Fasil Ali1, Usma Manzoor2, Reshmee Bhattacharya3, Aniket Kumar Bansal3, Kempohalli Sayanna Chandrashekharaiah1, Laishram Rajendrakumar Singh3, Suma Mohan Saraswati4, Vladimir Uversky5,6, Tanveer Ali Dar2. 1. Department of Studies and Research in Biochemistry, Jnana Kaveri Campus, Mangalore University, Karnataka 574199, India. 2. Department of Clinical Biochemistry, University of Kashmir, Srinagar 190006, India. 3. Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, New Delhi 110007, India. 4. School of Chemical & Biotechnology,SASTRA Deemed to be University, Tirumalaisamudram, Thanjavur 613401, Tamilnadu, India. 5. Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida 33612, United States. 6. Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center "Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences", Pushchino 142290, Russia.
Abstract
A strong correlation between brain metabolite accumulation and oxidative stress has been observed in Alzheimer's disease (AD) patients. There are two central hypotheses for this correlation: (i) coaccumulation of toxic amyloid-β and Myo-inositol (MI), a significant brain metabolite, during presymptomatic stages of AD, and (ii) enhanced expression of MI transporter in brain cells during oxidative stress-induced volume changes in the brain. Identifying specific interactive effects of MI with cellular antioxidant enzymes would represent an essential step in understanding the oxidative stress-induced AD pathogenicity. This study demonstrated that MI inhibits catalase, an essential antioxidant enzyme primarily inefficient in AD, by decreasing its k cat (turnover number) and increasing K m (Michaelis-Menten constant) values. This inhibition of catalase by MI under in vivo studies increased cellular H2O2 levels, leading to decreased cell viability. Furthermore, MI induces distortion of the active heme center with an overall loss of structure and stability of catalase. MI also alters distances of the vital active site and substrate channel residues of catalase. The present study provides evidence for the involvement of MI in the inactivation of the antioxidant defense system during oxidative stress-induced pathogenesis of AD. Regulation of MI levels, during early presymptomatic stages of AD, might serve as a potential early-on therapeutic strategy for this disease.
A strong correlation between brain metabolite accumulation and oxidative stress has been observed in Alzheimer's disease (AD) patients. There are two central hypotheses for this correlation: (i) coaccumulation of toxic amyloid-β and Myo-inositol (MI), a significant brain metabolite, during presymptomatic stages of AD, and (ii) enhanced expression of MI transporter in brain cells during oxidative stress-induced volume changes in the brain. Identifying specific interactive effects of MI with cellular antioxidant enzymes would represent an essential step in understanding the oxidative stress-induced AD pathogenicity. This study demonstrated that MI inhibits catalase, an essential antioxidant enzyme primarily inefficient in AD, by decreasing its k cat (turnover number) and increasing K m (Michaelis-Menten constant) values. This inhibition of catalase by MI under in vivo studies increased cellular H2O2 levels, leading to decreased cell viability. Furthermore, MI induces distortion of the active heme center with an overall loss of structure and stability of catalase. MI also alters distances of the vital active site and substrate channel residues of catalase. The present study provides evidence for the involvement of MI in the inactivation of the antioxidant defense system during oxidative stress-induced pathogenesis of AD. Regulation of MI levels, during early presymptomatic stages of AD, might serve as a potential early-on therapeutic strategy for this disease.
The leading cause of
Alzheimer’s disease, the most common
neurodegenerative disease in older people, has not been completely
understood but is generally characterized by the deposition of extracellular
β-amyloid (Aβ) aggregates and intracellular neurofibrillary
tangles of hyper-phosphorylated tau protein.[1−4] The amyloid cascade hypothesis
claims that Aβ deposition drives the remaining AD pathology.
Therefore, AD is detected more commonly by analyzing Aβ levels
in cerebrospinal fluid at the biochemical level.[5,6] Moreover,
the accumulation of such toxic protein species results in increased
oxidative stress, leading to synaptic dysfunction and eventual cell
death.[7,8] Molecular-level understanding of the increase
in oxidative stress is currently fairly low. It is well-known that
despite an increase in the expression of the antioxidant enzyme system
(as an attempt to suppress the increased oxidative stress) during
AD pathology, the activity of the main enzyme, catalase, is drastically
reduced, resulting in increased oxidative stress.[9] One central mechanism for the reduced catalase activity
is believed to be the direct interaction of Aβ with antioxidant
enzymes, which inhibits antioxidant functions.[10] Thus, post-translational events (rather than the transcriptional
processes) are believed to result in catalase inactivation, leading
to impairment in the intracellular hydrogen peroxide (H2O2) degradation. Furthermore, AD pathophysiological conditions
also involve specific alterations in the neuronal metabolites, including
Myo-inositol (MI), choline, glutamate, N-acetyl-aspartate, and sorbitol.[11,12] Nevertheless, the molecular mechanisms underlying the altered metabolite
levels and the inactivation of the antioxidant mechanism remain largely
unexplored.Among metabolites, MI is the most relevant molecule
in AD, as its
elevated level is strongly correlated with the Aβ-induced pathology
and the subsequent decline in cognitive performance.[13−15] Interestingly, abnormal brain levels of MI have been detected even
in the presymptomatic stages of AD, before any detectable Aβ
deposits are observed.[15] Clinical studies
have also demonstrated that part of the increased oxidative stress
is taken care of via upregulating MI uptake up to several millimolar
concentrations. Thus, MI appears to be one of the critical metabolites
associated with the decline of the antioxidant potential in AD pathophysiology.
