cellular, molecular and in silico evaluation of mechanism of action chapter 5...

Cellular, molecular and in silico evaluation of mechanism of action Chapter 5

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Summary

Efficacy of test compounds in chronic inflammatory conditions involving different TH cell

subtypes (TH1/TH2/TH17), suggests a probable cellular mechanism of action involving

modulation of TH cell polarization. NFκB activation plays an important role in pro-

inflammatory cytokine production, essential in TH cell polarization. Accordingly, expression

of COX2, a downstream marker of NFκB activation, was evaluated in LPS-stimulated

macrophages. The test compounds inhibited COX2 expression to varying levels of efficacy.

On the other hand, activation of Nrf2 (an anti-inflammatory transcription factor) has been

implied as a plausible mechanism of action for non-ulcerogenic anti-inflammatory agents.

Hence, expression of HO1, a major gastroprotective downstream marker of Nrf2 activation,

was evaluated in the presence of test compounds. While all four test compounds inhibited

COX2 expression, only DHPO and DMFO enhanced HO1 expression. AMPK activation,

while suppressing NFκB, also activates Nrf2, thereby orchestrating the inflammatory process

at a broader and higher level. Protein expression studies indicate that all the four test

compounds phosphorylated AMPKα. In induced fit docking studies on AMPKα, DMPI

binding exhibited least overall energy, comparable to curcumin. All four test compounds

were superior to metformin in AMPKα binding. Thus, the observed anti-inflammatory

activities of the test compounds may be at least partly the result of TH cell modulation

mediated via AMPK activation and its downstream target NFκB. The non-ulcerogenicity of

DMFO and DHPO may be also mediated via Nrf2 activation. Though most effective in both

cell-based and in-vivo models of inflammation, DMFO was uniformly moderate in

mechanistic studies, further demonstrating the value of temperance in modulating

inflammatory pathways comprehensively, akin to natural products.

5.1 Introduction

Dysregulated and persistent inflammation mediated by the adaptive immune system underlies

chronic inflammation. Among the different subtypes of TH cells (Jin et al., 2012), TH1, TH2,

TH17 and Treg are the most widely documented in chronic inflammation. TH1 is involved in

cell-mediated immunity and is pro-inflammatory, whereas TH2 is involved in humoral

immunity and is also anti-inflammatory (Allen and Wynn, 2011). TH17 amplifies a pro-

inflammatory response and also activates neutrophils and macrophages (Souto et al., 2014).

TH17 is implicated in a variety of immune disorders including IBD, RA, multiple sclerosis,

asthma, psoriasis, etc (Tesmer et al., 2008). The four TH cell subtypes are activated by unique

cytokines, and are involved in a yin-yang relation based on the cytokines that they produce.

IFNγ, IL2, etc are TH1-specific; IL4, IL5, IL13, etc are TH2-specific; IL17A, IL21, etc are


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TH17-specific; and IL10 is Treg-specific (Bourke et al., 2013). IL6 inhibition can tip the

balance towards anti-inflammatory Treg polarization (Zhu and Paul, 2008, Afzali et al., 2007).

An imbalance between TH1 and TH2 or TH17 and Treg underlies several immune-mediated

chronic inflammatory conditions (Sundrud et al., 2009, Romagnani, 2004, Nistala and

Wedderburn, 2009). Orally bioavailable non-toxic small molecules that target TH cell

inflammatory responses may be potential therapeutic agents in chronic inflammation.

Redox-sensitive transcription factor NFκB induces TH cell differentiation and activation

(Tomita et al., 2002, Gerondakis et al., 2014, Oh and Ghosh, 2013). NFκB induces

expression of genes for IFNγ (Tomita et al., 2002), IL4 (Oh and Ghosh, 2013), IL17 (Oh and

Ghosh, 2013), etc, in addition to a role in Treg development (Oh and Ghosh, 2013). NFκB is

implicated in asthma, IBD, RA and some cancers (Das et al., 2001). As NFκB induces the

transcription of inflammatory mediators such as cytokines, chemokines, iNOS, COX2, etc

(Tomita et al., 2002), agents that target NFκB may be useful in inflammatory diseases.

