Varnavas D Mouchlis1, Aaron Armando1, Edward A Dennis1. 1. Department of Chemistry and Biochemistry and Department of Pharmacology, School of Medicine , University of California, San Diego , La Jolla , California 92093-0601 , United States.
Abstract
Assaying lipolytic enzymes is extremely challenging because they act on water-insoluble lipid substrates, which are normally components of micelles, vesicles, and cellular membranes. We extended a new lipidomics-based liquid chromatographic-mass spectrometric assay for phospholipases A2 to perform inhibition analysis using a variety of commercially available synthetic and natural phospholipids as substrates. Potent and selective inhibitors of three recombinant human enzymes, including cytosolic, calcium-independent, and secreted phospholipases A2 were used to establish and validate this assay. This is a novel use of dose-response curves with a mixture of phospholipid substrates, not previously feasible using traditional radioactive assays. The new application of lipidomics to developing assays for lipolytic enzymes revolutionizes in vitro testing for the discovery of potent and selective inhibitors using mixtures of membranelike substrates.
Assaying lipolytic enzymes is extremely challenging because they act on water-insoluble lipid substrates, which are normally components of micelles, vesicles, and cellular membranes. We extended a new lipidomics-based liquid chromatographic-mass spectrometric assay for phospholipases A2 to perform inhibition analysis using a variety of commercially available synthetic and natural phospholipids as substrates. Potent and selective inhibitors of three recombinant human enzymes, including cytosolic, calcium-independent, and secreted phospholipases A2 were used to establish and validate this assay. This is a novel use of dose-response curves with a mixture of phospholipid substrates, not previously feasible using traditional radioactive assays. The new application of lipidomics to developing assays for lipolytic enzymes revolutionizes in vitro testing for the discovery of potent and selective inhibitors using mixtures of membranelike substrates.
Assaying the activity
of phospholipases A2 (PLA2s) has been challenging
because they are water-soluble enzymes
acting on water-insoluble phospholipid substrates.[1,2] To
set up a successful PLA2 assay, one must consider three
critical issues. First, a suitable phospholipid substrate must be
used because there is a variety of available phospholipids. Second,
phospholipids exist in aggregated forms in water and so the appropriate
physical form should be employed. Third, a sensitive detection system
must be used that is compatible with the substrate.[3] Traditional PLA2 assays have employed synthetic
radio-labeled phospholipids that contain 3H- or 14C-labeled fatty acids (FAs) at the sn-2 position of the phospholipid.
Such phospholipids are challenging to synthesize, expensive, and limited
in terms of commercial availability, and they require special handling
techniques.[4] These limitations pose significant
difficulties in choosing an optimum substrate for each of the various
types of PLA2s. The surface-dilution kinetics model was
successfully employed by our laboratory to explain the action of PLA2 enzymes on phospholipid/detergent mixed micelles.[5,6] The success of the surface dilution model to explain kinetics of
PLA2 enzymes in mixed micelles, the stability of the micelle
structure in the presence of various phospholipids or inhibitors,
and high efficiency in preparing mixed micelles make them a suitable
physical form of a substrate to employ in a PLA2 assay.[7] Lipidomics-based liquid chromatographic–mass
spectrometric (LC–MS) approaches have proven to be very powerful
in understanding how PLA2 enzymes regulate eicosanoid biosynthesis.[8,9] LC–MS provides a very sensitive detection system that is
compatible with mixed micelles in the presence of a surfactant.A novel lipidomics-based PLA2 assay using mixed micelles
was previously developed for substrate specificity studies on three
human enzymes including group IVA cytosolic (cPLA2), group
VIA calcium-independent (iPLA2), and group V secreted PLA2 (sPLA2).[10] This assay
is semi-high throughput, uses significantly smaller amounts of substrate
and enzyme compared to existing assays,[3,4] and allows
the use of a wide variety of natural and synthetic unlabeled phospholipids.
In the current study, we have further developed our assay to obtain
inhibitory dose–response curves using a variety of pure phospholipids,
not previously feasible using traditional radioactive assays. Three
potent and selective inhibitors, one each specific for cPLA2, iPLA2, and sPLA2, were employed to validate
the use of the assay for inhibitor studies. The ability to employ
lipidomics techniques in assaying PLA2 enzymes allowed
us for the first time to perform more complex inhibitory assessments
with mixtures of phospholipids. Determining XI(50) and
IC50 values using a membranelike substrate is now feasible,
which should aid in identifying potent and selective inhibitors for
PLA2 enzymes that are necessary for the development of
new therapeutics.
