Repurposing Resveratrol and Fluconazole to Modulate Human Cytochrome P450-Mediated Arachidonic Acid Metabolism

Article abstract of DOI:10.1021/acs.molpharmaceut.5b00873

Cytochrome P450 (P450) enzymes metabolize arachidonic acid (AA) to several biologically active epoxyeicosatrienoic acids (EETs) and hydroxyeicosatetraenoic acids (HETEs). Repurposing clinically-approved drugs could provide safe and readily available means

Full text of DOI:10.1021/acs.molpharmaceut.5b00873

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Article
Repurposing Resveratrol and Fluconazole to Modulate Human
Cytochrome P450-Mediated Arachidonic Acid Metabolism
Ahmed A El-Sherbeni, and Ayman O.S. El-Kadi
Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.5b00873 • Publication Date (Web): 26 Feb 2016
Downloaded from http://pubs.acs.org on February 28, 2016
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Abstract
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Cytochrome P450 (P450) enzymes metabolize arachidonic acid (AA) to several biologically-
active epoxyeicosatrienoic acids (EETs) and hydroxyeicosatetraenoic acids (HETEs).
Repurposing clinically-approved drugs could provide safe and readily-available means to control
EETs and HETEs levels in humans. Our aim was to determine how to significantly and
selectively modulate P450-AA metabolism in human by clinically-approved drugs. Liquid-
chromatography-mass-spectrometry was used to determine the formation of 15 AA metabolites
by human recombinant P450 enzymes, as well as human liver and kidney microsomes.
CYP2C19 showed the highest EET-forming activity, while, CYP1B1 and CYP2C8 showed the
highest mid-chain HETE-forming activities. CYP1A1 and CYP4 showed the highest subterminal-
and 20-HETE-forming activity, respectively. Resveratrol and fluconazole produced the most
selective and significant modulation of hepatic P450-AA metabolism, comparable to
investigational agents. Monte Carlo simulations showed that 90% of human population would
experience a decrease by 6-22%, 16-39% and 16-35% in 16-, 18- and 20-HETEs formation,
respectively, after 2.5 g daily of resveratrol, and by 22-31% and 14-23% in 8,9- and 14,15-EETs
formation after 50 mg of fluconazole. In conclusion, clinically-approved drugs can provide
selective and effective means to modulate P450-AA metabolism, comparable to investigational
drugs. Resveratrol and fluconazole are good candidates to be repurposed as new P450-based
treatments.
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Keywords: Human cytochrome P450; arachidonic acid; epoxyeicosatrienoic acids;
hydroxyeicosatetraenoic acids; Monte Carlo simulation
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Introduction
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Cytochrome P450 (P450) is a group of hemothiolate enzymes that are ubiquitous in
almost all biological systems. P450 is believed to be evolved about 1.5 billion years ago,1 and
their function was then to protect the organism from the increasing free oxygen concentration in
earth atmosphere.2 Thereafter, P450 was adapted to mediate the biosynthesis of several
endogenous compounds, besides their key exogenous role in inactivating xenobiotics. It has
been recently reported that P450 is able to mediate the metabolism of arachidonic acid (AA) to
give a new group of eicosanoids, the P450-mrdiated AA metabolites.3 This new pathway of AA
metabolism has garnered an increasing attention due to two factors; first, the evolutionary
conservation and abundance of P450 enzymes in nature.4 Second, P450-derived AA
metabolites exhibit potent and multifaceted roles in the regulation of several biological
functions.3, 5
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P450 enzymes mediate mid-chain and terminal oxygen insertion to AA to give several
epoxy- and hydroxy-metabolites.6 There are 4 epoxy-AA, namely 5,6-, 8,9-, 11,12- and 14,15-
epoxyeicosatrienoic acids (EETs), and 11 hydroxy-AA, namely 5-, 8-, 9-, 11-, 12-, 15-, 16-, 17-,
18-, 19- and 20-hydroxyeicosatetraenoic acids (HETEs). Among these metabolites, EETs and
20-HETE are the most studied metabolites.7 EETs are reported to exhibit vasodilatory, anti-
platelet, anti-inflammatory, antinociceptive, fibrinolytic, vascular smooth muscle anti-migratory
and angiogenic activities.8-10 In contrast to EETs, 20-HETE is reported to exhibit vasoconstrictor,
pro-inflammatory and pro-fibrotic activities.11, 12 However, contrary for EETs and 20-HETE, the
other HETEs are generally overlooked despite their reported biological activities. These HETEs
are divided into mid-chain HETEs (mHETEs), namely 5-, 8-, 9-, 11-, 12- and 15-HETEs, and
subterminal HETEs, namely 16-, 17-, 18-and 19-HETEs.7 It has been reported that subterminal
HETEs induce renal vasodilation and inhibit neutrophil adhesion, in addition to the suggested
role of 19-HETE as the endogenous antagonist of 20-HETE.13-15 While mHETEs have been
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reported to induce cellular hypertrophy, inflammation and fibrosis.16, 17 Several studies have
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shown the substantial association between the alterations in P450-derived AA metabolites
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levels and several pathological conditions.3,
We have previously reported that heart
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damage, induced by arsenic, isoproterenol, doxorubicin or pressure-overload, is accompanied
by consistent alterations in P450-mediated AA-metabolism.19-22 We also showed that the
correction of these alterations provides protection or even reversal of the induced heart damage
in rats and mice.19, 20, 23
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Because of the long recognition of P450 as the main xenobiotic inactivators, several
clinically-approved drugs have been identified to exhibit a long-considered unwanted effect of
inhibiting cytochrome P450 activity. Repurposing these clinically-approved drugs would provide
safe and rapid mean to control EETs and HETEs levels in humans by pharmacological
intervention. Therefore, it is imperative to determine which P450 enzyme is to be targeted based
on AA-metabolizing activity and metabolic profile. However, only sparse studies have tried to
compare P450 enzymes with regard to AA-metabolism under the same experimental
conditions.24 Also, it is yet to investigate the effect of P450 inhibition by these clinically-approved
drugs, and whether their effects would be maintained in humans after safe doses of these
drugs.