Nrf2 is a redox-sensitive transcription factor that has anti-inflammatory and cytoprotective

roles (Kumar et al., 2011). Nrf2 and NFκB cross regulate each other (Piao et al., 2011). Nrf2

can inhibit NFκB activation by reducing cellular oxidant levels, while NFκB can antagonize

Nrf2 activity. p65 subunit of NFκB can decrease Nrf2 binding to DNA, enhance Nrf2

ubiquitination, or bind to Keap1, leading to increased nuclear localization of Keap1 (Yu et

al., 2011, Salminen and Kaarniranta, 2012), all of which inhibit Nrf2 activation. Nrf2, upon

activation, translocates into the nucleus and binds to ARE of target genes, leading to

expression of antioxidant and cytoprotective enzymes including gastroprotective HO1(Surh

et al., 2008, Li et al., 2004, Steele et al., 2013).


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Evidence from literature suggests that Nrf2 activators may be gastroprotective anti-

inflammatory agents. PPIs eg., pantoprazole enhances Nrf2/HO-1 in rats (Hahm et al., 2012).

Curcumin can modify cysteine thiols present in Keap1 (Kumar et al., 2011) resulting in Nrf2

activation. Nrf2 activation is also reported to promote TH2 differentiation (Rockwell et al.,

2012).

AMP-activated kinase (AMPK) is a highly conserved serine/threonine protein kinase, which

is composed of a catalytic subunit and regulatory subunits, acting as a sensor of increased

levels of AMP and ADP, consequent to ATP depletion (Steinberg and Kemp, 2009; Hardie,

2011; Mihaylova and Shaw, 2011). AMPKα subunit has a kinase domain at N terminus,

activation loop, alpha-hook, and a conserved C terminal domain, which interacts with

AMPKγ and AMPKβ subunits. AMPK activation suppresses anabolic processes and activates

catabolic processes (Jager et al., 2007, Mor and Unnikrishnan, 2011). Allosteric stimulation

by AMP results in a two fold increase in activity (Chandrashekarappa et al., 2013). Thr172

phosphorylation activates the catalytic subunit resulting in a 500 fold increase in activity

(Chandrashekarappa et al., 2013).

AMPK activation in TH cells is particularly important because of its role in anti-inflammatory

TH cell polarization (O’Neill and Hardie, 2013, Chi, 2012). AICAR demonstrated therapeutic

potential in a murine model of IBD by reducing TH1 and TH17 activation and inhibiting

NFκB activation (Bai et al., 2010b). Several mechanisms for AMPK activation exist, such as

antagonizing autoinhibition of AMPKα (Pang et al., 2008), allosteric stimulation by AMP

analogue like ZMP (eg. AICAR) (Pang et al., 2008), Thr172 phosphorylation in activation

loop of α-subunit (Chandrashekarappa et al., 2013), activation by upstream AMPK kinases

such as LKB1, CaMKK, etc (Pang et al., 2008), increased cellular AMP:ATP ratio,


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protection of kinase domain from dephosphorylation (eg. Staurosporine) (Chandrashekarappa

et al., 2013), etc. Metformin interacts with γ subunit of AMPK (Zhang et al., 2012), and also

increases concentration of AMP. Berberine indirectly activates AMPK by inhibiting complex

I in mitochondria (Turner et al., 2008). Activator A769662 binds AMPKβ (Young, 2009). It

is reported that binding to regulatory subunit may be more selective, but the hit rate at this

target is reported to be very low (Sinnett et al., 2013).

Docking is a computer-based algorithm that evaluates ligand-receptor binding. In induced fit

docking, an energy minimized protein and all possible conformations of the ligand in 3D are

subjected to docking. Several isoforms of AMPKα exist, but lymphocytes express only α1

(Mayer et al., 2008). Therefore, we chose mammalian AMPKα1β2γ1 (Protein data bank

Accession code PDB ID : 2Y94 (present PDB ID : 4CFH), source rat (Carling et al., 2011),

containing the lymphocyte-specific isoform α1, for the docking studies. Conformational

adjustments are carried out in order to obtain the best fit and minimal free energy, following

which, the ligand-receptor poses are scored, which, in Glide, is called GScore (XP score)

(lowest kCal/mol).