Results and Discussion
Assay Development and Validation
A lipidomics-based
high-performance LC (HPLC)–MS assay using hydrophilic interaction
chromatography (HILIC) and multiple reaction monitoring (MRM), which
allowed quantification of a variety of lysophospholipid products,
was previously developed by us and employed to define the substrate
specificity for cPLA2, iPLA2, and sPLA2 (Figure A).[10] We have now used and also extended the assay
to use C18 reversed-phase chromatography for the quantification of
free FA products, including arachidonic acid (AA), deuterated AA (AA-d8),
and linoleic acid (LA, Figure B). 17:0 LPC and AA-d8 were used as internal standards for
normalizing variations related to sample handling, ionization efficiency,
and signal intensity fluctuations. Lysophospholipids and free FAs
were detected using the positive and negative ion mode, respectively.[10]
Figure 1
Quantification of primary and internal standards using
HPLC chromatography
and MRM: (A) for lysophospholipids using a HILIC column (adapted from
ref (10)) and (B) for
free FAs using a C18 reversed-phase column.
Quantification of primary and internal standards using
HPLC chromatography
and MRM: (A) for lysophospholipids using a HILIC column (adapted from
ref (10)) and (B) for
free FAs using a C18 reversed-phase column.Three inhibitors were used to develop and validate the PLA2 assay: pyrrophenone, which is a pyrrolidinecPLA2 inhibitor;[11] OTFP, which is a fluoroketone
iPLA2 inhibitor;[12] and Ly315920,
which is an indole sPLA2 inhibitor.[13] For each inhibitor, three dose–response inhibition
curves were generated for calculating XI(50) and IC50 values: two by using lipidomics assays (one measuring lysophospholipid
product in the positive ion mode and one the FA product in the negative
ion mode) and one by using the traditional radioactive assay. XI(50) is the mole fraction of the inhibitor in the total substrate
interface required to inhibit the enzyme by 50%.[14] XI(50) and IC50 values were calculated
by plotting the percentage of inhibition versus log (mole fraction)
or log (concentration), respectively. For the radioactive assay, a
phospholipid substrate containing 14C-labeled AA esterified
at the sn-2 position was used. Free 14C-labeled AA was
detected using a scintillation counter. Mixed micelles were prepared
using 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine
(PAPC) and C12E8 surfactant. PAPC was chosen as a substrate because
cPLA2 is selective for AA at the sn-2 position and to have
a common substrate for comparison of our results because iPLA2 and sPLA2 exhibit fair activity toward this substrate. Figures –4 show the dose–response
curves for pyrrophenone, OTFP, and Ly315920, respectively. XI(50) values of 0.0026 (IC50 = 1.83 μM) and 0.0027
(IC50 = 1.88 μM) were calculated for pyrrophenone
using the lipidomics assay in positive and negative ion mode, respectively
(Figures A,B). An
XI(50) value of 0.0022 (IC50 = 1.23 μM)
was determined for the same inhibitor using the radioactive assay
(Figure C). The XI(50) values for OTFP were 0.00008 (IC50 = 0.054
μM) and 0.00007 (IC50 = 0.049 μM) using the
lipidomics assay (Figure A,B) and 0.00009 (IC50 = 0.048 μM) using
the radioactive assay (Figure C). Finally, XI(50) values of 0.00015 (IC50 = 0.104 μM) and 0.00018 (IC50 = 0.131 μM)
(Figure A,B) were
determined for Ly315920 using the lipidomics assay and 0.00010 (IC50 = 0.056 μM) using the radioactive assay (Figure C). The XI(50) and IC50 values that were determined using the lipidomics
and radioactive assays were very similar for each of the three inhibitors
within the calculated experimental error, indicating the validity
of the lipidomics assays (Table ).
Figure 2
Dose–response inhibition curves for pyrrophenone
using PAPC
substrate. (A) Activity of cPLA2 was measured by detecting
16:0 LPC in a positive ion mode and (B) by detecting free AA in a
negative ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.
Figure 4
Dose–response inhibition curves for Ly315920 using PAPC
substrate. (A) Activity of sPLA2 was measured by detecting
16:0 LPC in a positive ion mode and (B) by detecting free AA in a
negative ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.