In the current study, our aim was to identify clinically-approved drugs and their dosage
that would significantly and selectively modulate P450-mediated AA metabolism in humans. We
compared between several human recombinant P450 enzymes under the same conditions that
best imitate in vivo environment with respect to their AA-metabolizing activity and metabolic
profile. Thereafter, we characterized the effects of P450 inhibition on hepatic AA metabolism by
clinically-approved drugs, as well as by investigational non-clinically-approved agents. Finally,
we combined the kinetics of P450 inhibition with the pharmacokinetic data of clinically-approved
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drugs to perform Monte Carlo simulations, in order to predict selectivity and magnitude of
modulating P450-AA metabolism after safe doses given to humans.
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Materials and methods
Materials
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Butylated hydroxytoluene, formic acid, nicotinamide adenine dinucleotide phosphate
(NADPH), triethylamine, α-naphthoflavone (α-NF), resveratrol (Res), fluconazole (Flu),
ticlopidine (Tic), sertraline (Ser) and danazol (Dan) were purchased from Sigma-Aldrich
Chemical Co. (St. Louis, MO). Propylthiouracil (PTU), MS-PPOH, HET0016, peroxide-free AA
and AA metabolites standards: 5,6-, 8,9-, 11,12- and 14,15-EET, and 5-, 8-, 9-, 11-, 12-, 15-,
16-, 17-, 18-, 19-and 20-HETE, as well as internal standards (14,15-EET-D11 and 15-HETE-D8)
were purchased from Cayman Chemical (Ann Arbor, MI). High-performance-liquid-
chromatography-grade acetonitrile, methanol, isopropanol, water and ethyl acetate were
purchased from EM Scientific (Gibbstawn, NJ). Human CYP1A1-, CYP1A2-, CYP1B1-,
CYP2B6-, CYP2C8-, CYP2C9, CYP2C18-, CYP2C19-, CYP2E1-, CYP2J2-, CYP3A4-,
CYP4A11-, CYP4F2-, CYP4F3A-, CYP4F3B- and CYP4F12-containing cell microsomes
supplemented with NADPH-P450 reductase (Supersomes) were obtained from Gentest
(Woburn, MA), whereas cytochrome b5 and NADPH-P450 reductase were from Oxford
Biomedical Research (Oxford, MI). Pooled human liver and kidney microsomes were obtained
from BioreclamationIVT (Baltimore, MD). Other chemicals were purchased from Fisher Scientific
Co. (Toronto, ON, Canada).
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Arachidonic acid metabolism
AA metabolism mediated by recombinant human P450 enzymes was characterized in
incubation mixture containing 3 mM magnesium chloride hexahydrate, NADPH-P450 reductase,
cytochrome b5, P450 enzyme and AA (75 µM) in 100 mM potassium phosphate buffer (pH 7.4)
to form a final volume of 300 µL. Preliminary incubations were performed to ensure that the
formation of AA metabolites was linear with respect to incubation time and protein content under
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assay conditions. NADPH reductase or cytochrome b5 alone did not mediate the formation of
P450-derived AA metabolites.
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AA was incubated with 50 pmol/mL of CYP2C19 or CYP4A11 for 15 min, 50 pmol/mL of
CYP4F2, CYP4F3A, CYP4F3B or CYP4F12 for 20 min, 100 pmol/mL of CYP1A1 or CYP1A2
for 15 min, or 100 pmol/mL of CYP1B1, CYP2B6, CYP2C8, CYP2C9, CYP2C18, CYP2E1,
CYP2J2 or CYP3A4 for 20 min. Cytochrome b5 was added to achieve molar ratio of 1:1 with
P450 enzyme.25, 26 Also, same experiment was repeated for CYP4A11, CYP4F2 or CYP4F3B in
the presence of 0.01-1000 µM Res. With respect to human microsomal-mediated AA-
metabolism, AA (7.5, 75 and 750 µM) was incubated with 0.5 mg/mL of liver or kidney
microsomes for 30 min in 100 mM potassium phosphate buffer (pH 7.4) containing 3 mM
magnesium chloride hexahydrate to form a final volume of 300 µL. Also, AA (75 µM) incubation
with liver microsomes was performed in the absence or presence of different concentrations of
each of the following agents: α-NF (40 and 160 nM), Res (0.03-1000 µM), MS-PPOH (5 and 50
µM), Flu (0.1 to 375 µM), Tic (10 and 100 µM), Ser (30 and 300 µM), Dan (20 and 200 nM),
HET0016 (50 nM and 1 µM) and PTU (0.1 and 1 mM). In P450 inhibition experiments, all
samples contained a fixed concentration of 0.1% of dimethylsulfoxide, and inhibitors were
incubated with recombinant enzymes or microsomes for 15 min on ice before the addition of AA.
For both experiments, recombinant enzymes and microsomes, background control samples
containing the same corresponding incubation mixture but without NADPH were prepared.
