSITION
Copyright © 2003 by The American Society for Pharmacology and Experimental Therapeutics
DMD 31:1093–1102, 2003
Vol. 31, No. 9
1025/1090841
Printed in U.S.A.
COMPARATIVE STUDIES ON THE CYTOCHROME P450-ASSOCIATED METABOLISM
AND INTERACTION POTENTIAL OF SELEGILINE BETWEEN HUMAN LIVER-DERIVED IN
VITRO SYSTEMS
JARMO S. SALONEN, LEENA NYMAN, ALAN R. BOOBIS, ROBERT J. EDWARDS, PATRICIA WATTS, BRIAN G. LAKE,
ROGER J. PRICE, ANTHONY B. RENWICK, MARIA-JOSÉ GÓMEZ-LECHÓN, JOSÉ V. CASTELL,
MAGNUS INGELMAN-SUNDBERG, MATS HIDESTRAND, ANDRE GUILLOUZO, LAURENT CORCOS, PETER S. GOLDFARB,
DAVID F.V. LEWIS, PÄIVI TAAVITSAINEN, AND OLAVI PELKONEN
(Received December 3, 2002; accepted May 30, 2003)
This article is available online at http://dmd.aspetjournals.org
ABSTRACT:
Selegiline was used as a model compound in a project aimed at
comparing, evaluating, and integrating different in vitro approaches for the prediction of cytochrome P450 (P450)-catalyzed
hepatic drug metabolism in humans (EUROCYP). Metabolic predictions were generated using homology modeling, cDNA-expressed P450 enzymes, human liver microsomes, primary cultured
human hepatocytes, and precision-cut human liver slices. All of the
in vitro systems correctly indicated the formation of two dealkylated metabolites, desmethylselegiline and methamphetamine. The
metabolic instability of selegiline was demonstrated by all of the in
vitro systems studied. Estimates of clearance varied from 16 l/h to
223 l/h. With the exception of one approach, all systems underpredicted the in vivo clearance in humans (236 l/h). Despite this, all
approaches successfully classified selegiline as a high clearance
compound. Homology modeling suggested the participation of
CYP2B6 in the demethylation of selegiline and of CYP2D6 in the
depropargylation of the drug. Studies with recombinant expressed
enzymes and with human hepatic microsomal fraction supported
the involvement of CYP2B6 but not of CYP2D6. These techniques
also suggested the involvement of CYP1A2, CYP2C8, and
CYP2C19 in the biotransformation of selegiline. In vitro, CYP2B6
was the most active form of P450 involved in selegiline metabolism. Metabolism by several enzymes operating in parallel implies
a low interaction potential for the drug. None of the techniques
alone was able to predict all aspects of the metabolic and kinetic
behavior of selegiline in vivo. However, when used as an integrated
package, all significant characteristics were predictable.
For more than a decade, in vitro techniques have had a well
established role in the early phases of drug development in predicting
the pharmacokinetic and metabolic behavior of new chemical entities.
When properly used, predictions based on results from in vitro studies
will save both development costs and time. In addition, they greatly
reduce the number of experimental animals used by the industry in
absorption, distribution, metabolism, and excretion studies. Support
for the increased utilization of in vitro techniques in drug metabolism
studies has come from regulatory authorities (CDER/FDA, 1997).
Most of these techniques are easily applicable to high throughput
screening, which has further promoted their use recently (Rodrigues,
1997).
Several in vitro methods for metabolic predictions are in common use,
and even commercially available, but little attention has been paid to the
validation of the systems in terms of quality of the predictions obtained
and their usefulness in the process of drug development. In particular,
comparisons of the data produced by different systems have been scarce.
The present study was part of the EUROCYP project within the Biomed2
(Framework IV) program of the European Union. The goals of the project
were to evaluate, compare, and integrate different in vitro approaches for
the prediction of P450-catalyzed hepatic drug metabolism in humans for
drug development. The final stage of the performance test was a “blind”
evaluation of the metabolism of four model compounds using molecular
modeling, hepatic subcellular fractions, recombinant expressed enzymes,
hepatocytes and human liver slices. The results were compared with the
existing human metabolic and pharmacokinetic data for each compound.
One of the four model compounds was selegiline (SEL1). The others
This study was supported by the European Union framework 4 programme
(EUROCYP Project BMH4-CT96-0254).
Address correspondence to: Jarmo S. Salonen, Orion Pharma Preclinical and
Clinical R&D, P.O. BOX 425 FIN-20101 Turku (Finland). E-mail: jarmo.salonen@
orionpharma.com
1
Abbreviations used are: SEL, selegiline; P450, cytochrome P450; MA, methamphetamine; A, amphetamine; DMS, desmethylselegiline; MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; CL, clearance.
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Orion Pharma, Preclinical and Clinical R&D, Turku, Finland (J.S.S., L.N.); Imperial College, Division of Medicine, Section on Clinical
Pharmacology, London, United Kingdom (A.R.B., R.J.E., P.W.); BIBRA International Ltd., Carshalton, Surrey, United Kingdom (B.G.L., R.J.P.,
A.B.R.); Unidad Hepatologı́a Experimental, Centro de Investigación, Hospital Universitario La Fe, Valencia, Spain (M.-J.G.-L., J.V.C.); Karolinska
Institutet, Institute of Environmental Medicine, Division of Molecular Toxicology, Stockholm, Sweden (M.I.-S., M.H.); University of Rennes,
Faculty of Pharmacy, INSERM U456, Rennes, France (A.G., L.C.); University of Surrey School of Biological Sciences, Guildford, Surrey, United
Kingdom (P.S.G., D.F.V.L.); and University of Oulu, Department of Pharmacology and Toxicology, Oulu, Finland (P.T., O.P.)
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SALONEN ET AL.
were almokalant (Andersson et al., 2001), carbamazepine (Pelkonen et
al., 2001) and carvedilol (A. R. Boobis and O. Pelkonen, unpublished
observation).
Selegiline is an irreversible inhibitor of the monoamine oxidase
type B enzyme (Fowler et al., 1981). It is widely used alone or as an
adjuvant to L-DOPA treatment in Parkinson’s disease (The Parkinson
Study Group, 1993; Koller, 1996; Myllylä et al., 1996). At the
neuronal level, selegiline is also a dopamine reuptake inhibitor (Zsilla
and Knoll, 1982; Tekes et al., 1988). More recently, interest has been
directed toward the drug as a neuroprotective or neuronal rescue agent
(Carrillo et al., 1991; Tatton and Greenwood, 1991; Mytileneou et al.,
1997).