5.1.1 Objectives:

In the treatment of chronic conditions involving a plethora of mediators, drugs which target a

single mediator/receptor are likely to be either suboptimally effective or suffer from

toxicities, for example, the adverse CV events associated with selective COX2 inhibitors

(Dieppe et al., 2004, Zheng et al., 2014, Unnikrishnan et al., 2014). In this context, the

pleiotropic nature of our compounds presents an opportunity for identifying possible

molecular mechanisms that ensure gastroprotective anti-inflammatory modulation oriented


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towards multiple targets. Hence, our aim was to explore the cellular and molecular

mechanism of action of the test compounds which had non-ulcerogenic anti-inflammatory

activities.

The specific objectives of the present study were:

To understand the cellular mechanism of action of test compounds targeting TH cells

To understand the molecular mechanism of action of test compounds targeting COX2,

HO1 and AMPK

To perform docking studies of test compounds on AMPKα

5.2 Materials and methods

5.2.1 Chemicals

Mouse TH1/TH2/TH17 phenotyping kit (BD PharmingenTM

Cat #560758), BDTM

Compensation beads (Cat #552844), BDTM

flow test tube (Cat #352008) were from BD

Biosciences, CA, USA. 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose

(2NBDG) was procured from Invitrogen, Life Technologies Corporation, NY, USA. Phorbol

12-Myristate 13-Acetate (PMA), Ionomycin, Dulbecco’s Modified Eagle’s Medium

(DMEM), RPMI Medium 1640 Lipopolysaccharide from E.coli 0111:B4 (LPS), Phosphatase

inhibitor cocktail, Protease inhibitor cocktail and Nonidet-P 40 (NP-40) were from Sigma-

Aldrich Co. LLC., St.Louis, MO, USA; Fetal Bovine Serum (FBS) was from Gibco®, Life

Technologies Corporation, NY, USA. All the consumables for western blotting were from

Bio-Rad Laboratories Inc., Hercules, CA, USA. The antibodies were from Cell Signalling

Technology Inc., Danvers, MA, USA (COX2(#4842S), HO1(#5061(HM)), pAMPK (#2535),


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GAPDH(#2118S), IgG-horseradish peroxidise (HRP) conjugate (#7074S)). Amplified Opti-

4CN™ Substrate kit was from Bio-Rad Laboratories Inc., Hercules, CA, USA) Tissue culture

accessories were from Tarsons Products Pvt. Ltd., Bangalore, KA, India.

5.2.2 Instruments/Softwares

FACS Calibur and Cell Quest software (BD BioSciences, San Jose, CA), FlowJo Treestar

software (TreeStar, San Carlos, CA, US) [at Central Imaging and Flow Cytometry Facility

(CIFF), NCBS-TIFR, GKVK Campus, Bangalore, Karnataka], Schrӧdinger Glide docking

software Version 5.5 (Schrödinger, LLC, New York, NY, 2009) [at NCBS-TIFR, GKVK

Campus, Bangalore, Karnataka]. CO2 incubator (NU-5510E, NuAire Inc., Plymouth, MN,

USA), Calibrated densitometer (GS 800, Bio-Rad Laboratories Inc., and Hercules, CA,

USA),

5.2.3 Experimental Animals

Female BALB/c mice 6-8 week old (20-25 g) were used for immunophenotyping.

Experimental animals were maintained as in Section 3.2.3.