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After a 5-min pre-equilibration period, the reaction was initiated by the addition of the
cofactor NADPH (final concentration 2 mM) and terminated by the addition of 600 µL ice-cold
acetonitrile containing 0.01% formic acid and 0.001% butylated hydroxytoluene. Incubations
were conducted at 37°C in a shaking water bath (90 rpm). The incubation mixtures were double
extracted with 1 ml ethyl acetate; thereafter the organic extracts were combined, evaporated to
dryness and reconstituted in 40 µL acetonitrile containing 0.01% formic acid.
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Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS)
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AA and its metabolites were analyzed using Liquid chromatography-electrospray
ionization-mass spectrometry (LC-ESI-MS) (Waters Micromass ZQ 4000 spectrometer) as
previously described.27 The mass spectrometer was run in negative ionization mode with single
ion monitoring: m/z= 303 for AA, m/z = 319 for AA metabolites and m/z = 327 and 330 for
internal standards, 15-HETE-D8 and 14,15-EET-D11, respectively. The nebulizer gas was
acquired from an in house high purity nitrogen source. The temperature of the source was set at
150 °C, and the capillary and cone voltage were 3.51 kV and 25 V, respectively. A gradient
separation was performed on a reverse phase C18 column (Alltima HP, 150 × 2.1 mm) at 35°C.
Mobile phase A consisted of water with 0.01% formic acid and 0.005% triethylamine (v/v),
whereas mobile phase B consisted of 8% methanol, 8% isopropanol and 84% acetonitrile with
0.01% formic acid and 0.005% triethylamine (v/v). Samples were subjected to linear gradient
elution at a flow rate of 200 µL/min, as follows: 60 to 48% in 4 min, held isocratically at 48% for
24 min, 48 to 35% in 11 min, 35 to 0% in 11 min, and finally held isocratically at 0% for 7 min of
mobile phase A. The concentrations of the AA metabolites were calculated by comparing their
corresponding analyte/reference response ratio based on peak area to calibration standards.
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Statistical analysis
Inhibitor concentration required for 50% inhibition (IC50) and maximal inhibition (Imax
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were determined by Enzyme Kinetics module from GraphPad Prism (version 5.0; GraphPad
software, San Diego, CA). Monte Carlo simulation is a highly valued tool to bridge
pharmacokinetic data with pharmacodynamic data, in order to make a prediction about the
fraction of human population that would attain the targeted biological response.28, 29 Accordingly,
we performed Monte Carlo simulations (10,000 subjects) to calculate the expected residual AA-
metabolizing activity in 90% of human population using random number generation module from
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SigmaPlot, version 11 (Systat Software, San Jose, CA, USA). Log-normal distribution was used
to describe the dispersion of human plasma concentrations, as well as the parameters of
enzyme inhibition kinetics around the mean values; whereas uniform distribution was used with
the ratios of hepatic tissue to plasma concentration. The following equation was stochastically
solved by Monte Carlo method:
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ꢌꢍꢆꢎ
ꢀꢁꢂꢃꢄꢅꢆꢇ ꢆꢈꢉꢃꢊꢃꢉꢋ = (100 − ꢌꢍꢆꢎ) +
1 + 10ꢏꢐꢑ[ꢒꢓꢔꢕꢖ:ꢗꢒꢘꢙꢚꢘ ꢖꢘꢛꢓꢐ.ꢜꢚꢘꢝ]ꢞꢏꢐꢑ[ꢟꢜꢠꢡ]
Throughout the paper, data are presented as mean SE. One-way analysis of variance
followed by a Tukey’s post hoc test was used. A result was considered statistically significant
where p< 0.05.
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Results
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AA-Metabolizing Activity and Metabolic Profile of Recombinant P450 Enzymes
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In the current study, we tested large group of human recombinant P450 enzymes for
their AA-metabolizing activities and metabolic profiles. Interestingly, we found that all tested
P450 enzymes were able to mediate AA-metabolism, but with variable activities and
characteristic profiles. On the other hand, there was no detectable formation of P450-derived
AA metabolites by NADPH reductase and cytochrome b5 alone in control samples.
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Among the tested P450 enzymes, CYP2C19 was of the highest activity followed by
CYP1A1 and CYP4F3B, and then CYP4A11 and CYP4F2 (Fig. 1). The rate of CYP2C19-
mediated AA consumption was 32.2 pmol/pmol P450/min. In contrast, CYP3A4 exhibited the
lowest AA-metabolizing activity, whose rate was 0.95 pmol/pmol P450/min (Fig. 1). CYP4
family, collectively, showed the highest activity towards AA compared with CYP1, CYP2 and
CYP3 families. Noteworthy, all tested P450 enzymes, except CYP1A2, mediated the
hydroxylation of AA (mid-chain, terminal and subterminal HETEs formation) more efficiently than
AA epoxidation (Fig. 1). For AA epoxidation, CYP2C19 was the highest P450 enzymes in the
formation rates of the four EETs, 1.7, 5.54, 1.68, 4.88 pmol/pmol P450/min for 5,6-, 8,9-, 11,12-,
and 14,15-EET, respectively (Fig. 2). Also, CYP1A2, followed by CYP1A1, showed high EETs-
formation activity emphasizing their importance as P450 epoxygenase (Figs. 1&2). CYP2J2 was
ranked the third highest enzyme in EETs formation rate (Fig. 1); CYP2J2-mediated formation
rate of 5,6-, 8,9-, 11,12-, and 14,15-EET was 0.05, 0.12, 0.09, and 0.21 pmol/pmol P450/min,
respectively (Fig. 2). With respect to hydroxylation, almost all P450 enzymes mediated the
hydroxylation of AA at its terminal and subterminal regions more efficiently than at the double
bond region (mHETEs). Although CYP1A1, CYP1A2, CYP2C19, CYP2C9 and CYP4F12
showed the highest mHETEs formation rates, only CYP1B1 and CYP2C18 mediated the
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formation of mHETEs more than the formation of EETs or terminal and subterminal HETEs (Fig.