Selegiline is eliminated exclusively by biotransformation. Originally, methamphetamine (MA) and amphetamine (A) were identified
as the major metabolic products in human urine and depropargylation
with subsequent demethylation was postulated as a key metabolic
pathway of the drug (Reynolds et al., 1978). Subsequently, a second
major pathway, via desmethylselegiline (DMS), was reported (Yoshida et al., 1986). In addition, hydroxylated amphetamines have been
reported in the urine of rats and humans dosed with selegiline, but
these have been shown to be minor metabolites (Fig. 1) (Yoshida et
al., 1986; Shin, 1997). Both initial dealkylations have been shown to
be catalyzed by P450 enzymes (Yoshida et al., 1986). Recently, some
work on the participating P450 enzymes has been published (Taavitsainen et al., 2000; Hidestrand et al., 2001), but no comparison of
available candidate systems has yet been reported.
Materials and Methods
The laboratories performing the incubations were blind to the identity of the
compound at the time of the study, and the analytical laboratory was blind to
the design of the study from which the samples being analyzed were derived,
until after completion of that phase of the study. Because of blinding, incubation conditions could not be optimized for the particular compound under
study which may have affected, especially, the clearance estimates. Since
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FIG. 1. Metabolic pathways of selegiline in humans; only major products are shown.
PREDICTION OF IN VIVO SELEGILINE METABOLISM
correspond to sample numbers 2, 5, 6, 11, 12, 14, 20, 23, and 24. All activities
were within the normal ranges reported previously (Boobis et al., 1998).
Inhibition by Selegiline of P450-Specific Enzyme Activities. The following enzyme assays were employed: ethoxyresorufin O-deethylation
(CYP1A1/2) (Burke et al., 1977), coumarin 7-hydroxylation (CYP2A6) (Aitio
1978), with a slight modification as described by Raunio et al. (1988, 1990),
bupropion hydroxylation (CYP2B6) (Faucette et al., 2000; Hesse et al., 2000),
tolbutamide methylhydroxylation (CYP2C9) (modified from Knodell et al.,
1987 and Sullivan-Klose et al., 1996), S-mephenytoin 4⬘-hydroxylation
(CYP2C19) (Wrighton et al., 1993), dextromethorphan O-demethylation
(CYP2D6) (modified from Park et al., 1984 and Kronbach et al., 1987),
chlorzoxazone 6-hydroxylation (CYP2E1) (Peter et al., 1990), and testosterone
6␤-hydroxylation (CYP3A4/5) (Waxman et al., 1983). The incubation conditions were similar for the different reactions. If not otherwise stated, each
analytical method was applied according to the reference mentioned.
IC50 values were determined by adding selegiline at final concentrations of
0.1, 1,10, 100, and 1,000 ␮M to the incubation mixture. The resultant activities
were compared with those from control incubations into which only solvent
(water) had been added. The IC50 values (the concentration of inhibitor causing
50% inhibition of the original enzyme activity) were determined graphically by
linear regression analysis of the plot of the logarithm of inhibitor concentration
versus percentage of activity remaining after inhibition using Origin, version
4.10 (OriginLab Corp., Northampton, MA). The reference inhibitors were
furafylline for CYP1A2, methoxsalen for CYP2A6, sulfaphenazole for
CYP2C9, omeprazole for CYP2C19, quinidine for CYP2D6, pyridine for
CYP2E1, and ketoconazole for CYP3A4. Methoxsalen and omeprazole are
known also to inhibit P450s other than their targets, but there are no selective
reference inhibitors for CYP2A6 and CYP2C19 (Pelkonen et al., 1998).
In Vitro Incubation System for Selegiline Metabolism. Selegiline (20 –
200 ␮M) was incubated for up to 2 h at 37°C with human liver microsomes in
an incubation system that comprised human liver microsomes (pooled sample
from 10 livers; 0.25 mg), NADPH (1.2 mM) or NADPH-regenerating system
(glucose-6-phosphate dehydrogenase; 4 mM NADP), and phosphate buffer,
pH 7.4, in a final volume of 1 ml. Formation of the metabolites, DMS and MA,
was linear for up to 0.75 h.
Inhibition of microsomal metabolism of selegiline by P450-specific inhibitors. Inhibition of selegiline metabolism in human liver microsomes by various
P450-specific inhibitors was studied in the incubation system described above
(20 ␮M selegiline; incubation time, 30 min). The following inhibitors were
used: CYP1A2, furafylline (1, 2, or 5 ␮M); CYP2A6, coumarin (10, 20, or 50
␮M); CYP2C8, quercetin (3, 10, 30 ␮M); CYP2C9, sulfaphenazole (3, 10, or
30 ␮M); CYP2C19, S-mephenytoin (100, 200, or 500 ␮M); CYP2D6, quinidine (1, 5, or 20 ␮M); CYP2E1, pyridine (1, 5, or 20 ␮M); and CYP3A4,
ketoconazole (1, 5, or 20 ␮M). All inhibitors were added in methanol (1%)
except pyridine, which was added in water.
Correlation study. Selegiline was incubated using the system described
above, and metabolism was determined in nine different human liver samples,
which had previously been characterized for their content and activity of all of
the major drug-metabolizing forms of P450 (CYP1A2, CYP1B1, CYP2A6,
CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4,
CYP3A5, and CYP4A11). The formation rates of desmethylselegiline and
methamphetamine were correlated with P450 specific activities, and the
amounts of P450 apoproteins were quantified by Western immunoblotting
using specific antipeptide antibodies, as described previously (Edwards et al.,
1998).
Human Hepatocytes. Isolation and culture of human hepatocytes. Two
approaches were tested. In the first, hepatocytes used for the present work were
obtained from the resection of an oxalic liver of a young female and were
seeded in Williams medium supplemented with 10% fetal calf serum at a
density of one million cells in 2 ml of medium in a Petri dish, 2.5 cm in
diameter. They showed a viability of ⬎65%. Cells were maintained in a
medium containing no serum but supplemented with 5 ⫻ 10⫺5 M hydrocortisone. Medium was refurbished daily (Guguen-Guillouzo and Guillouzo,
1986; Abdel Razzak et al., 1993). Since the cells seemed to have low metabolic
capacity, they were only used for qualitative purposes.
In the second approach, surgical liver biopsies (weighing 1–3 g) were
obtained from patients undergoing cholecystectomy after informed consent
was obtained. Patients had no known liver pathology, nor did they receive
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molecular modeling is based on the compound structure, modeling could not
be blinded.
Materials. Selegiline hydrochloride [(⫺)-(R)-N,␣-dimethyl-N-2-propynylphenethylamine hydrochloride] was obtained from Orion Pharma (Turku,
Finland) and desmethylselegiline from Chinoin Pharmaceutical and Chemical
Works (Budapest, Hungary). l-Methamphetamine and l-amphetamine were
obtained from Sigma-Aldrich (St. Louis, MO).
Determination of Selegiline and Its Metabolites. Selegiline and its metabolites were analyzed by gas chromatography using nitrogen-selective detection. The assay method is described in detail elsewhere (Taavitsainen et al.,
2000). Briefly, samples were made alkaline by adding potassium hydroxide
and extracted with heptane containing 2% (v/v) isoamyl alcohol. A portion of
the extract was injected into the gas chromatograph and run using a temperature gradient and helium as the carrier gas. Peaks were detected with a
nitrogen-phosphorus detector. Peak areas were used for quantitation.