Figure 3
Dose–response inhibition curves for OTFP using PAPC substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPC
in a positive ion mode and (B) by detecting free AA in a negative
ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.
Table 1
XI(50) and IC50 (μM) Values
of PLA2 Inhibitors
PLA2 activity was measured
by detecting 16:0 lysophospholipid product in a positive ion mode.
PLA2 activity was
measured
by detecting free FA product in a negative ion mode.
PLA2 activity was measured
by using 14C-labeled AA.
Dose–response inhibition curves for pyrrophenone
using PAPC
substrate. (A) Activity of cPLA2 was measured by detecting
16:0 LPC in a positive ion mode and (B) by detecting free AA in a
negative ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.Dose–response inhibition curves for OTFP using PAPC substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPC
in a positive ion mode and (B) by detecting free AA in a negative
ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.Dose–response inhibition curves for Ly315920 using PAPC
substrate. (A) Activity of sPLA2 was measured by detecting
16:0 LPC in a positive ion mode and (B) by detecting free AA in a
negative ion mode. (C) Activity of the enzyme was measured using 14C-labeled AA in a scintillation counter.PLA2 activity was measured
by detecting 16:0 lysophospholipid product in a positive ion mode.PLA2 activity was
measured
by detecting free FA product in a negative ion mode.PLA2 activity was measured
by using 14C-labeled AA.To further assess the accuracy of lipidomics assays,
three independent
dose–response inhibition experiments were performed for each
inhibitor (Figures S1–S3). The reported
average XI(50), IC50, and the standard error
values indicate the reproducibility, robustness, and accuracy of the
lipidomics assay (Table ).
Table 2
XI(50), IC50, and Standard Error
Values for the Inhibition of cPLA2 by Pyrrophenone, iPLA2 by OTFP, and sPLA2 by
Ly315920, Respectively, Calculated by Performing Three Independent
Dose–Response Inhibition Experiments on Each Inhibitor
pyrrophenone
OTFP
LY315920
positive
negative
positive
negative
positive
negative
XI(50)
IC50 (μM)
XI(50)
IC50 (μM)
XI(50)
IC50 (μM)
XI(50)
IC50 (μM)
XI(50)
IC50 (μM)
XI(50)
IC50 (μM)
0.0027
1.83
0.0027
1.88
0.00008
0.054
0.00007
0.049
0.00015
0.104
0.00019
0.131
0.0019
1.32
0.0020
1.38
0.00008
0.058
0.00009
0.060
0.00018
0.124
0.00018
0.127
0.0023
1.61
0.0021
1.47
0.00007
0.051
0.00005
0.034
0.00017
0.116
0.00020
0.136
average
0.0023
1.59
0.0023
1.58
0.00008
0.055
0.00007
0.048
0.00017
0.114
0.00019
0.131
STDEV
0.0004
0.26
0.0004
0.27
0.000005
0.004
0.00002
0.013
0.00001
0.010
0.00001
0.004
Substrate Affinity Affects Competitive Inhibitors
The
identification of a variety of lysophospholipid and free FA products
using LC–MS (Figure ) enabled us to perform dose–response inhibition curves
by using phospholipid substrates with a better affinity toward these
enzymes. On the basis of substrate specificity data, sPLA2 showed approximately 27-fold greater activity toward phospholipids
containing phosphoglycerol (PG) compared to PAPC.[10] The dose–response inhibition studies of Ly315920
in the presence of 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphoglycerol
(PAPG) gave XI(50) values of 0.026 (IC50 = 18
μM) and 0.032 (IC50 = 22 μM) in positive and
negative ion modes, respectively (Figure A,B). Ly315920 showed approximately a 170-fold
higher inhibitory potency toward sPLA2 when PAPC was utilized
as a substrate versus PAPG. iPLA2 exhibited approximately
fourfold higher activity toward phospholipids containing linoleic
(L) acid at the sn-2 position rather than AA.[10] XI(50) values of 0.00012 (IC50 = 0.083 μM)
and 0.00010 (IC50 = 0.067 μM) were determined for
OTFP in positive and negative ion modes, respectively, by using PLPC
as a substrate (Figure A,B). OTFP exhibited approximately twofold greater inhibitor potency
toward iPLA2 when PAPC was used as a substrate versus PLPC.
These two examples demonstrate that the inhibitory potency is dependent
on the substrate affinity when it comes to competitive inhibitors.