1). Their mHETEs formation rates were 0.38, and 0.62 pmol/pmol P450/min for CYP1B1, and
CYP2C18, respectively (Fig. 1). With respect to terminal hydroxylation, CYP1A1 was the most
active enzyme among tested P450 enzymes in the formation of 16-, 17-, and 18-HETE (1.81,
1.1 and 3 pmol/pmol P450/min, respectively), and the second most active enzyme for 19-HETE
(6.6 pmol/pmol P450/min) after CYP2C19 (Fig. 2). CYP2C19 also mediated the formation of 16-
, 17-, 18-, and 19-HETE at a specific activity of 0.46, 0.31, 0.62, and 11.34 pmol/pmol P450/min,
respectively (Fig. 2). On the other hand, the most active 20-HETE forming P450 enzymes were
CYP4A11, CYP4F2, CYP4F3A and CYP4F3B with specific activity of 7.17, 5.94, 1.06, and
16.25 pmol/pmol P450/min, respectively (Fig. 2).
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AA-Metabolizing Activity and Metabolic Profile of Human Microsomes
We investigated the AA-metabolism by human microsomes separated from liver and
kidneys. For liver microsomes, it was pooled from 10 non-smoker volunteers, whose age and
weight mean SD were 53.4 22.5 year and 98 23.5 Kg, respectively. For kidney microsomes, it
was pooled from 3 male volunteers, whose age and weight mean SD were 40.3 17 year and
93.5 18.2 Kg, respectively. There was low NADPH-independent formation of mHETEs, and
therefore the rates of P450-dependent formation of mHETEs were corrected accordingly. Liver
microsomes showed, expectedly, the highest overall AA-metabolizing activity at all AA
concentrations; liver-mediated AA metabolism was 2-fold higher than that of kidneys at 75 µM
AA (Fig. 3). Increasing AA concentration from 7.5 to 75 µM led to an increase in metabolite
formation rates, while increasing AA concentration from 75 to 750 µM led to the same formation
rates of almost all metabolites (Fig. 3). In the kidneys, we only detected the formation of 5,6-
and 8,9-EET and 18-HETE at 75 µM AA but not at 7.5 or 750 µM (Fig. 3). The most prominent
metabolites for both liver and kidneys was 20-HETE (111 and 64 pmol/mg protein/min at 75µM
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AA, respectively), followed by 19-HETE (18 and 10 pmol/mg protein/min at 75µM AA,
respectively) (Fig. 3).
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Effect of P450 Inhibition on AA-Metabolism Mediated by Human Liver Microsomes
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In in vitro and animal studies, three investigational agents are widely used to modulate
P450-mediated AA metabolism, namely MS-PPOH to inhibit P450 epoxygenases,30 HET0016 to
inhibit P450 ω-hydroxylases,31 and α-NF to inhibit CYP1 family and subterminal HETEs
formation.27 We tested the effect of these investigational agents on AA metabolism to help
evaluating the selectivity and effectiveness of the tested clinically-approved drugs. With respect
to MS-PPOH, its effect on hepatic AA metabolism was selective to 11,12- and 14,15-EETs and
12-HETE at either the low (5 µM) or the high (50 µM) concentrations (Table 1). The formation
rates of these metabolites were significantly inhibited by an average of 22% and 51% by 5 and
50 µM of MS-PPOH, respectively (Table 1). On the other hand, HET0016 selectivity was
impaired by increasing its concentration from 50 nM to 1 µM. At 50 nM, HET0016 caused a
significant inhibition by 9 and 67% of the hepatic formation rate of 19- and 20-HETEs,
respectively (Table 1). While at 1 µM. HET0016 significantly altered the formation of 5,6-EET
and 5-, 11-, 12-, and 15-HETEs in addition to 9-, 19- and 20-HETEs (Table 1). For 5,6-EET and
9-, 19- and 20-HETEs, there was an inhibition in the formation rate by 35, 35, 30 and 98%,
respectively, and for 5-, 11-, 12-, and 15-HETEs, there was an increase in the formation rate by
36, 18, 27 and 46%, respectively, by HET0016 (Table 1). Regarding α-NF, it significantly and
selectively inhibited the formation of subterminal HETEs, 16- and 18-HETEs in liver by 14% at
the low concentration (40 nM); whereas, at 160 nM, α-NF lost its selectivity and inhibited the
formation of 5 other metabolites in addition to 16- and 18-HETEs (Table 1). According to our
recombinant P450 data, CYP1As, CYP2Cs and CYP4s have the most prominent activity
towards AA metabolism. Consequently, clinically-approved drugs we tested in our study are:
Res to inhibit CYP1As,32 Flu to inhibit CYP2C9 and to a lower extend CYP2C19,33 Tic to inhibit
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CYP2C19 and to a lower extend CYP2C9.34 Regarding CYP4s, we could not find a direct
inhibitor for them; however, it has been previously reported that ω-hydroxylation of fatty acids by
CYP4s is dependent on cytochrome b5.26, 35, 36 Therefore, we explored the effect of cytochrome
b5 inhibition on hepatic AA metabolism by PTU, reported to exhibit selective inhibitory activity
against cytochrome b5.37 Also, we used Dan to inhibit CYP2J2 and Ser to inhibit CYP2B6.38, 39
Res at low and high concentrations significantly and selectively inhibited the formation rate of
16-, 18- and more interestingly 20-HETE by an average of 22 and 46%, respectively (Table 2).