Modeling. Molecular modeling of mammalian microsomal P450s using the
CYP102 bacterial crystal structure as a template has been carried out for all of
the major P450 families associated with the phase 1 metabolism of drugs and
other foreign compounds (Lewis et al., 1999). Three-dimensional models of
human P450s have been constructed from the CYP102 hemoprotein domain,
for which the X-ray coordinates are known, both in the substrate-bound (Li and
Poulos, 1997) and substrate-free states (Ravichandran et al., 1993). The methodologies employed in homology modeling of P450 enzymes from CYP102
are described in detail elsewhere, including a discussion of the rationale for
using the CYP102 structure as the preferred modeling template (Lewis, 1996).
A number of potential probe substrates (25 in total) for various human P450
enzymes have been identified and tested in the models for CYPlA1, CYP1A2,
CYP2A6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 (Lewis et
al., 1999). Selegiline was tested in these models.
In Vitro Assays. cDNA-expressed enzymes. Yeast expressing one of the
following enzymes, CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C9,
CYP2C19, CYP2D6, CYP2E1, and CYP3A4, were produced in the Laboratory of Molecular Toxicology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden. The expression levels were relatively high,
30 to 200 pmol/mg of microsomal protein. All microsomes produced good
difference spectra showing a homogenous peak at 450 nm in the reduced
carbon monoxide-bound state of the hemoprotein with no signs of P420. The
catalytic properties of the yeast microsomes were evaluated using probe
substrates, and all were active with affinities for the substrates as expected
(Andersson et al., 2001).
Selegiline (1 mM) was incubated with 0.2 mg of yeast microsomal protein
in 0.1 M potassium phosphate buffer, pH 7.4, containing 1 mM NADPH in a
total volume of 0.2 ml at 37°C. The reactions were started by the addition of
NADPH after a 2-min preincubation and terminated after 20 min by adding 20
␮l of 2 M NaOH. Incubations with CYP3A4 were also carried out in the
presence of additional human cytochrome P450 reductase and cytochrome b5
(1:1:3 ratio), which were added to the yeast microsomes and placed on ice 10
min before starting the incubation.
In subsequent experiments, conditions were used which ensured linearity
with protein and time. Substrate concentrations of between 0 – 640 ␮M were
used for determination of the Michaelis-Menten kinetics.
Human Liver Microsomes. Origin of livers and preparation of microsomes. Human liver samples used in this study were obtained from kidney
transplantation donors. The age of the donors (comprising both males and
females) ranged from 7 to 71 years. All samples were histologically normal.
None of the subjects was receiving any drugs known to affect the activity of
enzymes of drug metabolism. Information on cigarette smoking and alcohol
ingestion was not available for all subjects. The use of tissue surplus to
requirement was approved by the appropriate ethics committee in each university. Microsomes were prepared according to standard procedures. The final
microsomal pellet was suspended in 0.1 M phosphate buffer to a concentration
of approximately 20 mg of protein/ml. Protein concentration was measured by
the method of Bradford (1976). The livers were thoroughly characterized for
their P450 apoprotein content and specific model activities, and were shown to
contain all expected P450 enzymes, which were inhibitable by P450-specific
chemical inhibitors. Information on apoprotein content of the samples can be
found in Edwards et al. (1998). The samples used in the present study
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30 min, the medium was changed to fresh serum-free RPMI 1640 medium
containing 0.5 mM L-methionine, 1 ␮M insulin, 0.1 mM hydrocortisone
21-hemisuccinate and 0 to 500 ␮M selegiline (dissolved directly in the culture
medium). Liver slices were incubated for periods of 30 to 90 min, and the
incubations were terminated by removing the vials from the incubator and
plunging them into ice. Appropriate blank incubations (i.e., liver slices in
medium without any selegiline and selegiline in medium without any liver
slices) were also performed. To achieve a good recovery of parent compound
and metabolites (Worboys et al., 1995), the liver slices were removed from the
mesh of the roller inserts and homogenized in the culture medium by sonication (Beamand et al., 1993). Liver slice/medium homogenates were assayed for
total protein content by the method of Lowry et al. (1951) employing bovine
serum albumin as standard. Total protein content was determined to allow for
any differences in liver slice thickness between vials and to provide a scaling
factor for intrinsic clearance calculations. The liver slice/medium homogenates
were stored at ⫺80°C prior to dispatch to the laboratory undertaking the
analysis of selegiline metabolites.
Calculations. Scaling from in vitro candidate systems to whole liver.
Intrinsic clearance (CLint) is defined as the proportionality constant between
the initial rate of the enzymatic reaction (V0) and the drug concentration (C).
According to the Michaelis-Menten equation, V0/C ⫽ Vmax/Km ⫹ C ⫽ CLint.
At low substrate concentrations, the equation reduces to CLint ⫽ Vmax/Km (Ito
et al., 1998).
In all in vitro systems, either the rate of disappearance of the parent
compound or the rate of the appearance of metabolites was used to determine
Km and Vmax (or V0) values. It was not always strictly possible to use initial
linear conditions, but the deviations were modest. No allowance was made for
any nonspecific loss of selegiline or its metabolites in the incubations. In all
systems, appropriate scaling factors were required to convert the primary
kinetic data (Vmax/Km or intrinsic clearance) to whole human liver (hepatic
intrinsic clearance). The scaling was somewhat different for each in vitro
system.
For each cDNA-expressed P450, the form-specific intrinsic clearance was
calculated separately. Then, the calculated value was corrected by the human
liver microsomal content of that particular form based on results of immunochemical quantification, as published by BD Gentest at http://
[email protected]. These values are the average content of each form
found in 12 different human livers and are as follows: CYP1A2, 50 pmol/mg;
CYP2A6, 66 pmol/mg; CYP2B6, 26 pmol/mg; CYP2C9, 55 pmol/mg;
CYP2C19, 26 pmol/mg; CYP2D6, 11pmol/mg; CYP2E1, 53 pmol/mg; and
CYP3A4, 127 pmol/mg, and upscaled assuming 45 mg of microsomal protein/g of liver (Houston and Carlile, 1997; Carlile et al., 1997) and a liver mass
of 1,500 g.
In liver microsomes, the intrinsic clearance was converted to hepatic clearance by assuming 1 g of liver contains 45 mg of microsomal protein and the
liver mass to be 1,500 g.
In liver slices, scaling was performed on the basis of the liver slice whole
homogenate protein content compared with human liver total protein content.
Human liver whole homogenate protein has been determined by homogenizing
samples of the liver used to prepare the liver slices and determining the protein
content by the method of Lowry et al. (1951). Human liver total protein content
of 200 mg of protein/g of liver wet weight has been used in the literature
(Bayliss et al., 1990).