In this study, we attempted to investigate the functional consequences
of MI on the main cytoplasmic antioxidant enzyme, catalase. We discovered
that MI inhibits catalase function by increasing Km and altering the enzyme’s overall structure and
active site. The study highlights a novel role of MI in AD pathophysiology
and mediating cross-talk between the cellular antioxidant enzyme systems
and metabolites.
Results
Effect of MI on Catalase
Activity
The activity of catalase
was measured by monitoring the decrease in absorbance of H2O2 at 240 nm in the presence and absence of the polyol
osmolytes. Kinetic curves, obtained by plotting initial velocity (V0) versus substrate concentration, were analyzed
for Michaelis–Menten constant (Km) and catalytic constant (kcat) (Table ). It was observed
that, in the presence of increasing concentrations of MI, Km increases and kcat decreases. Furthermore, with increasing concentration of MI, kcat/Km , a measure
of catalytic efficiency, decreases from 4.38 × 107 to 1.63 × 107 M–1 s–1. In addition to this, activity of catalase was further carried out
in other polyol compounds like mannitol, glycerol, and sorbitol. It
was observed that Km decreases while kcat increases at all polyol concentrations which
signify increased kcat/km in the presence of the polyols. Altogether, activity
results imply that unlike other polyols MI reduces the activity of
catalase substantially (Table ).
Table 1
Kinetic Parameters of Catalase in
the Presence and Absence of the Polyols
concentration (M)
Km (mM)
kcat (s–1) (× 106)
kcat/Km (s–1 M–1) (× 107)
Myo-inositol
0.00
31.22a
1.37×
4.38 ± 0.13
0.05
32.11
1.29
4.01 ± 0.14
0.15
34.71
1.10
3.17 ± 0.09
0.30
37.28
0.81
2.18 ± 0.08
0.60
38.30
0.62
1.63 ± 0.05
Mannitol
0.00
31.22
1.37
4.38 ± 0.13
0.25
27.74
1.74
6.29 ± 0.23
0.50
25.90
2.04
7.87 ± 0.31
0.70
24.53
2.74
11.17 ± 0.49
Glycerol
0%
31.22
1.37
4.38 ± 0.13
10%
30.33
1.34
4.43 ± 0.14
20%
27.92
1.40
5.02 ± 0.20
30%
26.39
1.54
5.86 ± 0.22
40%
20.78
12.1
58.1 ± 0.37
Sorbitol
0.00
31.22
1.37
4.38 ± 0.13
0.25
30.54
1.38
4.53 ± 0.21
0.50
28.53
1.55
5.42 ± 0.22
0.75
25.11
1.80
7.16 ± 0.24
1.00
22.40
2.02
9.01 ± 0.36
A p-value <0.0001
was observed for all the measurements.
A p-value <0.0001
was observed for all the measurements.
Effect of MI on Catalase Structure
Secondary Structure
For this, far-UV CD spectral measurements
of catalase were carried out in the presence of different concentrations
of MI (0–0.6 M). As can be seen in Figure A, no significant change in the secondary
structure of catalase was observed in the presence of MI (Figure A).
Figure 1
Measurement of catalase
structure in the presence of MI. Panel
A represents far-UV CD spectra of catalase in the absence and presence
of different concentrations of MI. Panel B is representative of Heme
absorption spectra of catalase at a wavelength range of 350–450
nm in the presence of MI. Inset shows the variation of λmax versus [MI]. Panels C and D represent intrinsic and extrinsic
ANS fluorescence spectra in the presence of MI, respectively. Symbols
at the right corner of the respective panel represent different concentrations
of MI used. Panel E represents acrylamide fluorescence quenching measurements
of catalase: Stern–Volmer plots for the acrylamide quenching
of fluorescence of catalase in the absence (■) and
presence of highest concentrations of MI (*) used. Spectra and results
shown are representative of at least three independent measurements.
Measurement of catalase
structure in the presence of MI. Panel
A represents far-UV CD spectra of catalase in the absence and presence
of different concentrations of MI. Panel B is representative of Heme
absorption spectra of catalase at a wavelength range of 350–450
nm in the presence of MI. Inset shows the variation of λmax versus [MI]. Panels C and D represent intrinsic and extrinsic
ANS fluorescence spectra in the presence of MI, respectively. Symbols
at the right corner of the respective panel represent different concentrations
of MI used. Panel E represents acrylamide fluorescence quenching measurements
of catalase: Stern–Volmer plots for the acrylamide quenching
of fluorescence of catalase in the absence (■) and
presence of highest concentrations of MI (*) used. Spectra and results
shown are representative of at least three independent measurements.
Tertiary Structure
Soret Absorption of Catalase
Heme
Absorption spectra
of catalase, exhibiting maximum soret absorption peak around 403 nm,
was obtained in the presence of different concentrations of MI. Upon
addition of MI, a concentration-dependent change in heme absorption
intensity with a significant red shift of about 6 nm (from 403 to
409 nm) was observed (Figure B).
Intrinsic Fluorescence
Here, changes
in the microenvironment
of the tryptophan residues were monitored in the presence of MI. Upon
excitation at 280 nm, fluorescence emission spectra were recorded
with an absorption maximum at 336 nm. In presence of MI, a concentration-dependent
decrease in tryptophan fluorescence intensity with a red shift of
around 8 nm was observed (Figure C).
Solvent-Accessible Hydrophobic Patches in
the Presence of MI
To monitor for any change in exposure
of hydrophobic patches, ANS
binding experiments were carried out. With an increase in MI concentration,
an increase in ANS fluorescence intensity (enhanced binding) with
a prominent red shift of about 11 nm was observed, which indicates
increased exposure of hydrophobic residues to the solvent (Figure D).