A significant decrease was observed in the hepatic formation rates of 8,9- and 14,15-EETs by
low concentration of Flu by an average of 24% (Table 2). At high concentration of Flu, the
formation rates of 11-, 12- and 15-HETEs in addition to 8,9- and 14,15-EETs were significantly
decreased by an average of 49% (Table 2). At low concentration of Tic, the formation rates of
5,6- and 8,9-EET and 9-, 16-, 18- and 19-HETE were significantly decreased in the liver,
whereas, at high concentration of Tic, the formation rates of almost all metabolites were
decreased (Table 2). The inhibition of CYP2B6 by Ser and inhibition of CYP2J2 by Dan led to
modest effects on AA-metabolism. Low concentration of Ser only decreased the formation rate
of 18-HETE in liver by 15%, while high concentration of Ser decreased 11,12-EET and 9- and
18-HETEs by an average of 25% (Table 2). Similarly, Dan decreased the formation rate of 19-
HETE at its high concentration in the liver by 11% (Table 2). With respect to PTU, it did not
cause any significant alteration in the hepatic formation rates of the tested metabolites except
20-HETE, whose formation rate was significantly increased by 49% (Table 2).
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Kinetics of P450-Mediated AA Metabolism Inhibition
To explain how Res decreased the formation rate of 20-HETE, varied concentration of
Res (0.03-1000 µM) was incubated with the dominant hepatic 20-HETE-forming P450 enzymes,
CYP4A11, CYP4F2 and CY4F3B. We found that Res was able to inhibit all of the three P450
enzymes but with different kinetics (Fig. 4). For CYP4F2, the Imax and IC50 mean values were
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92% and 4 µM, respectively (Fig. 4). Whereas, for CYP4A11, the Imax and IC50 mean values
were 81% and 90 µM, respectively, and for CYP4F3B, the Imax and IC50 mean values were
100% and 109 µM, respectively (Fig. 4).
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Also, the kinetics of P450-mediated AA metabolism inhibition by Res and Flu were
determined, because their selectivity and effectiveness were comparable to MS-PPOH and
HET0016. We found that the formation rates of 11,12- and 14,15-EETs and 16-, 18-, 19- and
20-HETEs showed a significant inverse non-parametric Spearman rank correlation with Res
concentration. The Imax mean values of Res were 99, 100, 79, 69, 61 and 54% for 11,12- and
14,15-EETs and 16-, 18-, 19- and 20-HETEs, respectively (Fig. 5). Whereas, the IC50 mean
values of Res were 60, 68, 17, 5, 104 and 3 µM for 11,12- and 14,15-EETs and 16-, 18-, 19-
and 20-HETEs, respectively (Fig. 5). For Flu, the formation rates of 8,9- and 14,15-EETs and
11-, 12- and 15-HETEs were significantly correlated with Flu concentration. The Imax mean
values of Flu were 61, 64, 67, 80 and 57% for 8,9- and 14,15-EETs and 11-, 12- and 15-HETEs,
respectively (Fig. 5). Whereas, the IC50 mean values of Flu were 13, 27, 28, 28 and 36 µM for
8,9- and 14,15-EETs and 11-, 12- and 15-HETEs, respectively (Fig. 5).
Simulating the Inhibition of P450-Mediated AA Metabolism after Safe Oral Doses of Res
and Flu
To gain insight about the expected inhibition in P450-medaited AA metabolism in
humans after safe oral doses of Res and Flu, Monte Carlo simulation was performed to simulate
10,000 human subjects orally administered 0.5, 1, 2.5 or 5 g daily of Res, or 50, 150 or 400 mg
of Flu. We used the previously reported plasma and tissue concentration data combined with
the kinetics of AA metabolism inhibition showed above. It has been reported that maximum
plasma concentration mean values and SD are 0.19 0.17, 0.62 0.43, 1.45 0.86 and 4.24 2.27
µM for 0.5, 1, 2.5 or 5 g daily of Res, respectively.40 Also, the reported liver to plasma ratio of
Res is 2.49,41 and uniform distribution of 20% was assumed. For Flu, the reported maximum
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plasma concentration mean values and SD of 3.04 0.42, 8.78 1.4 and 8.53 1.56 µM for 50,
150 or 400 mg daily of Flu, respectively,42, 43 and the reported liver to plasma ratio is 3.4,44 with
20% uniform distribution.
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Our simulations predicted that 90% of human population would experience 2-12%, 6-
22% and 17-41% inhibition in 16-HETE, 7-26%, 16-39% and 34-55% in 18-HETE and 7-26%,
16-35% and 31-46% in 20-HETE formation rates after 1, 2.5 and 5 g daily of Res, respectively
(Fig. 6). In contrast, Res at 0.5 g daily caused very modest inhibitory effect, and, similarly,
11,12- and 14,15-EETs as well as 19-HETE were not effectively inhibited by Res at any of the
tested doses (Fig. 6).For Flu, 50, 150 and 400 mg of Flu led to an inhibition of 22-31%, 37-46%
and 50-56% for 8,9-EET, 14-23%, 28-40% and 45-55% for 14,15-EET, 13-23%, 23-41% and
45-57% for 11-HETE, 16-27%, 34-49% and 54-68% for 12-HETE and 9-17%, 20-31% and 36-
46% for 15-HETE, respectively, in 90% of human population (Fig. 6).