In hepatocytes, whole liver clearance was calculated assuming that cell
yield was 120 ⫻ 106 cells/g of liver (Iwatsubo et al., 1997).
Scaling from liver to in vivo. To calculate the hepatic organ clearance, the
well stirred model (Wilkinson and Shand, 1975) excluding protein binding,
suggested by Obach et al. (1997) to give a more accurate estimate, was applied.
A liver blood flow, QH ⫽ 1.450 l/min (Davies and Morris, 1993), was used.
According to the model, the organ clearance is CLH ⫽ QH 䡠 CLint/QH ⫹ CLint.
Results
Homology Modeling. Selegiline is a tertiary amine bearing an
N-methyl group. This indicates N-demethylation as a likely metabolic
pathway for the compound by P450 enzymes. Rotation of the C-N
bond could also enable N-depropargylation. Accordingly, homology
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medication during the weeks prior to surgery. None of the patients was a
habitual consumer of alcohol or other drugs. In total, four liver biopsies were
used. Patients’ ages ranged from 62 to 82 years. Hepatocytes were isolated
using a two-step tissue microperfusion technique as described elsewhere
(Gómez-Lechón et al., 1997). Cellular viability, estimated by dye exclusion
test with 0.4% trypan blue in saline, was greater than 90%. Hepatocytes were
seeded on fibronectin-coated plastic dishes (3.5 ␮g/cm2) at a density of 8 ⫻
104 viable cells/cm2 and cultured in Ham’s F-12/Lebovitz L-15 (1:1) medium
supplemented with 2% newborn calf serum, 10 mM glucose, 50 mU/ml
penicillin, 50 ␮g/ml streptomycin, 0.2% bovine serum albumin, and 10 nM
insulin. One hour later, the medium was changed, and after 24 h, cells were
shifted to serum-free, hormone-supplemented medium (10 nM insulin and 10
nM dexamethasone). The medium was changed daily. Under these culture
conditions, cells are metabolically competent (Donato et al., 1995; GómezLechón et al., 1997).
Cytotoxicity Assays. Cytotoxicity was assessed to assure the cells’ viability
and metabolic competence under the conditions used in further incubations.
Hepatocytes were seeded on 96-well microtiter plates, and treatment with
increasing concentrations of selegiline started at 24 h of culture. Cells were
exposed to the compound for the following 48 to 72 h, and the compound was
added daily at the time of medium renewal. Cellular viability was assessed at
the end of the treatments by the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) test as described in detail elsewhere (Borenfreund et
al., 1988). The IC50 and IC10 values, representing the concentrations of the
compound that reduce viability by 50% and 10% with respect to the controls,
were determined from the dose-response curves obtained. The IC50 value was
ⱕ0.125 mM.
7-Ethoxycoumarin O-Deethylase Activity Assay. 7-Ethoxycoumarin Odeethylation is catalyzed by several P450 enzymes (CYP1A2, CYP2A6,
CYP2B6, CYP2C8-9, CYP2E1, and CYP3A4/5; Waxman et al., 1991). Enzyme activity was measured in intact cells (Gómez-Lechón et al., 1997). Cell
monolayers were washed twice with warm PBS, and the assay was initiated by
adding 800 ␮M 7-ethoxycoumarin to the culture medium. Cells were incubated
for 30 min at 37°C, and the reaction was stopped by aspirating the incubation
medium from the plates. To hydrolyze any 7-hydroxycoumarin conjugates, 1
ml of the medium was incubated with ␤-glucuronidase/arylsulfatase (200
Fishman units/1200 Roy units) for 2 h at 37°C. Hydrolysis was stopped by
adding 125 ␮l of 15% trichloroacetic acid and 2 ml of chloroform, and then
shaking the mixture for 10 min at 37°C. After centrifugation (2,000g for 10
min), the organic phase was extracted with 1 M NaOH, and the fluorescence
of the aqueous phase was measured (excitation 368 nm, emission 456 nm) in
a microplate fluorimeter. Activity was expressed as picomoles of 7-hydroxycoumarin formed per minute and per milligram of cellular protein assessed by
the Lowry method (Lowry et al., 1951).
Incubation of Human Hepatocytes with Selegiline. For metabolic studies,
hepatocytes from biopsies were incubated with 62.5 and 125 ␮M selegiline and
hepatocytes from surgical resections with 100 and 500 ␮M selegiline. Treatment was started at 24 h of culture. Medium and cells were subsequently
frozen after 10, 24, and 48 h of continuous incubation with the compound, to
be analyzed for selegiline and its metabolites. Samples from parallel plates
without cells, incubated with medium containing the compound, were also
collected after the same incubation periods.
Preparation and Culture of Precision-Cut Human Liver Slices. The
sources of the tissue culture materials were as described previously (Beamand
et al., 1993; Lake et al., 1998). Samples of human liver (surplus to transplant
requirements) were collected and transported to BIBRA on ice. Tissue cylinders from liver samples were prepared using a 10-mm-diameter motor-driven
tissue coring tool. From the cylinders, liver slices (200 –300 ␮m) were prepared in oxygenated (95% O2/5% CO2) Earle’s balanced salt solution containing 25 mM D-glucose, 50 ␮g/ml gentamicin, and 2.5 ␮g/ml fungizone using a
Krumdieck tissue slicer (Alabama Research and Development Corporation,
Munford, AL). The liver slices were floated onto Vitron Inc. (Tucson, AZ)
type C titanium roller inserts (two slices per insert) and cultured in glass vials
containing 1.7 ml of culture medium in a Vitron dynamic organ incubator. The
culture medium consisted of RPMI 1640 medium containing 5% (v/v) fetal
calf serum, 0.5 mM L-methionine, 1 ␮M insulin, 0.1 mM hydrocortisone
21-hemisuccinate, 50 ␮g/ml gentamicin, and 2.5 ␮g/ml fungizone. Liver slice
cultures were maintained at 37°C in an atmosphere of 95% O2/5% CO2. After
PREDICTION OF IN VIVO SELEGILINE METABOLISM
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FIG. 3. Intrinsic clearances for individual recombinant P450s calculated on the
basis of DMS or MA formation from selegiline.
No measurable activity was found for CYP2D6 for either DMS or MA formation.
modeling indicated that the major biotransformations of selegiline
would occur by dealkylations of the side chain.
Modeling of selegiline in CYP2B6 indicated its similarity with the
likely mode of binding for benzphetamine, which is also Ndemethylated by the enzyme. As shown in Fig. 2A, the substrate is
able to become oriented within the putative active site of the CYP2B6
such that the N-methyl group lies close to the heme iron at a distance
of 3.6 Å. Orientation of selegiline for N-demethylation is effected by
a combination of favorable interactions with complementary amino
acid residues, essentially hydrophobic in nature, which are within the
heme environment. Interactions are with Phe205 (␲-stacking) and
with Ile113, Phe114, and Ala294 (hydrophobic). All four residues
have been the subject of site-directed mutagenesis experiments in
CYP2B subfamily proteins, and typical CYP2B6 substrates bind to
the same residues.