Effect of
MI on Compactness of Catalase
Acrylamide
quenching of fluorescence of catalase provides information about the
accessibility of the quencher to the intrinsic fluorophore (trp) as
well as any alteration in the microenvironment of the fluorophore.
For this, acrylamide-induced quenching of trp fluorescence in the
presence of MI was carried out and KD values
were calculated using eq (Figure E). For
control, the value for KD was found to
be 1.28 ± 0.04, while it was found to be 1.51 ± 0.06 in
the presence of MI. Increased KD values
in the presence of MI indicate enhanced exposure of the trp residues
to the surrounding aqueous environment.
Effect of MI on the Conformational
Stability of Catalase
To monitor for any MI-induced change
in the overall stability of
catalase, thermal denaturation studies of catalase were carried out
in the presence of MI. Thermal denaturation profiles, observed in
the presence and absence of MI, were analyzed by using eq , and the observed fD values were plotted as a function of temperature (Figure S1). These plots were further analyzed
for Tm by nonlinear fitting using eq . At 0.6 M MI, a decrease
of around 3.7 °C was observed in Tm of catalase, which suggests an overall decreased stability of catalase
in the presence of MI.
In Silico Studies of Catalase
Docking
Studies
To elucidate any possible interaction
between MI and catalase, molecular docking studies were carried out.
Twenty docking conformations were obtained with MI, and the docked
conformations were found to occupy and cluster at different sites
around the catalase (Figure S2). The binding
affinity of MI for catalase was found to be in the range of −4.7
to −4.2 kcal/mol and the lowest energy conformation was located
near the opening of the heme binding active site channel of catalase,
indicating favorable binding of MI at this position.
Molecular
Dynamics Simulation Studies
To understand
the effect of MI on the overall conformation/structure of catalase,
MDS studies were carried out in the presence of an MI cosolvent system,
where the concentrations for MI ranged up to 0.6 M with simulation
in water alone serving as a control (Table ). Simulation analysis was performed wherein
MDS parameters like root mean square deviation (RMSD), radius of gyration
(Rg), and hydrogen bonds were estimated
(Table ). In the MI
cosolvent system, catalase was found to be highly dynamic and fluctuating
with longer times of equilibration (Figure A, Table ). With respect to RMSD of peptide backbone atoms,
the values were found to decrease insignificantly for MI-bound catalase
(5.13 Å) when compared to catalase alone (5.42 Å). On the
other hand, Rg values showed almost no
change in the presence of MI. However, significant changes in RMSD
values were observed for the protein–heme region with an almost
two-fold increase in RMSD value in the presence of MI (0.63 Å)
compared to catalase alone (0.35 Å). Results obtained for the
heme region indicate that the heme group of catalase in the MI cosolvent
system was found to undergo pronounced structural fluctuations (Figure B). Additionally,
the RMSF plot indicated that fluctuations of the amino acids residues
from 5–70 and 380–480 are quite enhanced (Figure C).
Table 2
Summary
of the Cosolvent Simulation
Systems Used in the Study
system
[MI], M
No. of water molecules
No. of MI molecules
total No. of
atoms
simulation length (ns)
water
0.00
20765
0
70240
20
Myo-inositol
0.60
17789
192
65992
20
Table 3
Summary Statistics from the Trajectory
Analysisa
RMSD
No.
of hydrogen bonds
system
protein Cα (Å)
heme group (Å)
Rg (Å)
intraprotein
protein–water
protein–heme
protein–MI
MI–MI
water
5.42 ± 0.32
0.35 ± 0.04
24.77 ± 0.16
129 ± 13
526 ± 69
4 ± 1
–
–
myoinositol
5.13 ± 0.64
0.63 ± 0.07
24.82 ± 0.20
130 ± 12
389 ± 15
4 ± 1
32 ± 5
10 ± 4
The last 10 ns of the trajectory
were considered for the analysis.
Figure 2
Simulation studies of catalase in the presence of MI. Representative
plots of RMSD of Protein Cα atoms (A) and Heme group (B), RMSF
of Cα atoms (C), and Rg of Cα
atoms (D). Profiles observed from the water and MI simulations are
represented in black and red color, respectively.
The last 10 ns of the trajectory
were considered for the analysis.Simulation studies of catalase in the presence of MI. Representative
plots of RMSD of Protein Cα atoms (A) and Heme group (B), RMSF
of Cα atoms (C), and Rg of Cα
atoms (D). Profiles observed from the water and MI simulations are
represented in black and red color, respectively.
Effect of MI on the Hydrogen Bonding Pattern of Catalase
Presence of hydroxyl groups in MI may allow it to interact with either
water or surface protein groups. To explore the effect of MI on the
interaction network of catalase, hydrogen bond interactions within
the protein, and between the protein, MI, water, and the heme group
were analyzed (Table and Figure S3). The number of intraprotein
hydrogen bonds in the presence of MI was found to be same as that
of water alone (Table ). However, in the MI system a profound decrease in the number of
hydrogen bonds between protein and water was observed with a decrease
from 526 (in water) to 389 (in MI) (Table , Figure S3).
This loss of hydration sphere around catalase might be responsible
for the decreased hydrogen bonding pattern of the catalase with water.
As expected, a very small number of protein–MI hydrogen bonds
were observed (Table and Figure S3).