Figure 5
Dose–response
inhibition curves for Ly315920 using PAPG
substrate. (A) Activity of sPLA2 was measured by detecting
16:0 LPG in a positive ion mode and (B) by detecting free AA in a
negative ion mode.
Figure 6
Dose–response
inhibition curves of OTFP using PLPC substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPC
in a positive ion mode and (B) by detecting free LA in a negative
ion mode.
Dose–response
inhibition curves for Ly315920 using PAPG
substrate. (A) Activity of sPLA2 was measured by detecting
16:0 LPG in a positive ion mode and (B) by detecting free AA in a
negative ion mode.Dose–response
inhibition curves of OTFP using PLPC substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPC
in a positive ion mode and (B) by detecting free LA in a negative
ion mode.
Inhibition Studies on Membranelike
Mixtures of Substrates
PLA2 enzymes are localized
on different cellular membranes
where they encounter different substrates depending on their cellular
localization. Cellular membranes consist of a wide variety of phospholipids
that are substrates for PLA2 enzymes with different affinities.
Two factors affect the activity of a PLA2 enzyme toward
a particular phospholipid substrate including the association of the
enzyme with the membrane and the specific binding of the phospholipid
in the active site. To study the effect of the interfacial association
with the membrane on dose–response inhibition studies, a more
complex system of an equal molar mixture of five phospholipid species
was used to determine XI(50) values. The sn-1 and sn-2
positions of each phospholipid contained palmitic (P) and arachidonic
(A) acid, respectively, whereas the head groups were varied including
phosphatidic acid (PA), phosphocholine (PC), phosphoethanolamine (PE),
PG, or phosphoserine (PS). The XI(50) values of pyrrophenone
and OTFP, determined in positive ion mode, were similar for each of
the five phospholipids individually with some variations because of
human and instrumental error (Figures A and 8A). XI(50)
values based on total AA released of 0.0018 (IC50 = 1.30
μM) and 0.00007 (IC50 = 0.050 μM) were determined
for pyrrophenone and OTFP, respectively, which do not differ significantly
from the ones determined for each phospholipid separately in a positive
ion mode (Figures B and 8B).
Figure 7
Dose–response inhibition curves
for pyrrophenone using an
equal molar mixture of 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphate (PAPA), PAPC, 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphoethanolamine (PAPE), PAPG, and PAPS
as a substrate. (A) Activity of cPLA2 was measured by detecting
16:0 LPA, 16:0 LPC, 16:0 LPE, 16:0 LPG, and 16:0 LPS in a positive
ion mode and (B) by detecting free AA in a negative ion mode.
Figure 8
Dose–response inhibition curves for OTFP
using an equal
molar mixture of PAPA, PAPC, PAPE, PAPG, and PAPS as a substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPA,
16:0 LPC, 16:0 LPE, 16:0 LPG, and 16:0 LPS in a positive ion mode
and (B) by detecting free AA in a negative ion mode.
Dose–response inhibition curves
for pyrrophenone using an
equal molar mixture of 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphate (PAPA), PAPC, 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphoethanolamine (PAPE), PAPG, and PAPS
as a substrate. (A) Activity of cPLA2 was measured by detecting
16:0 LPA, 16:0 LPC, 16:0 LPE, 16:0 LPG, and 16:0 LPS in a positive
ion mode and (B) by detecting free AA in a negative ion mode.Dose–response inhibition curves for OTFP
using an equal
molar mixture of PAPA, PAPC, PAPE, PAPG, and PAPS as a substrate.
(A) Activity of iPLA2 was measured by detecting 16:0 LPA,
16:0 LPC, 16:0 LPE, 16:0 LPG, and 16:0 LPS in a positive ion mode
and (B) by detecting free AA in a negative ion mode.According to the substrate specificity data, cPLA2 and
iPLA2 did not exhibit significant preference for the phospholipid
headgroup;[10] thus, the XI(50)
values of pyrrophenone and OTFP were not affected significantly in
mixtures. In contrast, as previously reported, sPLA2 showed
strong preference for PAPG compared to the other four phospholipid
species.[10] For Ly315920, an XI(50) value of 0.0031 (IC50 = 2.14 μM) was determined
for PAPG as a substrate which is significantly higher than the XI(50) values for the other four phospholipids (Figure A). By detecting AA in a negative
ion mode, a total composite XI(50) value was determined
for the phospholipid mixture because this FA is common in all five
phospholipids. An XI(50) value of 0.0008 (IC50 = 0.60 μM) was determined for Ly315920, which differs from
the ones determined for each of the five phospholipids using a positive
ion mode (Figure B).