CYP2D6 was also predicted to participate in the metabolism of the
compound (Fig. 2B). According to the model, the enzyme would
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FIG. 2. The modeled P450 interaction of selegiline (black) shows the orientation
of the molecule within the putative active site (gray) of CYP2B6 favoring Ndemethylation (A) and of CYP2D6 favoring N-depropargylation (B).
catalyze predominantly the N-depropargylation of selegiline to methamphetamine. Interaction by CYP2D6 inhibition could also be possible. Interactions are with Asp290 (ion-pairing), Phe473 (␲stacking), and Phe113 (hydrophobic). Of these, the first two have been
mutated in CYP2D6 and have been shown to affect substrate binding.
Also, typical substrates of the enzyme bind to the same residues.
Modeling for CYP1A1, CYP1A2, CYP2A6, CYP2C8, CYP2C9,
CYP2C19, CYP2E1, and CYP3A5 suggested no other form participating in the metabolism of selegiline.
Recombinant Expressed Enzymes. All nine available recombinant P450s were evaluated as catalysts of the metabolism of selegiline, using a 200 ␮M substrate concentration, including kinetic analysis with respect to time and protein concentration. Selegiline was
metabolized by CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C9,
CYP2C19, and CYP2E1 (Fig. 3). CYP2D6 showed hardly any activity. CYP3A4 was not active without added human P450 reductase and
cytochrome b5, which increased the formation of desmethylselegiline
about 5-fold and methamphetamine formation 2- to 5-fold, depending
on the substrate concentration. Both metabolites were produced by all
forms of P450 that were active, and the rate of MA formation
generally exceeded that of DMS. No amphetamine was formed by any
of the forms tested.
CYP2B6 and CYP2C19 were the main forms responsible for the
formation of metabolites, as shown by their intrinsic clearances, i.e.,
Vmax/Km ratios, for both desmethylselegiline and methamphetamine
production (Fig. 3). In the case of CYP2B6, the ratio was almost the
same for the formation of both metabolites, whereas in the case of
CYP2C19, the ratio for MA production was 3 times higher than that
for DMS formation. When the relative amounts of the P450 enzymes
in human liver (see Materials and Methods) were taken into account,
the contributions of CYP2B6 and CYP2C19 to the overall clearance
of selegiline were calculated to be 52.1% and 34.5% of the total,
respectively. In contrast, the role of other P450 enzymes was estimated to be minor. When the contribution of all six active forms,
excluding CYP3A4, to the total hepatic clearance were summed, a
value of 223 l/h was obtained. Studies on selegiline metabolism with
cDNA-expressed P450 enzymes, to reveal the contribution by
CYP3A4, have been continued after the completion of the present
work (Hidestrand et al., 2001).
Human Liver Microsomes. Metabolite pattern and metabolic
rates. The biotransformation of selegiline in microsomes was assessed
both from substrate disappearance and from product formation. Metabolites could be detected at all substrate concentrations tested (20,
1098
SALONEN ET AL.
50, and 200 ␮M). Substrate turnover was appreciable at all concentrations, up to 200 ␮M, with no evidence of saturation (Fig. 4). Two
metabolites, DMS and MA, were readily detected, with trace amounts
of a third (amphetamine) evident at the highest substrate concentration
(200 ␮M) after 60 min. Levels of this metabolite were at the limits of
detection of the assay. Formation rates of the two major metabolites
increased with time for up to 45 min, after which they leveled off.
Formation rates of DMS and MA showed some evidence of beginning
to saturate at 200 ␮M selegiline (Fig. 4). These data were used to
obtain approximate estimates of the kinetic constants for the formation rates of the two metabolites by nonlinear regression analysis.
The apparent Km values for both DMS (99 ␮M) and MA (103 ␮M)
formation in microsomes were the same. In contrast, the maximum
velocity for MA formation (1551 pmol/min per mg of microsomal
protein) was about 2-fold greater than that for DMS formation (733
pmol/min per mg of microsomal protein). Consequently, the calculated intrinsic clearances were 15.1 ␮l/min per mg of microsomal
protein for MA formation and 7.4 ␮l/min per mg of microsomal
protein for DMS formation, respectively. These values scale up to a
total hepatic clearance of 61.2 l/h for MA and 30.0 l/h for DMS, and
a total metabolic CL via these two pathways of 91.2 l/h (Table 3).
Inhibition of P450-Specific Model Activities in Human Liver
Microsomes. Selegiline was an inhibitor of CYP2B6 (IC50 ⫽ 26 ␮M)
and CYP2C19 (IC50 ⫽ 28 –37 ␮M) and a moderate inhibitor (IC50 ⫽
50 –75 ␮M) of three other forms, CYP2D6, CYP2A6, and CYP1A2,
in decreasing order of potency. It had little or no effect on CYP2C9
or CYP3A4 (Table 1). Although differences between the values
measured by two laboratories may be due to specific details and
conditions between model assays and tissues available, the overall
picture of inhibitory potencies was rather similar. The discrepancy
between IC50 values of the two CYP2D6-catalyzed model activities,
dextromethorphan O-demethylase and debrisoquine hydroxylase, is
probably due to kinetic properties of two different substrates.
Inhibition of Microsomal Metabolism of Selegiline by P450Specific Inhibitors. Model inhibitors differentially affected the formation of the main metabolites of selegiline (Table 2). Both furafylline and fluvoxamine inhibited an appreciable component of DMS
formation. Also, methoxsalen inhibited the formation of DMS, but at
Downloaded from dmd.aspetjournals.org at ASPET Journals on October 24, 2016
FIG. 4. Hepatic microsomal metabolism of selegiline.
Substrate disappearance (f), MA formation (), and DMS formation (Œ) are
shown. Results are from a pool of liver samples (n ⫽ 12) and are means of replicate
determinations.
much higher concentrations than needed for the inhibition of
CYP2A6. Fluvoxamine inhibited the formation of MA. Ketoconazole
(CYP3A4) and quercetin (CYP2C8) were the most effective inhibitors
of selegiline metabolism in human liver microsomes, causing 58%
and 47% inhibition of DMS formation and 71% and 55% inhibition of
MA formation, respectively. Quinidine, a CYP2D6 selective inhibitor,
had a very minor inhibitory effect on selegiline metabolism.