5.2.4 TH1/TH2/TH17 phenotyping of splenocytes (Foster et al., 2001) (Kit protocol):

Briefly, freshly isolated naive female BALB/c mice splenocytes (3*106 cells) were treated

with test compounds in RPMI culture media for 2h, stimulated with phorbol ester (50ng/mL)

and ionomycin(1µg/mL) along with 4µL protein transport inhibitor (monensin) for 5h. The

assay was performed according to the manufacturer’s recommendations. The concentration of

test compounds (DHPO, DHFO, DMFO, DMPI) were decided based on the results of thus


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far. The cells were then fixed, permeabilized and subjected to immunofluorescent staining of

intracellular cytokines followed by flow-cytometric analysis on FACS Calibur .

Compensation was carried out using BDTM

Compensation beads as per the recommended

protocol. ~1,00,000 splenocytes per sample were acquired. Cell Quest software was used for

acquisition. From the FSC Vs SSC plot, lymphocytes were selected and gated on to CD4+ Vs

SSC plot. From the CD4+ Vs SSC plot, CD4+ T-lymphocytes were selected and gated on to

IFNγ-FITC-FLI Vs IL4-APC-FL4 plot and IL17-PE-FL2 Vs IL4-APC-FL4 plot. FlowJo was

used for data analysis. Quandrant statistics was used to calculate the % of IFNγ(TH1)+ ,

IL4(TH2)+, IL17(TH17)+ T helper cells. Data are represented after correcting with respect to

unstimulated untreated control (NC) and expressed as percentage with respect to

PMA/Ionomycin-stimulated untreated control (PC).

5.2.5 Cell culture and maintenance

RAW 264.7 murine macrophage cell line and L6 rat skeletal myotubes were maintained in

DMEM complete culture medium (90% DMEM and 10% FBS) at 37oC in a CO2 incubator.

5.2.6 Western blot for COX2, HO1

Briefly, 2*106

RAW cells were treated with test compounds (dose was selected based on

Section 2.2.8)/Curcumin (25μM) as standard and stimulated with LPS as in Section 2.2.8.

Cytoplasmic extracts were prepared using NP-40 buffer (150mM NaCl, 1% NP-40, 50mM

Tris (pH8.0), 1X phosphatase and 1X protease inhibitor cocktail). Protein was resolved in

10% SDS-polyacrylamide gel and transferred to polyvinylidene difluoride (PVDF)

membrane. The blot was blocked with 5% non-fat milk protein in Tris buffered saline (TBS)

followed by incubation with 1:1000 dilutions of primary antibodies against COX2/HO1 and


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GAPDH over-night at 4°C. This was followed by probing with 1:1000 dilution of secondary

antibody namely, IgG-horseradish peroxidise (HRP) conjugate. Amplified Opti-4CN™

Substrate kit was used to develop the blot which was then analysed using a calibrated

densitometer. Two independent experiments were performed.

5.2.7 AMPKα1 Molecular Docking studies

For the docking studies, the crystal structure of active mammalian AMPKα1β2γ1 (Protein

data bank Accession code PDB ID : 2Y94, source rat; replaced with 4CFH (Carling et al.,

2011) was used (Berman et al. 2000). The α1 subunit was selected because AMPKα1, is

predominantly expressed in immune cells, such as T cells and APC (Nath et al., 2009), and

threonine phosphorylation on this subunit is essential for AMPK activation. The structure

was prepared using Protein Preparation Wizard workflow in Schrödinger software, by

correcting bond order, adding hydrogen, assigning partial charges using OPLS-2005 force

field, assigning protonation states and geometry optimization of added hydrogens, followed

by minimization of structure with the Impact Refinement module (Impref; Impact version

5.5, Schrödinger, LLC, New York, NY). Ligand preparation was performed, using the 3D

structures of DHPO, DHFO, DMFO, DMPI, metformin, staurosporine and curcumin

(ACD/ChemSketch (freeware) Version12.01), to obtain all possible conformations. Docking

studies were performed using Schrӧdinger Glide software with induced-fit docking module.

The best poses were further refined using prime side-chain prediction and Glide redocking of

ligand was performed into the induced-fit receptor (Kalid et al. 2012). The pose with the best

Glide Score (XP GScore - least energy) is represented.