Furthermore, the XI(50) values for PAPS and PAPA (the least
good substrates) are higher than those for PAPE and PAPC, the next
best substrates, and lowest for PAPG, the best substrate, in the order
expected. This demonstrates that one can enlarge the dynamic range
of experimentally determining inhibition constants by judicious choice
of substrate and substrate mixtures.
Figure 9
Dose–response inhibition curves
for Ly315920 using a mixture
of PAPA, PAPC, PAPE, PAPG, and PAPS as a substrate. (A) Activity of
sPLA2 was measured by detecting 16:0 LPA, 16:0 LPC, 16:0
LPE, 16:0 LPG, and 16:0 LPS in a positive ion mode and (B) by detecting
free AA in a negative ion mode.
Dose–response inhibition curves
for Ly315920 using a mixture
of PAPA, PAPC, PAPE, PAPG, and PAPS as a substrate. (A) Activity of
sPLA2 was measured by detecting 16:0 LPA, 16:0 LPC, 16:0
LPE, 16:0 LPG, and 16:0 LPS in a positive ion mode and (B) by detecting
free AA in a negative ion mode.
Application of PLA2 Assay Combined with Molecular
Dynamics to Identify Novel Inhibitors
Elucidating the biological
function of cPLA2, iPLA2, and sPLA2 is very important because they are involved in several inflammatory
diseases including cancer, diabetes, and atherosclerosis.[1] Small organic molecules with potent and selective
inhibitory properties are essential tools for studying the biological
function of these enzymes. This in vitro assay can be combined with
in silico screening techniques to identify new hit compounds for each
enzyme. Because the available three-dimensional structures of these
enzymes do not contain a bound inhibitor, molecular docking was employed
to create an initial enzyme–inhibitor complex that was consistent
with previously published HD-XMS data.[12,15,16] Each complex was then placed on the surface of the
membrane based on previous models for each enzyme binding to membranes.[10] In the context of the relaxed complex scheme,
which combines the advantages of molecular docking with dynamic structural
information,[17] each system was subjected
to molecular dynamics (MD) simulations in the presence of a membrane.
Movies 1, 2,
and 3 show the binding interaction of pyrrophenone,
OTFP, and Ly315920 in the active site of cPLA2, iPLA2, and sPLA2, respectively. Clustering analysis
allowed the identification of dynamic structures for each enzyme (Figure A–C). These
structures will be used to virtually screen compound libraries, select
a reasonable number of good binders, and test them in vitro using
the PLA2 LC–MS assay described herein. Even though
cPLA2, iPLA2, and sPLA2 can bind
and hydrolyze the same phospholipid substrate, cPLA2 binds
large inhibitors similar to pyrrophenone, whereas iPLA2 and sPLA2 bind relatively small inhibitors such as OTFP
and Ly312059. The volume of the cPLA2 active site was stabilized
at ∼900 Å3 during the simulation, whereas the
volume of the iPLA2 and sPLA2 active site was
stabilized at ∼500 Å3 (Figure D). This indicates that iPLA2 and sPLA2 can adjust the volume of their active site
by recruiting small molecule inhibitors that optimize interactions
with small binding pockets.
Figure 10
MD simulations and clustering analysis allowed
the identification
of dynamic structures suitable for in silico screening of compound
libraries for (A) cPLA2, (B) iPLA2, and (C)
sPLA2. (D) Active site volume during the time of the simulation
for cPLA2, iPLA2, and sPLA2 is shown.
MD simulations and clustering analysis allowed
the identification
of dynamic structures suitable for in silico screening of compound
libraries for (A) cPLA2, (B) iPLA2, and (C)
sPLA2. (D) Active site volume during the time of the simulation
for cPLA2, iPLA2, and sPLA2 is shown.