Correlation Study. Several significant correlations were found for
selegiline metabolism in nine different human liver samples characterized for their major P450 content. Formation of the two major
metabolites was correlated with total P450 content (DMS: r2 ⫽ 0.58,
P ⬍ 0.02; MA: r2 ⫽ 0.67, P ⬍ 0.01). DMS formation was significantly correlated with MA formation (r2 ⫽ 0.83, P ⬍ 0.001), suggesting the participation primarily of the same P450 enzymes in their
formation. Both DMS (r2 ⫽ 0.64, P ⬍ 0.01) and MA (r2 ⫽ 0.77, P ⬍
0.002) production correlated with phenacetin O-deethylase activity
(CYP1A2). Less marked, but still significant, correlations were found
between MA formation and CYP2C19 (r2 ⫽ 0.52, P ⬍ 0.05) and
between DMS formation and CYP2C9 (r2 ⫽ 0.52, P ⬍ 0.05). DMS
formation showed a significant correlation with CYP2B6 content (r2
⫽ 0.56, P ⬍ 0.05), and formation of both metabolites showed a
significant correlation with CYP2C8 content (DMS: r2 ⫽ 0.69, P ⬍
0.01; MA: r2 ⫽ 0.62, P ⬍ 0.02). MA formation was correlated with
microsomal CYP1A2 content (r2 ⫽ 0.49, P ⬍ 0.05).
Primary Cultured Human Hepatocytes. Cytotoxicity and induction potential of selegiline. Selegiline was incubated with human
hepatocytes at concentrations from 30 to 1,000 ␮M for 48 to 72 h, to
determine its cytotoxicity by the MTT assay. Under these conditions,
the compound showed minimal cell toxicity at concentrations below
125 ␮M.
The potential P450 inducing effects of selegiline were evaluated
after 48 –72 h incubation, by measuring 7-ethoxycoumarin O-deethylase activity. Selegiline did not increase enzyme activity. Rather, the
drug caused a dose-dependent inhibition (40 – 60% reduction) of
7-ethoxycoumarin O-deethylase activity.
Rate of Elimination and Metabolite Production. Two concentrations of selegiline (62.5 and 125 ␮M) were incubated for 10, 24, or
48 h with human hepatocytes originating from surgical biopsies. The
cells produced considerable amounts of DMS and MA. In several
experiments, the formation rate of MA was 2- to 3-fold greater than
the formation rate of DMS. Amphetamine was formed to a lesser
extent. Total recovery of the compounds (SEL ⫹ DMS ⫹ MA ⫹ A)
from the incubate clearly decreased with increasing time.
The kinetics of selegiline elimination were evaluated on the basis of
substrate disappearance, and an “initial” velocity of 13.7 nmol/h per
one million cells was obtained. This value corresponds to a total
hepatic clearance of about 16.1 l/h. However, the rate of selegiline
metabolism was determined over a 10-h period, and true initial conditions were probably lost within the first hour or two. Clearance
estimation based on the sum of metabolite formation yielded a much
lower value (Table 3). This may be related to the recovery problems
mentioned above.
Both DMS and MA, but not amphetamine, were detected as biotransformation products of selegiline in hepatocytes isolated from
surgical liver resections. However, the overall metabolism in these
cells was low, and no useful clearance estimate could be calculated.
This may also be related to recovery problems, in this particular case.
Precision-Cut Human Liver Slices. Selegiline underwent biotransformation in human liver slices at all substrate levels tested. Both
DMS and MA were produced at appreciable rates, and the amounts
formed increased with substrate concentration, but no time dependence was observed after 0.5 h of incubation, suggesting that reaction
1099
PREDICTION OF IN VIVO SELEGILINE METABOLISM
TABLE 1
Effect of selegiline on P450-model activities in human liver microsomes
Model substrates and reference inhibitors are listed in parentheses.
IC50
Cytochrome P450
Lab 1
Lab 2
Reference Inhibitor
SEL/Reference
Ratio
␮M
CYP1A2
(Ethoxyresorufin O-deethylation)
CYP2A6
(Coumarin 7-hydroxylation)
CYP2B6
(Bupropion hydroxylation)
CYP2C9
(Tolbutamide methylhydroxylation)
CYP2C19
(S-Mephenytoin 4⬘-hydroxylation)
CYP2D6
75
500
67
26
not tested
670
800
28
37
580
(Dextromethorphan
O-demethylation)
430
50
(Debrisoquine
hydroxylation)
2,000
825
1,300
TABLE 2
Inhibition of microsomal metabolism of selegiline by P450-specific inhibitors
Target P450
Inhibitor
CYP1A2
CYP2A6
CYP2C8
CYP2C9
CYP2C19
CYP2D6
CYP2E1
CYP3A4
Furafylline
Coumarin
Quercetin
Sulfaphenazole
S-Mephenytoin
Quinidine
Pyridine
Ketoconazole
Highest
Concentrations
Tested
␮M
5
50
30
30
500
10
20
20
DMS Formation
MA Formation
% inhibition
26
11
47
15
Negligible
11
19
58
39
20
55
10
16
18
11
71
equilibrium had been reached before that point, with some clearance
of the primary products by secondary metabolism. Consistent with
this, detectable levels of amphetamine were observed, particularly at
the highest substrate concentration.
Kinetics were evaluated on the basis of the sum of the formation
rates of the two metabolites. The velocity concentration curves
(Eadie-Hofstee plot) indicated biphasic kinetics. Apparent kinetic
parameters were calculated for the first (high affinity) phase only.
This resulted in an apparent Km of 4 ␮M and Vmax of 14 pmol/min per
mg liver slice whole homogenate protein. The corresponding intrinsic
clearance was 3.5 ␮l/min per mg liver slice whole homogenate protein. This scales up to a total (hepatic) metabolic clearance of 36.5 l/h.
Discussion
Elucidation of the Identity of Metabolites and the Metabolic
Route. The primary metabolites of selegiline in humans are desmethylselegiline and methamphetamine (Reynolds et al., 1978; Shin,
1997). Amphetamine is a secondary product formed by dealkylation
of either of the two compounds (Fig. 1). These three metabolites have
been detected in human urine, blood plasma, and serum, as well as in
cerebrospinal fluid (Reynolds et al., 1978; Heinonen et al., 1989;
Shin., 1997). Methamphetamine is the most abundant metabolite
observed in vivo. In vitro, conversion of selegiline to methamphetamine by rat liver microsomes also occurred at a high rate (Yoshida
et al., 1986).
0.045
(Furafylline)
0.7
(Methoxsalen)
not available
1,667
96
4.1
(Sulfaphenazole)
67
(Omeprazole)
0.41
(Quinidine)
195
4.7
(Pyridine)
0.34
(Ketoconazole)
91
0.42
122
2,426
In the current study, all of the in vitro systems tested correctly
produced the two primary metabolites from selegiline. Since the
identity of the test compound was originally not revealed to the
participating laboratories, other than to the molecular modeling group,
this group was the only one in a position to make any predictions on
the structure of the metabolites. Modeling correctly predicted the sites
of metabolic attack and the metabolite structures. It predicted both
methamphetamine and N-desmethylselegiline as the primary P450
products. Methamphetamine was the most abundant product with
cDNA-expressed enzymes, microsomes, hepatocytes, and liver slices,
in agreement with the in vivo data.