Effect
on Heme Binding Active Site of Catalase
Altered
catalytic activity of catalase in the presence of MI encouraged us
to investigate its effect on the heme binding active site cavity of
catalase (Figure , Figure S4 and S5). Here, the representative structure
of the catalase (Figure A) was subjected to active site cavity measurements using CASTp program,
and the identified active site cavities were visualized (Figures B,C). As can be
seen from Table S1, an expansion of the
active site cavity near the entrance of the channel with a volume
of 577 Å3 was observed in the presence of MI. In addition
to this, noticeable fluctuations in the threading arm (residues 1–66)
and wrapping loop (residues 376–439) of catalase (Figures A,C) were observed.
In the superposed conformation (Figure A), we could see that the threading arm and the wrapping
loop, in the case of the MI system (gray and orange), were getting
rearranged and coming close to the β-barrel part, that is, central
core of the catalase fold.
Figure 3
Binding of MI to heme active site of catalase.
Panel A is a representative
structure of catalase in water (gray) and MI cosolvent system (orange).
Panels B and C represent an active site cavity identified in water
(B) and MI (C) cosolvent system using CASTp program.
Binding of MI to heme active site of catalase.
Panel A is a representative
structure of catalase in water (gray) and MI cosolvent system (orange).
Panels B and C represent an active site cavity identified in water
(B) and MI (C) cosolvent system using CASTp program.To further elucidate the observed effects of MI on the heme
binding
active center (Figure S4 and S5), the distance
of some of the catalytically important residues, such as His74 and
Asn147, with respect to the iron in the heme center, was monitored.
As can be seen in Figure , Asn147 and Tyr357 are maintained at a larger distance from
the heme iron in the presence of MI (Figure A–C). Results suggest that the altered
distance between the residues and the heme iron might have contributed
towards the MI-induced modulation of catalase activity. Additionally,
the distance between other important channel residues, including Gln167-Leu198
and Asp127-Trp185, was also analyzed (Figure D,E). In the presence of MI, a respective
increase and decrease in the distance of Cα atoms of the Gln167-Leu198
and Asp127-Trp185, with respect to the heme center, was observed.
Furthermore, MI shows binding interaction with various hydrophobic
residues lining the heme active site channel, including Val125, Arg126,
Trp185, Val181, His465, Trp185, and Val181 (Figures S5 and S6).
Figure 4
Representative plots of distance between catalytically
important
residues and iron of heme group in catalase. Panels represent distances
of His74 (A), Asn147 (B), and Tyr357 (C) and regions Gln167-Leu198
(D) and Asp127-Trp185 (E) in the absence and presence of MI. Profiles
from the water and MI simulations are represented in black and red
color, respectively.
Representative plots of distance between catalytically
important
residues and iron of heme group in catalase. Panels represent distances
of His74 (A), Asn147 (B), and Tyr357 (C) and regions Gln167-Leu198
(D) and Asp127-Trp185 (E) in the absence and presence of MI. Profiles
from the water and MI simulations are represented in black and red
color, respectively.
Effect of MI on the Redox
State of Heme Iron
To verify
whether MI has any effect on the oxidation state of Fe-center of heme,
H2O2 decomposition by hemin chloride was monitored
in the presence and absence of MI (Figure A). As can be seen in Figure A, no significant change was observed in
the rate of H2O2 degradation by hemin chloride
in the presence of MI.
Figure 5
Effect of MI on redox status of heme. Panel A represents
H2O2 degradation profile of hemin chloride and
panel
B represents EPR spectra of catalase in the presence and absence of
MI. All the experiments were done in triplicate, and results presented
are derived from three independent measurements. For all measurements,
the standard mean error (SEM) ranged from 0.01% to 0.05% across all
the wavelengths monitored.
Effect of MI on redox status of heme. Panel A represents
H2O2 degradation profile of hemin chloride and
panel
B represents EPR spectra of catalase in the presence and absence of
MI. All the experiments were done in triplicate, and results presented
are derived from three independent measurements. For all measurements,
the standard mean error (SEM) ranged from 0.01% to 0.05% across all
the wavelengths monitored.Furthermore, EPR measurements of catalase were carried out in the
presence of MI to confirm any perturbation in the redox state of catalase
heme. As can be seen in Figure B, no alteration in the redox status of the catalase heme
moiety was observed in the presence of MI. Altogether, results infer
that the MI-induced loss of catalase activity is not due to any change
in the redox status of heme center of catalase.
Effect of
MI on Cell Viability
Using MTT assay, the
effect of MI on viability of HeLa cell lines was investigated. On
treatment of cells with MI, a percentage decrease of about 20% was
observed in the concentration of viable HeLa cells, suggesting a cytotoxic
effect of MI on HeLa cells (Figure A).
Figure 6
Effect of MI on cell viability. Panel A represents cell
viability
in the presence of MI with right bar showing the percent viability
of Hela cell lines in the presence of MI. Panels B and C represent
flow cytometric analysis of MI-induced cell cycle arrest and ROS generation
in Hela cell lines, respectively. Experiments were done in triplicate.
A p-value <0.0001 was considered statistically significant.
Effect of MI on cell viability. Panel A represents cell
viability
in the presence of MI with right bar showing the percent viability
of Hela cell lines in the presence of MI. Panels B and C represent
flow cytometric analysis of MI-induced cell cycle arrest and ROS generation
in Hela cell lines, respectively. Experiments were done in triplicate.
A p-value <0.0001 was considered statistically significant.
Effect of MI on Cell Cycle Progression
For this, quantification
of cell cycle phases of HeLa cells after 24 h of MI treatment was
performed using propidium iodide dye, which stains cellular DNA. Flow
cytometry analysis showed that in the presence of MI, the cell cycle
progression stopped and the cells were arrested at the G1 phase, as
indicated by the increased population of cells (about 51%) in this
phase (Figure B).
