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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 Hepatología 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.)
(Received December 3, 2002; accepted May 30, 2003)
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Abstract |
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 Top Abstract Materials and MethodsResultsDiscussionReferences |
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). 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 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.
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Materials and Methods |
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TopAbstractMaterials and MethodsResultsDiscussionReferences |
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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 µl 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 µM 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 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 6ß-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 µM 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 µM) 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 µM selegiline; incubation time, 30 min). The following inhibitors were used: CYP1A2, furafylline (1, 2, or 5 µM); CYP2A6, coumarin (10, 20, or 50 µM); CYP2C8, quercetin (3, 10, 30 µM); CYP2C9, sulfaphenazole (3, 10, or 30 µM); CYP2C19, S-mephenytoin (100, 200, or 500 µM); CYP2D6, quinidine (1, 5, or 20 µM); CYP2E1, pyridine (1, 5, or 20 µM); and CYP3A4, ketoconazole (1, 5, or 20 µM). 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 x
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
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 µg/cm2) at a density
of 8 x 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 µg/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;
Gómez-Lechón 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 
0.125 mM.
7-Ethoxycoumarin O-Deethylase Activity Assay.
7-Ethoxycoumarin O-deethylation 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 µM 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
ß-glucuronidase/arylsulfatase (200 Fishman units/1200 Roy units) for 2 h
at 37°C. Hydrolysis was stopped by adding 125 µl 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 µM selegiline and hepatocytes from surgical resections with 100 and 500 µM 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 µm) were prepared in oxygenated (95%
O2/5% CO2) Earle's balanced salt solution containing 25
mM D-glucose, 50 µg/ml gentamicin, and 2.5 µg/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 µM insulin, 0.1 mM hydrocortisone
21-hemisuccinate, 50 µg/ml gentamicin, and 2.5 µg/ml fungizone. Liver
slice cultures were maintained at 37°C in an atmosphere of 95%
O2/5% CO2. After 30 min, the medium was changed to fresh
serum-free RPMI 1640 medium containing 0.5 mM L-methionine, 1 µM
insulin, 0.1 mM hydrocortisone 21-hemisuccinate and 0 to 500 µM 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://www.gentest@bd.com.
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 x 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 · CLint/QH + CLint.
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Results |
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TopAbstractMaterials and MethodsResultsDiscussionReferences |
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Modeling of selegiline in CYP2B6 indicated its similarity with the likely
mode of binding for benzphetamine, which is also N-demethylated 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.
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CYP2D6 was also predicted to participate in the metabolism of the compound
(Fig. 2B). According to the
model, the enzyme would 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 µM 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.
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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, 50, and 200 µM). Substrate turnover was appreciable at all concentrations, up to 200 µM, 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 µM) 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 µM 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.
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The apparent Km values for both DMS (99 µM) and MA (103 µM) 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 µl/min per mg of microsomal protein for MA formation and 7.4 µl/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).
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Inhibition of P450-Specific Model Activities in Human Liver Microsomes. Selegiline was an inhibitor of CYP2B6 (IC50 = 26 µM) and CYP2C19 (IC50 = 28–37 µM) and a moderate inhibitor (IC50 = 50–75 µM) 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.
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Inhibition of Microsomal Metabolism of Selegiline by P450-Specific 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 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.
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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 µM 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 µM.
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 µM) 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 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 µM and Vmax of 14 pmol/min per mg liver slice whole homogenate protein. The corresponding intrinsic clearance was 3.5 µl/min per mg liver slice whole homogenate protein. This scales up to a total (hepatic) metabolic clearance of 36.5 l/h.
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Discussion |
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; 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). 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 x 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 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 phenobarbital. 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. 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 CYP3A4-dependent 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 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.
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Acknowledgments |
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Footnotes |
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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. 
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{at}orionpharma.com
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References |
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-dimethyl-N-propynylphenethylamine,
by cytochrome P450 2D6. Chem Res Toxicol
7: 286-290.[CrossRef][Medline]
), MA formation (
), and DMS formation
(
) are shown. Results are from a pool of liver samples (n =
12) and are means of replicate determinations.