The secondary metabolite, amphetamine, was not detected when
using recombinant enzymes and was produced in only trace amounts
by the other systems. This is not surprising in view of the reaction
rates of the primary pathways. Hydroxylated amphetamines, which
have also been detected as secondary metabolites of selegiline in vivo
(Yoshida et al., 1986; Shin, 1997), were not observed in the studies
reported here. Since the analytical method used includes extraction
into an organic solvent, these compounds could have escaped detection, as a consequence of their polarity. However, no hydroxylated
products were found in an earlier study in which selegiline was
incubated with rat liver microsomes (Yoshida et al., 1986). Because
these products would require the involvement of three sequential
reactions, significant amounts would not be anticipated in vitro.
Elucidation of the Metabolic Rate and Prediction of in Vivo
Clearance. In humans, selegiline is eliminated exclusively by biotransformation, resulting in a high systemic clearance. The reported
clearance, 236 l/h (Heinonen et al., 1994), exceeds the maximum
metabolic capacity of two parallel operating hepatic reactions. The
theoretical maximum clearance by formation of desmethylselegline
and methamphetamine would be equal to twice the hepatic blood
flow; i.e., approximately 2 ⫻ 90 l/h. Some extrahepatic metabolism of
selegiline by P450s has been observed in rats (Yoshida et al., 1987),
and it may be that this also contributes to the elimination of the drug
in humans. Since the drug concentration in plasma is very low, after
an oral dose of 10 mg, the maximum level is approximately 10 nM
(Heinonen et al., 1994); binding to monoamine oxidase type B also
makes a minor contribution to the observed overall elimination rate.
All of the in vitro techniques indicated that selegiline is readily
Downloaded from dmd.aspetjournals.org at ASPET Journals on October 24, 2016
CYP2E1
(Chlorzoxazone 6-hydroxylation)
CYP3A4/5
(Testosterone 6␤-hydroxylation)
350
1100
SALONEN ET AL.
TABLE 3
Estimates of the metabolic rate in various in vitro systems
CLh
Candidate System
CLh (Summed)a
Assumptions
DMS
MA
A
95.7
30
1.38
na
128.2
61.2
3.56
na
na
na
0.25
na
SEL
l/h
Recombinant expressed enzymes
Liver microsomes
Hepatocytes
Liver slices
Relative content (BD Gentest)
45 mg microsomal protein/g liver
120 million hepatocytes/g liver
200 mg total protein/g liver
na
na
16.1
na
223.8
91.2
5.2
36.5
na, not available.
a
DMS ⫹ MA ⫹ A.
barbital. Thus, enzymes of the CYP2B subfamily (Waxman and
Azaroff, 1992) might be involved.
In humans, it has been suggested that CYP2D6 is the enzyme
responsible for selegiline demethylation. This was based on findings
with human recombinant CYP2D6 microsomes but was not supported
by the model of CYP2D6 used by the authors (Grace et al., 1994).
They proposed that the discrepancy was explicable by an atypical
reaction mechanism. Similar activity of CYP2D6 was reported in
another study with microsomes from CYP2D6 cDNA-expressing cells
(Bach et al., 2000). In the present study, homology modeling indicated
an interaction of selegiline with CYP2D6 that could also lead to
inhibition of the enzyme. In the recombinant expressed enzyme system, activity of this form of P450 was below the limit of detection. No
support for CYP2D6 participation was obtained in either the microsomal inhibition or correlation studies: quinidine did not significantly
inhibit DMS or MA formation (Table 2), and the IC50 of SEL for
CYP2D6 was at least 120-fold higher than that of the reference
inhibitor (Table 1).
There was no correlation between either CYP2D6 content or activity with the rates of formation of either metabolite. A similar lack
of correlation with CYP2D6 was found by Jurima-Romet et al.
(2000). In humans in vivo, the CYP2D6 polymorphism was shown to
have no effect on the metabolism of selegiline, the kinetics of the
compound being very similar in poor and extensive metabolizers of
debrisoquine (Scheinin et al., 1998). Hence, overall, it appears very
unlikely that CYP2D6 plays any significant role in the biotransformation of selegiline in humans.
Studies with both microsomes and recombinant expressed human
P450s suggested a role for CYP2C19 in selegiline metabolism. Clear
evidence for a contribution from this P450 form was obtained using
recombinant expressed enzymes, CYP2C19 being particularly active
in depropargylation to produce MA. Additional evidence for a contribution from CYP2C19 was obtained in studies of the inhibition of
model reactions (Table 1), selegiline having a lower IC50 value for
this enzyme than the reference inhibitor, and the existence of significant correlation between MA formation and CYP2C19 content. The
latter result is consistent with data from recombinant enzymes that
CYP2C19 is more active in depropargylation than demethylation of
selegiline. Data from studies in vivo in extensive metabolizers and
poor metabolizers for CYP2C19 (Laine et al., 2001) support a modest
contribution of this enzyme to the metabolism of selegiline, via the
depropargylation pathway. Hence, although molecular modeling did
not identify CYP2C19 as one of the forms of P450 involved in
selegiline metabolism, there is good evidence that this enzyme does
contribute to the (primary) metabolism of selegiline in vivo, albeit
normally only to a minor extent.
Molecular modeling identified CYP2B6 as one of the forms of
P450 involved in selegiline metabolism, particularly via demethylation to produce DMS. Correlation studies with hepatic microsomal
fractions also suggested a contribution of CYP2B6 to DMS formation.
Downloaded from dmd.aspetjournals.org at ASPET Journals on October 24, 2016
metabolized by P450 enzymes. For the reasons outlined above, predicted clearances should be compared with the theoretical value of
hepatic intrinsic CL rather than the total body CL. Upscaling of the
intrinsic clearance resulted in an underestimate of the in vivo clearance for all in vitro systems except the recombinant enzymes where,
instead, a slight overestimate was obtained (Table 3). In the case of
microsomes, hepatocytes, and liver slices, biotransformations in addition to those quantified may take place. Thus, measurement of
substrate disappearance, rather than the formation of individual metabolites, should give a more valid estimate of the drug clearance.
However, any nonspecific loss of substrate would bias this estimate.
In fact, an acceptable estimate of in vivo clearance was achieved from
the sum of the rates of formation of the two main metabolites in
human liver microsomes (Table 3). Hepatocytes performed less satisfactorily, most probably because the incubation time was too long,
and hence, it was not possible to obtain an accurate estimate of initial
rates when the measurements were made at the end of the incubation
period. Over this interval, it is very likely that secondary reactions had
consumed some of the primary metabolites produced, reducing the
accuracy of the estimation of reaction rate and clearance.
The same mechanisms may have influenced, in part, the results
obtained with liver slices, in which metabolite formation gave a low
estimate of clearance (Table 3), although the incubation time was
shorter and hence there would be less opportunity for secondary
metabolism. It is possible that with a rapidly metabolized compound
such as selegiline, the surface cell layers of the slice exhaust the
substrate before it reaches the inner cell layers. Consequently, the
observed total metabolic rate will be lower than with a similar mass of
freely accessible enzymes, e.g., in microsomes, resulting in a reduced
clearance estimate. Differences between surface and inner layers of
cells in substrate access may well also explain the observed biphasic
kinetics of selegiline metabolism in liver slices.