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5.2.8 Western blot for AMPKα phosphorylation

Briefly, 2*106

L6 myotubes were treated with test compounds (100µM) and cytoplasmic

extracts were prepared. The rest of the procedure was the same as in Section 5.2.6. The blot

was incubated with 1:1000 dilutions of pAMPK and GAPDH over-night at 4°C and the blots

were analysed using a calibrated densitometer. Two independent experiments were

performed.

5.2.9 2-NBDG Glucose uptake assay in L6 myotubes by flow cytometry (Le et al., 2010)

Briefly, 0.5*106 L6 myotubes were seeded in 60mm petridishes and treated overnight with

test compound (100 μM). Unstained and Negative controls received media alone. As

standard, Insulin was used at a 100nM for 15min. The cell culture supernatents were decanted

and the petridishes were rinsed twice with cold PBS, followed by incubation with 100 μM 2-

NBDG (λex=475nm, λem=550nm) for 30 minutes. The plates were washed twice with cold

PBS and the cells were recovered by scraping on ice and transferred to flow tubes followed

by flow-cytometric analysis of 10000 live cells on FACS Calibur. Isotonic PI was used to

differentiate between live and dead cells by appropriate gating on a FL1(2-NBDG)-FL2(PI)

plot. Cell Quest software was used for acquisition and FlowJo was used for data analysis.

Data is represented as a histogram.


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5.3 Results

5.3.1 TH cell modulation studies

Figure 5.1: Effect of different doses of DHPO on TH cell polarization into TH1

Figure 5.2: Effect of different doses of DHPO on TH cell polarization into TH2, TH17


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Figure 5.3: Effect of different doses of DHFO on TH cell polarization into TH1

Figure 5.4: Effect of different doses of DHFO on TH cell polarization into TH2, TH17


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Figure 5.5: Effect of different doses of DMFO on TH cell polarization into TH1 cells

Figure 5.6: Effect of different doses of DMFO on TH cell polarization into TH2, TH17


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Figure 5.7: Effect of different doses of DMPI on TH cell polarization into TH1

Figure 5.8: Effect of different doses of DMPI on TH cell polarization into TH2, TH17


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Table 5.1: Effect of test compounds on TH cell polarization

Groups TH1+ TH17

+ TH2

+ % with respect to PC

NC (Media Control) 0.505 0.573 0.524 TH1+ TH17

+ TH2

+

PC (Positive Control) 8.06 2.26 1.11 100 100 100

DHPO-100µM 1.34 1.21 0.909 11.05 37.76 65.70

DHPO-50µM 5.97 1.64 0.705 72.34 63.25 30.89

DHPO-10µM 6.81 1.75 0.834 83.45 69.77 52.90

DHFO-100µM 6.21 2.03 1.27 75.51 86.37 127.30

DHFO-50µM 6.9 1.91 1.18 84.65 79.25 111.95

DHFO-10µM 6.62 1.66 0.957 80.94 64.43 73.89

DMFO-100µM 7.13 1.62 1.17 87.69 62.06 110.24

DMFO-50µM 5.87 1.28 1.12 71.01 41.91 101.71

DMFO-10µM 6.53 1.64 0.983 79.75 63.25 78.33

DMPI-100µM 7.81 1.92 3.31 96.69 79.85 475.43

DMPI-50µM 5.39 1.17 2.35 64.66 35.39 311.60

DMPI-10µM 6.06 1.24 1.37 73.53 39.54 144.37

3*106 splenocytes treated with test compounds for 2 h, followed by stimulation with phorbol

ester (50ng/mL) and ionomycin(1ug/mL) and protein transport inhibitor (monensin) for 5 h.

The cells were then fixed, permeabilized and subjected to immunofluorescent staining of

intracellular cytokines followed by flow-cytometric analysis on FACS Calibur according to

kit protocol. ~1,00,000 splenocytes per sample were acquired.. Quadrant statistics was used

to calculate the % of IFNγ(TH1)+ , IL4(TH2)

+, IL17(TH17)

+ T helper cells. Data are corrected

with respect to unstimulated untreated control (NC) and expressed as percentage of

PMA/Ionomycin-stimulated untreated control (PC).