Effect of MI on ROS generation
Using fluorescence microscopy,
the effect of MI on ROS generation in cells was monitored with the
help of a fluorescent dye, DCFH-DA (Figure C). Intracellular esterases cleave DCFH-DA,
producing a relatively polar and cell membrane impermeable nonfluorescence
product (H2DCF). This nonfluorescent molecule accumulates intracellularly,
and subsequent oxidation yields the highly fluorescent product DCF.
The redox state of the sample was then monitored by measuring fluorescent
intensity. In our case, HeLa cells were treated with MI (0.2 M) and
then stained with DCHF-DA, a ROS scavenger. It was observed that upon
treatment with MI, the fluorescence intensity was found to increase
5-fold (Figure C),
indicating oxidation of H2DCF to DCF, which is possible due to increased
ROS levels in HeLa cells.
Discussion
Our
results on activity measurements revealed inhibition of catalase
function by MI with a Km increase of 7.08
mM (Table ). Consequently,
the overall catalytic efficiency (kcat/Km) decreased to 63% in the presence
of the highest concentration of MI (0.6M). Interestingly, the inhibitory
behavior was found to be confined to MI only as all other polyols
(the class of compounds to which MI belongs) increased functional
activity of the catalase (Table ). Inhibition of catalase activity indicates that MI
may perhaps be a ligand for catalase. For this, we have intentionally
performed blind docking of MI to the native catalase using Autodock
Vina. As evident in Figure S2, MI binds
at the vicinity of the heme binding site (comprising Val125, Arg126,
Trp185, and Val181) with a free energy change of −4.7 to −4.2
kcal/mol (Figure S2). Thus, inactivation
of catalase by MI might be due to binding of MI in the vicinity of
the active site of catalase which in turn should affect the substrate
accessibility.The peroxidase activity of catalase is due to
the presence of iron
(Fe2+) in a specialized porphyrin ring present in the protein.[16−18] The Fe2+ form of iron could donate one electron to H2O2 and cleave it into O2 and H2O, thereby converting the enzyme into its inactive oxidized state
(Fe3+). Therefore, a change in the oxidation state from
Fe2+ to Fe3+ should be a signature for the nonfunctionality
of catalase. To verify this possibility, we performed two key experiments.
First, we analyzed the oxidation state of the MI-treated catalase
by measuring EPR spectra. Second, the peroxidase activity of the hemin
(non-protein part of catalase) was also examined in the presence of
MI. As evident in Figure B, there is no alteration in the oxidation state and consequently
no significant change in the peroxidase activity of hemin. Taken together,
the results indicate that MI-mediated enzyme inactivation is not related
to the non-protein part (porphyrin ring) and might thus involve the
protein part of catalase. It is possible that MI-induced conformational
changes in catalase might result in its inability to pick a substrate
due to the decreased accessibility of the substrate to the active
site or hampering its catalytic mechanism in some other way.Conformational analysis revealed no change in the secondary structure
(Figure A), but the
tertiary contacts appeared to be distorted (Figure C). In terms of the tryptophan microenvironment,
significant changes were observed in λmax and hyperchromicity
(Figure C,D). Concomitantly,
we also observed a slight increase in acrylamide quenching behavior
in the MI-treated catalase as compared to the control (Figure E) which must have resulted
in the blue shift in trp microenvironment. The observed red shift
in Figure C might
be due to unusual reshuffling of many of the trp residues in the nonpolar
environment while few might be in the polar environment exposed to
the solvent. Enhanced binding of ANS in MI-treated catalase further
indicates that some of the hydrophobic groups are also exposed to
the solvent (Figure D). Furthermore, the overall tertiary changes force the exposition
of the catalytic heme center to the solvent (Figure B). In agreement, there is an overall decrease
in the thermodynamic stability of the protein (Figure S1), which may be due to the distortion of the tertiary
contacts. Taken together, the results suggest that MI binding induces
a functionally deficient non-native state in catalase, characterized
by an intact secondary structure with altered tertiary contacts and
distorted heme microenvironment.Next, we investigated the molecular
level structural alterations
in catalase due to MI binding by performing MD simulations in the
presence of the MI cosolvent system. Generally, a quantitative description
of the global effect of ligands on the overall conformation of proteins
is described in terms of RMSD and Rg profiles,
followed by measuring dynamics of inter/intramolecular hydrogen bonding
interactions. Similar to the results obtained in secondary structure
measurements (Figure A), there is no significant change in RMSD and Rg parameters in catalase-MI system when compared to catalase
alone (Table and Figure ). Furthermore, the
significant decrease in catalase–water hydrogen bonding interaction
in the presence of MI and the consequent increase in MI–protein
hydrogen bonding interaction indicates that MI binds to catalase by
replacing water molecules from the protein hydration sphere (Table ).We also observed
a large increase in RMSD values of heme moiety
in the presence of MI (almost two-fold compared to the control), implying
major structural fluctuations in the microenvironment of the heme.