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In the current study, we determined the AA-metabolizing activity of 16 recombinant
human P450 enzymes belong to different P450 families and subfamilies to get a good idea
about the differences in AA-metabolizing activity among human P450 enzymes. Tested P450
enzymes were untagged, expressed in the same expression system and previously validated for
activity studies. Noteworthy, there are P450 enzymes, such as CYP4F11, have been reported to
metabolize AA at a low rate,45 and they were commercially unavailable to us at the time to be
included in the current study. Interestingly, CYP4 family was collectively the most active P450
family with regard to AA-metabolizing activity. CYP4 family is one of the most antique within the
P450 enzymes, which implies its importance in biological systems.1 AA-metabolizing activities
were variable among the tested P450 enzymes; there was a 34-fold difference in AA-
metabolizing activity between P450 enzyme of the highest activity (CYP2C19) and of the lowest
activity (CYP3A4). The activity of an enzyme towards a substrate is governed by two factors:
the volume of the active site, and the amino acids forming the active site. Our results suggest
that there is an optimum volume for P450 active site to get the highest AA-metabolizing activity.
With respect to CYP1s, the volume of active site is decreasing from 524 Å3 for CYP1A1, to 469
Å3 for CYP1A2 and 441 Å3 for CYP1B1,46 which is correlated with the decreasing trend of AA
metabolizing activities among CYP1s. CYP2E1 has one of the smallest active site volume
among P450 enzymes (~ 250Å3),46, 47 and it showed low AA-metabolizing activity. On the other
hand, large active site volume may negatively affect AA-metabolizing activity. CYP2C8 has one
of the largest active site volumes (~ 1450 Å3) among P450 enzymes, and showed low AA-
metabolizing activity. The closely related CYP2C19 has smaller active site (estimated to be
~850 Å3) as well as CYP2C9, whose active site volume is ~1250 Å3,48 and this again is
correlated with their AA-metabolizing activities (CYP2C19>CYP2C9>CYP2C8).49 It has been
reported that CYP2C8 simultaneously binds to two molecules of retinoic acid, which is
structurally similar to AA.50 Therefore, we can insightfully postulate that this unusual binding
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may restrain the AA-metabolizing activity of CYP2C8, compared with the closely related
CYP2C19 and CYP2C9. This was also true for CYP3A4, whose active site volume is the largest
among P450 enzymes (~ 1600Å3), and its AA metabolizing activity was the lowest.51 Likewise,
CYP2J2 has a large active site volume of 1420 Å3, which is comparable to CYP3A4 and
CYP2C8, but, it has been reported that CYP2J2 active site is narrower than CYP3A4 near the
heme iron;51 as a result, CYP2J2 showed a higher AA-metabolizing activity compared with
CYP3A4.
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Both the AA-metabolizing activity, as well as the amount expressed in a tissue of each
P450 enzymes, dictate the tissue-specific metabolism of AA. In rats, we previously reported that
differences in the metabolic and kinetic profiles of AA metabolism by liver, kidneys, lungs and
heart can be explained by differences in tissue-specific expression of P450 enzymes.52 In
human, due to their high AA-metabolizing activity, CYP1As, CYP2C19 and CYP4s are
potentially dominating the P450-mediated AA metabolism. With respect to CYP1As, liver has
the highest expression of CYP1A2 among human organs, whereas CYP1A1, despite it was also
detected in the liver,53 is considered mainly an extrahepatic enzyme.54 Being the major
metabolites of recombinant CYP1As, subterminal HETEs and EETs formation was significantly
reduced by CYP1As selective inhibition by α-NF, while Res reduced the formation of
subterminal HETEs. Similar to CYP1As, previous reports found CYP2C19 is mainly hepatic and
no or little expression was reported in kidneys.55, 56 In agreement, the formation of EETs in
kidneys is in a much lower rate than liver, and additionally, inhibition of CYP2C19 by Tic or Flu
led to wide inhibition in the formation of AA metabolites, most importantly the major metabolites
of CYP2C19, viz. 8,9- and 14,15-EETs. While, the low AA-metabolizing activity of recombinant
CYP2B6 and CYP2J2 is in agreement with the weak inhibitory effect of their selective inhibitors,
Ser and Dan, respectively. With respect to CYP4s, their expression in either liver or kidneys is
comparable, but no or little expression of CYP4s was noted in other tissues.56, 57 Consistent with
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our findings that CYP4s have the highest AA-metabolizing activity, the formation rate of 19- and
20-HETE formation was the highest in both human liver and kidneys compared with all other
P450-derived AA metabolites. Also, the high 20-HETE formation rates of recombinant human
CYP4 family are consistent with the inhibitory effect of HET0016 on 20-HETE formation.
Interestingly, the almost complete inhibition of 20-HETE formation by HET0016 could be the
explanation of the unexpected increase in the formation rates of mHETEs, namely 5-, 11-, 12-
and 15-HETEs, by HET0016. Blocking CYP4s from mediating the hepatic formation of 20-
HETE, which is the dominant metabolite in the liver, made AA more available to the other still-
active P450-enzymes. Consequently, all P450-derived AA metabolites, other than 5,6-EET and
9-, 19- and 20-HETEs, showed an increase in their formation rates, which was only significant
for 5-, 11-, 12- and 15-HETEs. Similarly, there was a significant increase in the formation rate of
20-HETE, which was the only observed alteration in liver-mediated AA metabolism by PTU.