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Figure 5.9: Effect of different doses of test compounds on TH cell polarization

DHPO

M

100M

50M

10M

100M

50M

10M

100M

50M

10

0

20

40

60

80

100TH1

TH17

TH2

% o

f T

H c

ell

wit

h r

esp

ect

to p

osi

tive

co

ntr

ol

DHFO

M

100

M

50M

10M

100

M

50M

10M

100

M

50M

10

0

50

100

150

% o

f T

H c

ell

wit

h r

esp

ect

to p

osi

tive

co

ntr

ol

DMFO

M

100M

50M

10M

100M

50M

10M

100M

50M

10

0

50

100

150

% o

f T

H c

ell

wit

h r

esp

ect

to p

osi

tive

co

ntr

ol

DMPI

M

100

M

50M

10M

100

M

50M

10M

100

M

50M

10

0

100

200

300

400

500

% o

f T

H c

ell

wit

h r

esp

ect

to p

osi

tive

co

ntr

ol


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5.3.2 Protein expression studies

5.3.2.1 COX2 expression studies

0.0

0.5

1.0

1.5

2.0

2.5

Media Control

LPS Control

Curcumin (25M)

DMFO (50M)

DMPI (500M)

DHFO (150M)

DHPO (75M)

*

Re

lative

De

nsity (

CO

X2

:GA

PD

H)

#

#

* #

* #

* #

* #

* #

*

Figure 5.10: Effect of test compounds on COX2 expression

2*106

RAW cells were treated with test compounds/curcumin (standard), stimulated

with LPS, cytoplasmic extracts were prepared using NP-40 buffer and was resolved in

10% SDS-polyacrylamide gel, transferred to PVDF membrane, probed with primary

antibodies - COX2 and GAPDH. Results are mean ± SEM of two independent

experiments [*: p<0.05 compared to LPS control; #: p<0.05 compared to curcumin].


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5.3.2.2 HO-1 expression studies

0.0

0.5

1.0

1.5

Media Control

LPS Control

Curcumin (25M)

DMFO (50M)

DMPI (500M)

DHFO (150M)

DHPO (75M)*

**

Re

lative

De

nsity (

HO

1:G

AP

DH

)

##

#

# #

#

Figure 5.11: Effect of test compounds on HO1 expression

2*106

RAW cells were treated with test compounds/curcumin (standard), stimulated

with LPS, cytoplasmic extracts were prepared using NP-40 buffer and was resolved in

10% SDS-polyacrylamide gel, transferred to PVDF membrane, probed with primary

antibodies – HO1 and GAPDH. Results are mean ± SEM of two independent

experiments [*: p<0.05 compared to LPS control; #: p<0.05 compared to curcumin].


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5.3.3 AMPKα1 Molecular Docking studies

(a) (b)

(c) (d)

Figure 5.12(a) Molecular docking of the following compounds to AMPKα : a)

DHPO, b) DHFO, c) DMFO, d) DMPI.

Crystal structure of active mammalian AMPKα1β2γ1 (PDB ID : 2Y94) prepared

using Protein Preparation Wizard workflow in Schrödinger software. Ligands-

DHPO, DHFO, DMFO, DMPI, metformin and curcumin were drawn in 3D using

ACD/ChemSketch (freeware) Version12.01 and ligand preparation performed.

Induced fit docking studies performed using Schrӧdinger Glide software, best pose

with lowest Glide Score (XP GScore) represented.


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(e) (f)

(g)

Figure 5.12(b) Molecular docking of the following compounds to AMPKα : e)

Metformin, f) Curcumin, and g) Staurosporine.

Crystal structure of active mammalian AMPKα1β2γ1 (PDB ID : 2Y94) prepared

using Protein Preparation Wizard workflow in Schrödinger software. Ligands-

DHPO, DHFO, DMFO, DMPI, metformin and curcumin were drawn in 3D using

ACD/ChemSketch (freeware) Version12.01 and ligand preparation performed.