Catalase contains four heme groups buried deep within the individual
subunits of catalase. It has a long amino-terminal threading arm,
an antiparallel eight-stranded β-barrel, a wrapping loop, four
α-helical domains, and a C-terminal helical domain. The extended
threading arm (residues 5–70) stabilizes the quaternary structure
by interconnecting two subunits and hooking through a long wrapping
loop (residues 380–480) around another subunit. The heme is
positioned in the middle of each subunit, with the distance between
the iron and the center of the tetramer being around 23 Å and
around 20 Å between the iron and the external surface. In addition
to the changes in the heme binding site, noticeable fluctuations in
the threading arm and wrapping loop of catalase (Figure A,C) were observed. In fact,
in the superposed conformation (Figure A), we could see that the threading arm and wrapping
loop of catalase (in the presence of MI) (gray and orange) come close
to the β-barrel part of catalase (Figure B,C). RMSF measurements also revealed higher
fluctuations in residues related to the threading arm and wrapping
loop regions of the protein (Figure C), indicating minute tertiary/quaternary level conformational
changes. Thus, the results on MDS studies are in excellent agreement
with those of the spectroscopic studies.In catalase, substrate
accessibility towards the heme iron (or
proper affinity) is regulated with the help of a 20 Å funnel-shaped
substrate channel, that is, the part of the enzyme responsible for
connecting the deeply buried heme with the surface. At the neck of
this channel are four residues including Asp 127, Trp185, Glu167,
and Leu198, which play a key role in catalytic activity of the enzyme.
It is also known that distances between Glu167–Leu198 and Asp127–Trp185
play a major role in determining the channel diameter. Therefore,
we intentionally studied the channel size and the distances of these
two residues (Figure ). Interestingly, an overall decrease in the channel diameter with
a consequent increase in distance between Asp127–Trp185 (but
not Glu167–Leu198) was observed. The distances between His74
and Asn147 with the iron center, aiding in electron transfer reaction
during catalysis, were also altered and significantly decreased due
to reduction in channel diameter (Figure A,B). Furthermore, MI also forms binding
contacts with various hydrophobic residues associated with the narrow
heme part of active site channel, including Ala116, Phe152, Phe153,
Trp185, Val181, Val 185, Val125, and Arg126 (Table S1, Figures S5 and S6). Thus, binding
to these residues and the longer distance between Asp127–Trp185
might force a decrease in channel diameter, thereby limiting the substrate
entry to the catalytic site. In support of this argument, it has been
demonstrated that modulation of catalase activity by various compounds
has been attributed to the altered channel size by inducing overall
conformational changes in the enzyme.[19,20]To further
support our results on MI-mediated catalase inhibition,
we performed cellular level studies by treating HeLa cells with MI
and measured cell viability and oxidative stress. As evident in Figure , a decrease in cell
viability was observed in the presence of MI (Figure A) with around a 5-fold increase in ROS level
(Figure C) leading
to inhibition of the cell cycle at the G1 phase (Figure B). Intracellular esterases
cleave DCFH-DA at the two ester bonds, producing a relatively polar
and cell membrane impermeable product, H2DCF. This nonfluorescent
molecule accumulates intracellularly, and subsequent oxidation yields
the highly fluorescent product DCF. The redox state of the sample
was then monitored by detecting the fluorescent intensity. In our
case, HeLa cells after treatment with MI (0.2 M), followed by staining
with DCHF-DA, a ROS scavenger, observed a 5-fold increase in the fluorescence
intensity (Figure C), indicating oxidation of H2DCF to DCF and thus resulting in increased
ROS level generation in HeLa cells. Altogether, the results conclude
that decreased cell viability, observed in MTT assay, is due to the
arrest of cells in G1 phase probably due to the inefficient antioxidant
system as enhanced production of ROS was observed in the presence
of MI. The inefficient antioxidant system in turn results in oxidative
stress in the cells. Since H2O2 is a signaling
molecule involved in cell proliferation, autophagy, and apoptosis,[21−24] the results indicate that regulation of MI levels during oxidative
stress disorders could serve as a potential therapeutic strategy for
neurodegenerative diseases like Alzheimer’s.
Significance
Our results indicate that MI might act as a specific inhibitory
ligand for catalase and could be responsible for the inefficient,
otherwise overexpressed, antioxidant enzyme system during presymptomatic
stages of AD. In other words, one of the primary causes for the compromised
antioxidant defense system during oxidative stress stages of AD could
be attributed to the increased MI concentrations in the brain. Furthermore,
the observed results suggest that caution should be taken with prolonged
use of MI and its derivatives as promising supplements for preventing
female infertility, restoring polycystic ovary syndrome, type-II diabetes,
bronchial dysplasia, and cardiovascular disorder.[25−31]
Materials and Methods
Bovine liver catalase, myo-inositol,
and 8-anilino-1-naphthalene
sulfate (ANS) were obtained from Sigma Chemical Co. U.S.A. Disodium
hydrogen orthophosphate and sodium dihydrogen orthophosphate were
purchased from Himedia laboratories while H2O2 was obtained from Merck, Darmstadt, Germany. All other reagents
used in the study were of analytical grade. HeLa cells were purchased
from National Centre for Cell Science, Pune, India.
Preparation of Stock Solutions
The stock solution of
catalase was prepared in 0.05 M degassed sodium phosphate buffer of
pH 7.0. Prior to its use, the protein solution was dialyzed overnight
in 0.1 M KCl at 4 °C, and its concentration was determined spectrophotometrically
using molar extinction coefficient (ε405) value of
3.24 × 105 M–1cm–1. H2O2 solution, prepared in 50 mM phosphate
buffer of pH 7.0, was always fresh and its concentration was determined
using a molar extinction coefficient (ε240) value
of 40 M–1cm–131. The stock solution
of MI was prepared in 50 mM sodium phosphate buffer, pH 7.0. All
the reaction mixtures were checked for any pH change upon addition
of MI, which in most of the cases was found to be insignificant.