Therefore, we believe that PTU increased 20-HETE formation by activating CYP4s through
heterotropic cooperativity.58
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Our results show that the addition of the tested clinically-approved drugs induced
significant alterations in P450-mediated AA metabolism in the liver, comparable to the
alterations induced by investigational agents in term of magnitude and selectivity. As a result,
HET0016 and MS-PPOH, which have been used extensively in in vitro and animal studies as
selective inhibitors for 20-HETE and EETs formation, respectively,30, 31 can be easily replaced
with Res and Flu, respectively, in clinical studies. The other clinically-approved drugs were
either of low inhibitory activity or of low selectivity towards AA metabolism. As mentioned above
CYP4 family has the major contribution to 19- and 20-HETE formation in human. Therefore, we
could not initially explain how Res as a CYP1s inhibitor significantly decreased the formation of
20-HETE.32 We found thereafter that Res does inhibit all of the hepatic CYP4s; however, at low
Res concentration, Res selectively inhibits CYP4F2 with statistically the same IC50 value
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determined for Res inhibition of liver-mediated 20-HETE formation. Likewise, the IC50 values of
Res inhibition of liver- and CYP4A11- mediated 19-HETE formation are not significantly
different, which also in agreement with recombinant CYP4A11 data. The reported IC50 values
for CYP1As inhibition by Res are in line with our IC50 values for liver-mediated formation of 16-
and 18-HETEs.32 For Flu, it inhibits 8,9- and 14,15-EETs and 11-, 12- and 15-HETEs with IC50
values very similar to the reported IC50 values of Flu inhibition of CYP2C9/19.33
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Based on our results, several P450 enzymes can mediate AA-metabolism, and therefore
the in vivo modulation of P450-mediated AA-metabolism requires highly selective P450
inhibitors. Also, it is important to note the substantial loss of selectivity by the increase in the
concentration of the tested P450 inhibitors, which highlights the importance of identifying the
optimum doses to retain selectivity. Our simulations show that Res would maintain its selectivity
and magnitude of inhibition when given to human subjects at relatively high but safe oral dose of
2.5 g daily.59 Whereas, for Flu, selectivity and magnitude of inhibition would be maintained by
low oral dose of 50 mg.60 Because liver has the highest P450 content in the body, it has been
reported that hepatic P450-mediated AA metabolism controls the systemic levels of P450-AA
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metabolites.61,
Elevated levels of 20-HETE has been associated with several diseases,
especially cardiovascular and renal diseases;63, 64 whereas, elevated levels of EETs has been
reported to promote cancer progression due to EET-induced angiogenesis.65 In conclusion,
pharmacological modulation of P450-derived AA metabolites, similar to cyclooxygenase and
lipoxygenase-derived metabolites, has great potential for clinical uses. Recently, soluble
epoxide hydrolase inhibitors, which increase EETs levels, have been successfully used for
prevention and treatment of several diseases and pathological conditions.66 Likewise, targeting
P450 enzymes to alter P450-derived AA metabolites starts to be in the focus of biomedical
research.67 The advantage of repurposing clinically-approved drugs is that their dosage and
human safety profile are known. Upon determining which drug is the best candidate as a
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treatment of heart enlargement and heart failure, drug could be easily introduced to clinical
trials. In this regards, we systematically identified safe doses of Res and Flu to modulate P450-
mediated AA metabolism in human.
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This work was supported by a grant from the Canadian Institutes of Health Research (CIHR)
[Grant MOP 106665]. AAE is the recipient of Egyptian Government Scholarship and Alberta
Innovates-Health Solutions studentship.
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Figure legends
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Figure 1. The metabolizing activity of human recombinant P450 enzymes: arachidonic
acid (AA) consumption, epoxyeicosatrienoic acids (EETs) formation, mid-chain
hydroxyeicosatetraenoic acids (mHETEs) formation, and terminal and subterminal
hydroxyeicosatetraenoic acids formation (ω/ω-1 HETEs). Recombinant P450 enzymes
were incubated with AA for 15-20 min, and AA and its metabolites were measured by liquid
chromatography-mass, as described under Materials and Methods. Results are presented as
mean and SE, based on at least 3 individual experiments. Using ANOVA followed by a Tukey’s
post hoc test, the five most active P450 enzymes were identified (indicated by Arabic numbers);
different numbers indicate significantly different activities at p<0.05.
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Figure 2. Heat map of the activities ofP450-derived AA metabolites formation of human
recombinant P450 enzymes. Recombinant P450 enzymes were incubated with AA for 15-20
min, andP450-derived AA metabolites were measured by liquid chromatography-mass
spectrometry, as described under Materials and Methods. Results are presented referring to the
color key at the bottom side.
Figure 3. The formation of P450-derived AA metabolites mediated by human liver and
kidney microsomes. Microsomal protein from liver or kidney was incubated with 7.5, 75 and
750 µM of AA for 30 minutes, and P450-derived AA metabolites were measured by liquid
chromatography-mass spectrometry, as described under Materials and Methods. Results are
presented as mean and SE, based on at least 3 individual experiments.
Figure 4. Concentration-dependent inhibition of CYP4A11-, CYP4F2- and CYP4F3B-
mediated 20-HETE formation by Res. Recombinant P450 enzymes were incubated with AA
for 15-20 min and 0.01-1000 µM of Res, and 20-HETE was measured by liquid
chromatography-mass spectrometry, as described under Materials and Methods. Results are
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presented as mean and SE, based on at least 3 individual experiments. Log(IC50) and Imax
mean SE were determined by Enzyme Kinetics module from GraphPad Prism, version 5.0.