Conclusions
Assaying
PLA2 enzymes using traditional radioactive
assays has been extremely limiting because radiolabeled phospholipid
substrates are challenging to synthesize and purify and few are available
commercially. In this article, we present a novel lipidomics PLA2 assay which is simple, semi-high throughput, and does not
require the use of radiolabeled phospholipid. The LC–MS-based
system described herein has a sensitivity similar to the radioactive
assay. The new assay was validated by using pyrrophenone, OTFP, and
Ly315920, which are potent inhibitors for cPLA2, iPLA2, and sPLA2, respectively. Because detailed dose–response
inhibition studies proved the robustness of the assay, it is now possible
to use it with mixtures of phospholipids and in combination with in
silico screening to identify novel PLA2 inhibitors.In the classic radiolabeled assay, the radiolabeled substrate is
used as a tracer for a particular phospholipid which is present (i.e.,
1-palmitoyl-2-(1-[14C]-arachidonoyl)-sn-glycero-3-phosphocholine for PAPC); therefore, if a mixture of phospholipids
was included as a substrate, the hydrolysis of the radiolabeled substrate
would be competing with other nonlabeled phospholipids as a substrate,
so the apparent activity would depend on the specific phospholipid
mixture used. In contrast with the lipidomics assay, the specific
lysophospholipid and the specific FA products can each be detected
for each different phospholipid in the mixture. This is illustrated
in Figures and 8 whereby in the presence of an inhibitor, the net
activity (expressed as XI(50) or IC50) reflects
the inhibitor binding to the enzyme effecting its affinity for each
substrate phospholipid proportionally. For these two enzymes (cPLA2 and iPLA2), each of the five substrates in the
mixture has a similar affinity for the enzyme; therefore, the XI(50) or IC50 are the same, measured for each lysophospholipid
product and for the total AA released from all five phospholipids.
In contrast, in Figure with sPLA2, where the affinity for each phospholipid
substrate is different, the XI(50) or IC50 for
the sPLA2 specific inhibitor is different for each phospholipid.
If one of the phospholipids in the mixture was not a substrate for
the enzyme as might be the case in a natural membrane, then no lysophospholipid
or FA products would appear for that phospholipid, but one could still
determine the XI(50) or IC50 for the inhibition
of the enzyme acting on each of the other phospholipids present.Additionally, it is important to test inhibitors on natural substrates
found in the membrane of the specific subcellular organelle that each
enzyme acts on. Mixtures of phospholipids with varying sn-2 FA leaving
groups and polar groups can now be combined to mimic natural membranes,
and the resulting activity of each PLA2 can be determined.
This new approach to assaying PLA2s will allow us to determine
if a given inhibitor is more effective with one substrate over another.
We are now exploring the extension of this in vitro assay to determine
the ex vivo activity of these enzymes in living cells, where the analysis
of the products after enzyme activation in the cells should provide
greater insight as to the relevance to the in vivo activity.
Experimental and Computational Methods
Lipidomics
PLA2 Assay
Group-specific assays
were employed to determine the activity of human recombinant group
IVA cytosolic (cPLA2), group VIA calcium-independent (iPLA2), and group V secreted PLA2 (sPLA2)
in a mixed micelle 96 well-plate assay, as previously described.[10] The substrate for each enzyme consisted of 100
μM of phospholipid, 400 μM of C12E8 surfactant, 2.5 μM
of 17:0 LPC, and 10 μM AA-d8 internal standards for positive
and negative ion modes, respectively. For cPLA2, the total
phospholipid concentration (100 μM) consisted of 97 μM
phospholipid substrate and 3 μM PI(4,5)P2, which enhances the
activity of the enzyme. A specific buffer was prepared to achieve
optimum activity for each enzyme. The buffer for cPLA2 contained
100 mM HEPES of pH 7.5, 90 μM CaCl2, and 2 mM DTT.
For iPLA2, the buffer consisted of 100 mM HEPES of pH 7.5,
2 mM ATP, and 4 mM DTT. Finally, the buffer for sPLA2 contained
50 mM Tris-HCl of pH 8.0 and 5 mM CaCl2. The enzymatic
reaction was performed in a 96-well plate using a Benchmark Scientific
H5000-H MultiTherm heating shaker for 30 min at 40 °C. Each reaction
was quenched with 120 μL of methanol/acetonitrile (ACN; 80/20,
v/v), and the samples were analyzed using the HPLC–MS system.
A blank experiment, which did not contain enzyme, was also included
for each substrate to determine the nonenzymatic hydrolysis product
and to detect any changes in the intensity of both 17:0 LPC and AA-d8
internal standards. For each inhibitor dose–response curve,
three replicates were performed for each inhibitor concentration during
three independent experiments. The standard deviation was calculated
for each triplicate and is included in each graph with error bars.
Each inhibitor was dissolved in dimethyl sulfoxide at a 5 mM concentration.