Measurement
of Catalase Activity
Activity measurement
of catalase was carried out by spectrophotometric method, using Agilent
Cary 100 UV/vis spectrophotometer, wherein a decrease in the absorbance
of the substrate, H2O2, was monitored in the
presence of catalase.[32,33] For monitoring the effect of
MI on catalase activity, catalase at a concentration of 10 nM was
preincubated in different concentrations of MI. A reaction was initiated
upon addition of H2O2 to the reaction mixture
containing preincubated catalase, and the catalase-mediated degradation
of the substrate was followed by measuring the change in the absorbance
of H2O2 at 240 nm for 20 min. From each progress
curve and at a given substrate concentration, the initial velocity
(V0) was determined from the linear portion
of the kinetic curve. Catalase-mediated H2O2 degradation reaction observed first order rate kinetics, wherein
the rate of reaction was found to depend on H2O2 concentration.[32] Plots of V0 versus substrate concentrations were analyzed for the
kinetic parameters (Km and kcat) using eq where V0 is the
initial velocity of the enzyme, Km is
Michaelis–Menten constant, S is substrate
concentration, and Vmax is the maximum
velocity of the enzyme.
Absorption Measurements
Absorption
spectra of catalase
(0.3 μM) in the presence and absence of MI (0.05, 0.15, 0.3,
and 0.6 M) at 25 ± 0.1 °C were obtained in the wavelength
range of 350–450 nm by using Agilent Cary 100 UV–vis
spectrophotometer. The soret region of catalase showed a maximum absorbance
around 403–405 nm, a typical region for the presence of a heme
group.[34,35] The effect of MI on the absorption spectra
of catalase heme was monitored by following change in absorption intensity
and maximum absorption wavelength (λmax) shift.
Fluorescence Measurements
Intrinsic
fluorescence measurements
of catalase in the presence and absence of MI were carried out at
25 °C, pH 7.0 by using Cary Eclipse fluorescence spectrofluorometer.
Fluorescence spectral measurements were recorded in the wavelength
range of 300–500 nm with excitation wavelength of 295 nm and
bandwidth of 10 nm.
Extrinsic (ANS) Fluorescence
Extrinsic
fluorescence
measurements, through ANS binding assays, were carried out to detect
any change in the exposure of surface hydrophobic patches of catalase
in the presence of different concentrations of the MI. For this, the
excitation wavelength was set at 360 nm, and the emission spectra
were recorded in the wavelength range of 400–600 nm with a
catalase concentration of 0.3 μM. All the samples were run
in triplicates. ANS concentration was kept 16-fold higher than that
of the protein concentration, and all the samples were prepared in
dark to avoid photodecomposition of ANS.
Acrylamide Quenching
Acrylamide quenching of intrinsic
fluorescence of catalase at 295 nm was carried out by titrating catalase
with acrylamide in the presence of MI. The data obtained was analyzed
by Stern–Volmer model using eq where F0 and Fi represent protein fluorescence intensity in
absence and presence of varying concentrations of quencher, respectively. Q is the concentration of quencher used and KD is the Stern–Volmer constant related to the fluorophore
lifetime and the bimolecular quenching constant.
Circular
Dichroism Measurement
Far-UV circular dichroism
(CD) spectral measurements in the presence and absence of MI were
carried out at a wavelength range of 200–240 nm with a catalase
concentration of 0.5 μM. The spectra were recorded on Jasco
J-810 spectropolarimeter equipped with a temperature-controlled Peltier
system under constant nitrogen flow at a scan speed of 50 nm/min in
a cuvette of path length 0.1 cm. Necessary corrections for reference
samples were also carried out.
Thermal Stability Measurement
In this, thermal denaturation
of catalase in the presence of MI was monitored by using Cary 100
UV–vis spectrophotometer equipped with a temperature-controlled
Peltier system. All the solutions were prepared in 0.05 M phosphate
buffer, pH 7.0. Each sample with a catalase concentration of 0.2 μM
was heated from 25 to 85 °C at a rate of 1 °C/min and the
change in absorbance was followed at 280 nm. Heat-induced denaturation
curves were analyzed for fD (fraction
unfolded) using eq where y is the optical property
at a certain temperature and MI concentration, and yN and yD are the optical properties of native
and denatured states of catalase, respectively.The heat-induced
transition curves were further analyzed for melting temperature, Tm, using a nonlinear least-squares analysis
method according to eq where y(T) is the optical property at temperature T (Kelvin), YN(T) and YD(T) are the
optical properties of the
native and denatured protein at T (K), respectively, R is the gas constant, and ΔHm is the enthalpy change.
Molecular Docking Measurements
The crystal structure
of the catalase with PDB ID 1TGU was selected for the docking studies. The chain A
of the crystal structure with heme moiety in the binding site was
optimized using the protein preparation wizard in Schrodinger Release
2016-1.[36] The structure of MI (Pubchem
ID: 892) was obtained from Pubchem Database and optimized using the
ligprep module of Schrodinger. The docking studies were performed
using Autodock Vina with a grid box covering the whole protein structure
and the number of conformations at 100.[37]
Molecular Dynamic Simulation (MDS) Measurements
Simulation
System
An optimized structure of the catalase
chain A with PDB ID 1TGU was used for the simulation studies. Two separate simulation systems
were prepared, one without MI (in water alone) and one with MI as
a cosolvent. Details of the simulation systems are summarized in Table . The simulation system
was prepared using Chimera[38] and simulation
setup option in Desmond. A cubic box with a 10 Å buffer between
the system and the edge of the box was used including periodic boundary
conditions. In case of the cosolvent systems, the MI molecules, as
per their molarity, were placed inside the box. The system was solvated
using the TIP3P water model and ions were added to neutralize the
system. The system was relaxed using the default protocol in Desmond.