Induced fit docking studies performed using Schrӧdinger Glide software, best pose

with lowest Glide Score (XP GScore) represented.


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Table 5.2 Molecular docking study of the test compounds to AMPKα – XP Gscore

and amino acid interactions

Sl.No. Molecules

XP Gscore

(kcal/mol)

Amino acid interactions at AMPKα1

1 DHPO -6.938 Val96 (H-bond), Glu100 (salt bridge)

2 DHFO -10.163 Val24, Glu143 (H-bonds)

3 DMFO -10.058 Val96, Val24, Glu143, Gly25 (H-bonds)

4 DMPI -11.152 Asp157, Val24, Glu143, Gly25 (H-bonds)

5 Metformin -3.221 Glu100 (2 H-bonds), Asp103 (H-bonds),

Gly98 (H-bond), Val96, Lys107, Gly99,

Leu22, Ser97, Tyr95

6 Curcumin -11.478 Val96, Glu100, Asp157, Lys45 (H-bonds)

7 Staurosporine -10.566 Val96, Glu100, Glu94 (H-bonds)

Schrӧdinger Glide Molecular Docking software was used to evaluate possible

interaction between AMPKα1(Genetic Source: Rat) and chosen ligands. Induced fit

docking studies are performed using induced-fit docking module.

5.3.4 AMPKα phosphorylation

0.0

0.1

0.2

0.3

0.4

0.5

Media Control

DHPO(100M)

DHFO(100M)

DMFO(10M)

DMPI(100M)

*

*

*

*

*

Ph

osp

ho

-AM

PK

(T

hr1

72

) :

GA

PD

H

Figure 5.13: Effect of test compounds on AMPKα phosphorylation

2*106

L6 cells were treated with test compounds/curcumin (standard) overnight.

Cytoplasmic extracts were prepared using NP-40 buffer and 50μg of protein was

resolved in 10% SDS-polyacrylamide gel, transferred to PVDF membrane, blot was

incubated with primary antibodies – pAMPK and GAPDH. Results are mean ± SEM

of two independent experiments [*: p<0.05 compared to media control].


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5.3.5 2-NBDG uptake assay in L6 myotubes

Figure 5.14 Effect of test compounds on 2NBDG uptake in L6 myotubes

0.5*106 L6 myotubes treated overnight with test compound (100μM). Cells rinsed

twice with cold PBS, followed by incubation with 100μM 2-NBDG (λex:475nm,

λem:550nm) for 30 min, and cells recovered by scraping on ice followed by flow-

cytometric analysis of 10000 live cells on FACS Calibur. Isotonic PI used to

differentiate between live and dead cells.


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(Insulin[8.1%]<DMFO=DHPO[20.5%]< DHFO[22.2%]<DMPI[51.1%])

Figure 5.15 Effect of test compounds on 2NBDG uptake in L6 myotubes (contd)

0.5*106 L6 myotubes treated overnight with test compound (100μM). Cells rinsed

twice with cold PBS, followed by incubation with 100μM 2-NBDG (λex:475nm,

λem:550nm) for 30 min, and cells recovered by scraping on ice followed by flow-

cytometric analysis of 10000 live cells on FACS Calibur. Isotonic PI used to

differentiate between live and dead cells.


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5.4 Discussion

5.4.1 TH cell modulation

Dysregulated and persistent T effector cell responses underlie chronic inflammatory

conditions (Weaver et al., 2006). PMA/Ionomycin synergestically activate TH cells in

the ex-vivo system (Chatila et al., 1989). PMA, a structural analog of diacylglycerol,

activates PKC, thereby releasing calcium that triggers a signalling cascade involving

production and secretion of IL2, important in growth and differentiation of TH cells.