The radioactive assay was extensively described in previous publications.[12,16] Dose–response inhibition curves were generated using GraphPad
Prism 5.0 and the nonlinear regression by plotting percentage of inhibition
versus log (mole fraction) or log (concentration) to calculate the
reported XI(50) and IC50 values and their associated
error.
A Shimadzu HPLC system consisting of a system
controller (SCL-10Avp) with two HPLC pumps (LC-10ADvp), a CTC Analytics
PAL autosampler platform (Leap Technologies), and a column controller
instrument (Analytical Sales & Products, Inc) were employed for
the LC analysis. Mass spectrometric analysis was performed using an
AB Sciex 4000 QTRAP triple quadrupole/linear ion trap hybrid mass
spectrometer equipped with a Turbo V ion source.[10]
Chromatography (HPLC)
For separation
and quantification
of the lysophospholipids, a Phenomenex Kinetex 2.6 μm HILIC
100 Å column of 30 × 2.1 mm size was used. The binary gradient
consisted of (A) ACN/water (95/5, v/v, pH = 8.0) containing 25 mM
AcNH4 and (B) ACN/water (50/50, v/v, pH = 7.5) containing
25 mM AcNH4. Gradient elution was carried out for 1.6 min
at a flow rate of 0.8 mL/min. Gradient conditions were as follows:
0% B for 0.8 min; 0–100% B for 0.4 min; 100% B for 0.3 min;
and 100% B for 0.1 min.[10] For separation
and quantification of free FAs, a Phenomenex Kinetex 2.6 μm
C18 100 Å column of 30 × 2.1 mm size was used. A mobile
phase of ACN/water (80/20, v/v, pH = 8.9) containing 10 mM NH4HCO3 was used in an isocratic elution. A 10 μL
aliquot of each sample was injected into the column. The column temperature
was kept at 40 °C. All samples were maintained at 4 °C throughout
the analysis.
Mass Spectrometry
Lysophospholipids
(primary and internal
standards), phospholipids, and surfactants (C12E8) were detected in
a positive electrospray ionization (ESI) mode, whereas free FAs in
a negative ESI mode. Molecular species were detected as [M + H]+ ions in the positive ion mode and as [M – H]− ions in the negative ion mode. Curtain gas (CUR), nebulizer gas
(GS1), and turbo gas (GS2) were set to 10, 50, and 20 psi, respectively.
The electrospray voltage was set to +4.5 or −4.5 kV, and the
turbo ion spray source temperature was set to 500 °C. Lysophospholipids
were analyzed using scheduled MRM. Declustering potentials and collision
energies were optimized for each analyte to achieve optimal mass spectrometric
detection. Nitrogen was employed as the collision gas. Data acquisitions
were performed using Analyst software. MultiQuant software was used
to quantify all metabolites.
Reagents
Pyrrophenone
was purchased from Cayman Chemical
Company and was stated to be 100% pure based on HPLC and TLC. OTFP
was synthesized by Dr. Bruce Hammock’s group and was stated
to be more than 97% pure based on GC, NMR, and TLC.[18] Ly315920 was purchased from Selleckchem and was stated
to be more that 99% pure based on NMR and HPLC. Phospholipids, primary
standards, and internal standards were purchased from Avanti Polar
Lipids, Inc. Optima LC–MS grade ACN, water (H2O),
and HPLC grade ammonium acetate (AcNH4) were obtained from
Fisher Scientific. HPLC great ammonium bicarbonate (NH4HCO3) was obtained from Spectrum Chemical Mfg. Corp. Octaethylene
glycol monododecyl ether (C12E8) was obtained from Sigma-Aldrich.