Subsequently, MDS studies were carried out for 20 ns for each system
in the NPT ensemble using a Nose–Hoover chain thermostat (300
K) and a Martyna–Tobias–Klein barostat (1 Atm) with
OPLS 2005 force field parameters.
MDS Analysis
The
analysis of the three simulated trajectories
were carried out using the simulation quality analysis in Maestro
in the Schrodinger Release 2016-1[39] and
VMD1.9.4.[40] Trajectories were analyzed
for total energy, root mean square deviation (RMSD), root mean square
fluctuation (RMSF), radius of gyration (Rg), number of hydrogen bonds, and radial distribution function (RDF).
The plots obtained were generated using Qtgrace.[44] A representative structure from the three simulations was
selected based on the clustering approach using the clustering plugin
in VMD 1.9.4.[40] On the basis of CA atoms
with an RMSD cutoff of 3 Å, the last 10 ns of the trajectory
from each simulation was considered for clustering. The protein conformations
were visualized using Chimera,[38] and the
heme interaction diagram was prepared using Ligplus.[41] The cavity volumes were measured using the CASTp program,[42] and the cartoon representations of the protein
structures were generated using Chimera.
Measurement
of H2O2 Decomposition by Hemin
Chloride
Absorption spectra of the MI treated and untreated
hemin chloride were recorded with Agilent Cary 100 UV/vis spectrophotometer
equipped with a Peltier-type temperature controller at 37 °C.
The concentrations of hemin and H2O2 were 5
and 300 μM, respectively, and the decomposition progress was
followed at 240 nm for 30 min. A sample cell of 1.0 cm path length
was used for all measurements.
Electron Paramagnetic Resonance
(EPR) Measurements
EPR measurements were carried out in a
Bruker EMX MicroX spectrometer.
Conditions used for the measurements included gain, 1 × 105; modulation amplitude, 7G; microwave power, 0.677 mW; temperature,
298 K and conversion time, 40 ms. Samples with catalase concentration
of 20 μM were loaded in sealed quartz capillary tubes and transferred
to the EPR cavity to obtain spectra.
Cell Viability Assay
For this, MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium
bromide) assay was conducted as outlined by Mosmann with slight modifications.[43] Briefly, cells with a density of 5 × 104 cells/ml were seeded in a 96-well plate and incubated in
a humidified CO2 incubator for 24 h to allow for cell attachment.
After 24 h of MI (200 mM) treatment, the cell viability was measured.
Following this, 20 μL of MTT reagent (5 mg/mL) was added to
each well and incubated for 4 h. Formazan crystals were dissolved
by adding DMSO and absorbance at 570 nm was monitored by using an
ELISA microplate reader.
Measurement of Reactive Oxygen Species (ROS)
Generation
HeLa Cells (1 × 106 cell/ml) under
standard conditions
were seeded in a 12-well plate containing media and allowed to attach
for 24 h. Following this, the cells were treated with MI (200 mM).
After 24 h of incubation, the media was removed and 25 μM of
DCFDA dye was added to each well and kept in the dark for 45 min before
fluorescence imaging by using Flow cytometry.
Cell Cycle
Analysis
Cell cycle progression of HeLa
cells was monitored by using propidium iodide (PI) dye. Analysis of
cell cycle progression was performed on the basis of DNA content of
cells treated with MI. After 24 h of incubation, cells were treated
with RNase A and PI dye and were kept in the dark. After centrifugation,
the cells obtained were analyzed for cell cycle phase distribution
by using flow cytometry.
Statistical Analysis
Results are
expressed as mean
± SEM; n is indicated in the figures and/or
legends. Results were analyzed by two-tailed student’s test
or 1- or 2- way ANOVA, wherever appropriate, using GraphPad prism
software. A Bonferri posthoc test was used to test for significant
differences revealed by ANOVA. A p-value of <0.05
was considered statistically significant.The t test was also performed on the MD simulation data for RMSD (protein
Cα and heme group), Rg, and no.
of hydrogen bonds (intraprotein, protein–water, protein–heme)
between water and MI simulations using R 4.1.2.[45] The data from the last 10 ns of the trajectory from each
simulation were used for the analysis. A significant difference (p-values <0.001) was observed between simulation data
(RMSD, Rg, and no. of H-bonds) from water
and MI simulations.
Authors: W Huang; G E Alexander; E M Daly; H U Shetty; J S Krasuski; S I Rapoport; M B Schapiro Journal: Am J Psychiatry Date: 1999-12 Impact factor: 18.112
Authors: Anna M Vetrano; Diane E Heck; Thomas M Mariano; Vladimir Mishin; Debra L Laskin; Jeffrey D Laskin Journal: J Biol Chem Date: 2005-08-02 Impact factor: 5.157
Authors: Stephen Ashwal; Barbara Holshouser; Karen Tong; Teresa Serna; Renatta Osterdock; Matthew Gross; Daniel Kido Journal: Pediatr Res Date: 2004-08-04 Impact factor: 3.756
Authors: Payam Emami Khoonsari; Anna Häggmark; Maria Lönnberg; Maria Mikus; Lena Kilander; Lars Lannfelt; Jonas Bergquist; Martin Ingelsson; Peter Nilsson; Kim Kultima; Ganna Shevchenko Journal: PLoS One Date: 2016-03-07 Impact factor: 3.240