Indeed, despite the relative underestimation of total in vivo CL, all
of the in vitro systems tested successfully classified the compound
into the correct clearance category; i.e., all showed selegiline to be a
high clearance drug. In addition, it is anticipated that these systems
could correctly rank the clearance of a series of closely related drug
candidates, inasmuch as this depends on relative rather than absolute
predictions. In practice, this result would be sufficient for screening
purposes, and more accurate clearance values would be obtained
during further drug development.
Identification of the Participating P450 Isoforms. Prediction of
pharmacokinetic drug interaction potential as well as of individual
variability in drug response relies on the identification of the P450
enzymes involved in the metabolism of the drug. In the case of
selegiline, characterization of the metabolizing P450s remains to be
completed (see Taavitsainen et al., 2000; Hidestrand et al., 2001).
Yoshida et al. (1986), in addition to proving that the conversion of
selegiline to methamphetamine in rat liver microsomes is catalyzed by
the P450 system, showed that the reaction was inducible by pheno-
1101
PREDICTION OF IN VIVO SELEGILINE METABOLISM
these conclusions, no metabolism-related drug interactions involving
selegiline have been reported to date.
Conclusions. When comparing the results of the present study to
the existing in vivo data in humans (Heinonen et al., 1994; Laine et
al., 1999), it can be concluded that, in spite of the variable numeric
values for predicted intrinsic clearance, recombinant enzymes, liver
microsomes, hepatocytes, and liver slices were all able to predict the
metabolic lability, i.e., the high metabolic clearance, of selegiline.
Homology modeling correctly predicted the primary metabolic reactions and the sites of metabolism. Indeed, all of the other systems
enabled the correct identification of the major metabolic products.
Although uniform prediction of the relative contribution of different
P450s to desmethylselegiline and metamphetamine formation, the
primary metabolic reactions of selegiline, was not obtained, there was
a reasonable degree of agreement among them. All of the systems
utilized (homology modeling, recombinant enzymes, and microsomes) suggested the participation of several P450 enzymes and
(correctly) predicted low interaction potential in vivo. Although none
of the techniques studied here was alone able to predict all aspects of
the metabolic and kinetic behavior of selegiline in vivo, with an
integrated package, all significant characteristics were predictable. It
is reasonable to suggest that such an approach would be the best
procedure for new chemical entity metabolism screening in general.
When a particular aspect of metabolism needs to be investigated
further, a single in vitro system, appropriate to the issue of concern,
can be selected on the basis of the type of information reported here.
Acknowledgments. We wish to acknowledge the contributions of
the other members of the EUROCYP project: Dieter Paul, Rainer
Klocke (Fraunhofer Institute, Hannover, Germany), Tommy B.
Andersson (AstraZeneca, Mölndal, Sweden), and Gisela Backfisch
(Roche Diagnostics, Mannheim, Germany). We also thank Orion
Pharma for providing selegiline and its metabolites.
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Selegiline inhibited moderately the hydroxylation of a CYP2B6 substrate, bupropion (Table 1). Recombinant expressed CYP2B6 exhibited both high affinity and a high capacity to metabolize selegiline,
with similar kinetic constant for the formation of DMS and MA, thus
supporting the participation of CYP2B6 in the formation of these two
metabolites. The kinetics of CYP2B6 are such that it is predicted that
this would be the major form of P450 involved in its metabolism
(present study and Hidestrand et al., 2001). However, CYP2B6 expression and activity are highly variable, with appreciable expression
in only 20% of the population (Edwards et al., 1998; Ekins et al.,
1998; Ekins and Wrighton, 1999; Gervot et al., 1999). Recent studies
have established that much of this variability has a genetic origin
(Lang et al., 2001). Hence, the role of CYP2B6 in vivo as a determinant of the kinetics and dynamics of selegiline within the population
as a whole remains to be determined.
Studies with human liver microsomes implicated CYP2C8 in the
metabolism of selegiline. There were significant correlations between
CYP2C8 content and the formation rates of both MA and DMS.
Similarly, quercetin, a selective inhibitor of CYP2C8 and CYP1A2
(Dierks et al., 2001), inhibited both microsomal depropargylation and
demethylation of selegiline to a greater extent than furafylline, a very
selective inhibitor of CYP1A2 (Sesardic et al., 1990; Dierks et al.,
2001) Recombinant expressed CYP2C8 exhibited only low activity
toward selegiline (Hidestrand et al., 2001). Overall, these data suggest
that CYP2C8 may play a minor role in selegiline oxidation.
There was also a significant correlation between CYP1A2 content
of hepatic microsomal samples and MA formation. In addition,
furafylline inhibited the microsomal formation of both MA and DMS,
with a greater effect on MA formation, and recombinant expressed
CYP1A2 was active in the formation of both metabolites but, again,
was more active in MA formation. Hence, the evidence would suggest
a modest contribution of CYP1A2 to the metabolism of selegiline,
particularly in MA formation.
There was no indication from molecular modeling for the involvement of CYP3A4 in the metabolism of selegiline. Similarly, there was
no correlation between microsomal CYP3A4 content and selegiline
metabolite formation, nor did selegiline significantly inhibit CYP3A4dependent reactions. Recombinant CYP3A4 itself was inactive but, in
the presence of human cytochrome P450 reductase and cytochrome
b5, showed modest activity in both MA and DMS formation
(Hidestrand et al., 2001). Ketoconazole inhibited an appreciable component of selegiline turnover by human liver microsomes, and in an
earlier study, selegiline metabolism by human liver microsomes was
reduced by CYP3A inhibitors (Wacher et al., 1996). However, although ketoconazole is a relatively selective inhibitor of CYP3A4, at
the concentrations used, it also inhibits CYP1A2, CYP2B6, CYP2C8,
and CYP2C19 (Dierks et al., 2001; Zhang et al., 2002). Thus, there is
little evidence for a significant contribution from CYP3A4 to the
biotransformation of selegiline.
Predicted Interaction Potential. From the present data, it is apparent that the metabolism of selegiline in human liver to desmethylselegiline and metamphetamine is a multiple enzyme process, involving at least CYP1A2, CYP2B6, CYP2C19, and possibly
CYP2C8. The participation of several different forms of P450 in the
elimination of the drug reduces the likelihood of possible drug interactions affecting selegiline clearance in humans. In contrast, selegiline
is an effective inhibitor of CYP2C19 and hence could possibly reduce
the clearance of drugs dependent on this enzyme for their elimination.
However, systemic levels of selegiline remain in the low nanomolar
range (Heinonen et al., 1994), and micromolar concentrations would
be required to inhibit CYP2C19. Thus, it is highly unlikely that any
interaction would arise by this mechanism either. Consistent with
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