MD Simulations
Enzyme–Inhibitor–Membrane Complexes
Initial
complexes of each enzyme with pyrrophenone, OTFP, and Ly315920 were
generated using molecular docking.[19] The
crystal structure of cPLA2,[20] a previously published homology model of iPLA2 based
on patatin,[2] and a previously published
homology model of GV sPLA2 based on GIIA sPLA2 were used for docking.[10] The calculations
were performed using a previously published docking protocol.[12,16] The Membrane Builder implemented in CHARMM-GUI was employed to generate
enzyme–inhibitor–membrane models for MD simulations.[21,22] As previously reported, the membrane patch consisted of POPC, SAPC,
POPE, POPA, POPG, POPS, SAPI(4,5)P2, and cholesterol. The
average ratios of the phospholipids were chosen to be 0.48 for PC,
0.27 for PE, 0.10 for PI(4,5)P2, 0.06 for PS, and 0.09
for PA and PG. The average cholesterol/phospholipid ratio was chosen
to be 0.40. These ratios are the average ratio of the nuclear, mitochondrial,
and plasma membranes where cPLA2, iPLA2, and
sPLA2 are localized, respectively.[23−26] Each system was solvated with
TIP3P water molecules and neutralized with 150 mM sodium chloride
(NaCl) using the Visual MD (VMD) package.[27]
Equilibration and Production Runs
MD simulations were
carried out using NAMD 2.12.[28] The following
minimization and equilibration protocol was performed, as previously
described:[10] a minimization of 80 000 steps
was initially performed by applying harmonic constraints on the enzyme–inhibitor–membrane
that were gradually turned off using a constraint scaling factor,
followed by a second 120 000 steps minimization without constraints.
An initial equilibration of 10 000 steps was performed by also
applying harmonic constraints on the enzyme–inhibitor–membrane
that were gradually turned off using the same constraint scaling factor,
followed by a second 10 000 steps equilibration without constraints.
During the equilibration, each system was slowly heated and held to
310 K using temperature reassignment with a reassignment frequency
of 500 timesteps (1000 fs) and a reassignment increment of 1 K. The
above minimization and equilibration protocol was sufficient to induce
an appropriate disorder of a fluidlike bilayer and avoid unnatural
atomistic positions and failure of the simulations by atoms moving
at very high velocities. Each system was finally subjected to a 1
μs production run. For each production run, the temperature
was maintained at 310 K using the Langevin thermostat with Langevin
coupling coefficient of 1/ps.[29] The NPT ensemble was employed, and the pressure was kept constant
at 1.01325 kPa using the Langevin piston method with the “useGroupPressure”,
“useFlexibleCell”, and “useConstantArea”
parameters turned on.[30] A timestep of 2
fs was used in combination with the SHAKE algorithm to hold the bonds
of hydrogen atoms similarly constrained.[31] Nonbonded interactions and full electrostatics were calculated for
every 1 and 2 timesteps, respectively. Switching functions are used
to smoothly take electrostatic and van der Waals interactions to zero
with a switching distance of 10 Å and a cutoff of 12 Å.
Long-range electrostatic forces in the periodic system were evaluated
using the particle mesh Ewald Sum method with a grid spacing of 1/Å.[32] The CHARMM General Force Field (CGenFF) and
the CHARMM36 all-atom additive force field and parameters were used
for other simulations.[33,34]
Binding Pocket Volume Calculations
The POVME algorithm
was employed for calculating the volume of the binding pocket of each
enzyme over the time of each simulation.[10,35] A total number of 6252 frames from each simulation trajectory was
used for the calculations. The frames were aligned on the initial
complex that was used to carry out the simulation using VMD and were
saved in a multiframe PDB format. To define the “inclusion
sphere” that entirely encloses the binding pocket of each enzyme,
the center of mass of the residues within 5 Å around the bound
inhibitor was used as the x, y,
and z coordinates of the sphere. An “inclusion
sphere” radius of 11 Å was used. Equidistant points were
generated in POVME using a grid spacing of 1 Å and a distance
cutoff of 1.09 Å.
Authors: Christina Dedaki; Maroula G Kokotou; Varnavas D Mouchlis; Dimitris Limnios; Xiaoyong Lei; Carol T Mu; Sasanka Ramanadham; Victoria Magrioti; Edward A Dennis; George Kokotos Journal: J Med Chem Date: 2019-03-12 Impact factor: 7.446
Authors: Maria A Theodoropoulou; Anastasia Psarra; Martin Erhardt; Aikaterini Nikolaou; Anna-Dimitra D Gerogiannopoulou; Dimitra Hadjipavlou-Litina; Daiki Hayashi; Edward A Dennis; Andrea Huwiler; George Kokotos Journal: Biomolecules Date: 2022-02-07
Authors: Varnavas D Mouchlis; Daiki Hayashi; Alexis M Vasquez; Jian Cao; J Andrew McCammon; Edward A Dennis Journal: Proc Natl Acad Sci U S A Date: 2022-01-11 Impact factor: 11.205
Authors: Giorgos S Koutoulogenis; Maroula G Kokotou; Daiki Hayashi; Varnavas D Mouchlis; Edward A Dennis; George Kokotos Journal: Biomolecules Date: 2020-03-24