7
8
9
Figure 5. Concentration-dependent inhibition of hepatic microsomal-mediated formation
of P450-derived AA metabolites by Res and Flu. Microsomal protein from liver was incubated
with AA for 30 minutes, and P450-derived AA metabolites were measured by liquid
chromatography-mass spectrometry, as described under Materials and Methods. Results are
presented as mean and SE, based on at least 3 individual experiments. Log(IC50) and Imax
mean SE were determined by Enzyme Kinetics module from GraphPad Prism, version 5.0.
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Figure 6. Box plot showing Monte Carlo simulations of P450-mediated AA metabolism
modulation by different doses of Res and Flu. Monte Carlo simulations of 10,000 human
subjects were performed using random number generation module from SigmaPlot, version 11,
as described under Materials and Methods. Results are presented as median and 10th, 25th,
75th and 90th percentiles; circles represent outliers.
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Table 1. Effect (mean SE) of different selective P450 inhibitors on AA metabolism mediated by liver microsomes.
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11
12
13
14
% Alterationa
P450 inhibitor
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
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37
38
39
40
41
42
43
44
45
46
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48
49
5,6-EET 8,9-EET 11,12-EET14,15-EET 5-HETE 9-HETE 11-HETE 12-HETE 15-HETE 16-HETE 18-HETE 19-HETE 20-HETE
23 10
160 nM -64 2*
13
9
16
4
28 17
-1
7
25 10
29 19
32 26
10
3
-14 2*
-14 3*
5
2
4 1
α-NF
40 nM
-9 5
-12 7
-28 10
32 11
-15 4*
-46 5**
-21 4*
-18 5*
-51 5**
-20 6*
-9 18
-4 6
-20 4*
-30 11
-55 37
15 3
-32 6*
-57 9*
-17 3*
-22 10
-48 21
29 12
-32 6*
13 16
-16 19
-17 4*
-4 19
14 17
-8 5
-10 6
5 5
0 4
-8 6
-29 15
-52 19
-49 23
MS-PPOH 5 µM
50 µM -33 30
-26 20
-1 7
7
9
8
2
26
9
18
5
6
3
-22
3
4
10
2
7
3
5
10
7
-9 2*
-67 7**
HET0016 50 nM
1000nM -35 1**
5 2
21 13
28 7
36 2**
-35 5*
18 2*
27 2*
46 4**
3 1
31 18
-30 2**
-98 7**
aData are based on at least three individual experiments; * significant at P = 0.05; ** significant at P = 0.01.
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Table 2. Effect (mean SE) of different selective P450 inhibitors on AA metabolism mediated by liver microsomes.
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8
9
% Alterationa
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
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27
28
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30
31
32
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37
38
39
40
41
42
43
44
45
46
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48
49
P450 inhibitor
5,6-EET 8,9-EET 11,12-EET14,15-EET 5-HETE 9-HETE 11-HETE 12-HETE 15-HETE 16-HETE 18-HETE 19-HETE 20-HETE
18 16
10 µM -28 19
-12
7
10
8
0
7
-7 11
-4
5
-17
8
-4
6
34 13
-21 6*
-33 6*
6
1
-12 1**
Res
1 µM
-13 17
-22 4*
-61 1**
-16 8
-9 8
-15 18
-6 2
-23 6
-19 10
-41 1**
-33 15
-40 18
-40 5**
-65 2**
-5 7
-32 6*
16
5
-9
6
-26 2**
-43 3**
-16
4
-21 12
-12 20
-47 5*
-57 5**
-15 10
-34 1**
-15
4
-15
9
2
1
2
0
2
4
14 4
Flu
10 µM
100 µM -9 9
-21 8
38 11
32 30
11 12
-19 0**
41 40
-61 1**
14 13
-38 2**
-17 36
-14 2*
-27 6*
-8 10
-10 2*
-41 4**
-15 3*
-21 1**
-11 10
-18 2*
-43 4**
18 13
-49 4** -29 2**
10 µM
-3
7
-5
5
1
5
-7
3
1 2
Tic
100 µM -85 3**
-50 15*
37 31
-1 11
-54 14*
-1 3
-30 4*
0 0
-28 13
-36 6*
-21 5
23 11
0
4
6
9
31
5
0
5
14
4
20
7
17 5
Ser
30 µM
300 µM 32 35
38 24
32 10
-2 1
34 12
0 0
53 33
21 37
7 12
2 7
46 37
3
10
6
8
24
7
4
9
-10
9
2
10
5
7
5
3
1
9
-10
4
5
6
2 8
Dan 20 nM
200 nM -8 6
2 2
1 1
-1 1
-10 3
-3 1
-2 1
-7 3
2 2
-13 5
-11 2*
-1 2
-42 17
-6
7
6
5
5
6
32 20
1
8
-4
7
9
2
4
-12 10
45 20
18 16
2
8
6 7
PTU 0.1mM
39 17
-23 11
6
-7
1
14 15
-36 20
7 9
7 7
17 7
22 14
14 11
8 5
49 5**
1 mM
aData are based on at least three individual experiments; * significant at P = 0.05; ** significant at P = 0.01.
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Figure 3. The formation of P450ꢀderived AA metabolites mediated by human liver and kidney microsomes.
Microsomal protein from liver or kidney was incubated with 7.5, 75 and 750 µM of AA for 30 minutes, and
P450ꢀderived AA metabolites were measured by liquid chromatographyꢀmass spectrometry, as described
under Materials and Methods. Results are presented as mean and SE, based on at least 3 individual
experiments.
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