The order of TH polarization by test compounds (100µM) is summed up below:

TH2 (promote differentiation) : DMPI>>DHFO>DMFO

TH1 (suppress differentiation) : DHPO>DHFO>DMFO>DMPI

TH17 (suppress differentiation): DHPO>DMFO>DMPI>DHFO

The above pattern of TH polarization demonstrates anti-inflammatory potential of all

test compounds. DHPO seems to be slightly different because it was the only

compound that inhibited TH2 polarization. However, this was more than compensated

by the suppression of TH1 and TH17 differentiation. DHPO (100µM) reduced TH1

polarization by as much as 90%. AICAR is reported to suppress TH1 and TH17 (Bai et

al., 2010a). The TH2 polarisation was consistent with AMPK activation potential for

all compounds except DHPO (see Figure 5.13).

The most remarkable observation was that though DMPI induced approximately

500% increase in TH2 polarization, it did not increase IgE levels in-vivo (Figure 4.5),

indicating its potential therapeutic value in inflammatory conditions. A combination

of DMPI and DHPO might form a two-pronged strategy to treat chronic inflammation

because it simultaneously operates on pro-inflammatory TH1 and TH17 on the one

hand and anti-inflammatory TH2 on the other.


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It is indeed possible that lower doses may be equipotent, but this requires further

experiments. We have already seen that DHFO at a low dose of 10µM was more

effective in inhibiting TH17 polarization. DMFO and DMPI were more effective at

50µM in reducing TH1 and TH17 polarisation. Additionally, we observed that DHFO

(150µM), produced 40% inhibition of IL6 (Mathew et al., 2013), a cytokine essential

for TH17 polarization (Zhu and Paul, 2008, Afzali et al., 2007). All four test

compounds significantly reduced IL6 levels in vivo (Figure 4.3). The above results

substantiated the suppression of TH17 differentiation by test compounds.

The therapeutic potential of targeting TH cells for chronic inflammation is exemplified

by the recent success of IL4 as an immunocytokine in an animal model of arthritis

(Hemmerle et al., 2014). The therapeutic potential of the antibody–IL4 fusion

protein, probably via promotion of TH2 differentiation (and the consequent

suppression of TH1 and TH17 differentiation), elicits a response similar to our test

compounds, particularly DMFO. On a similar note, DMFO, like the antibody–IL4

fusion protein, failed to increase in-vivo IgE levels significantly (Chapter 4).

In view of the above results, the test compounds may be anti-inflammatory by

suppressing TH1/TH17 and/or enhancing TH2 differentiation. TH17 and Treg being

cross-regulatory (Lee et al., 2009), suppression of TH17 polarisation also suggests

possible promotion of Treg differentiation which requires further investigation.

5.4.2 COX2 and HO1 expression

In addition to stimulating cytokines in TH cells (Tomita et al., 2002), NFκB also

induces the transcription of additional inflammatory mediators such as chemokines,

iNOS, PGs, etc (Tomita et al., 2002). NFκB activation also upregulates COX2 in

inflammatory sites (Zamamiri-Davis et al., 2002). All four test compounds inhibited

COX2 expression in macrophages significantly. Curcumin (standard) reduced COX2


131 | P a g e

expression down to 45%, while DMFO and DHFO were better than curcumin (32%

and 7% respectively). DMFO, which proved superior to other three compounds in-

vivo, inhibited COX2 in moderation as seen in TH modulation also, further lending

credibility to the value of temperance. On the other hand, DHFO with relatively sub-

optimal in-vivo activity almost completely abolished LPS-induced COX2 expression

in macrophages. DMPI and DHPO reduced COX2 expression to 75% and 70% (of

control) respectively. Previous experiments, separately conducted on DHFO, have

confirmed 65% reduction of nuclear NFκB levels (Mathew et al., 2013). While it has

been previously demonstrated that DHFO has no inhibitory effect on COX isozymes

per se (Prabhakar et al., 2006), we have shown that expression of COX2 was indeed

suppressed (Mathew et al., 2013). In addition to a reduction in COX2 expression,

DHPO also inhibited COX2 and COX1 enzymes with IC50 of 78 and 186 μM

respectively (Unpublished results).

Recent literature supports the gastroprotective ability of HO1(Costa et al., 2013,

Gomes et al., 2010, Lee et al., 2012, Bindu et al., 2011). HO1 degrades free heme into

its metabolites namely CO and biliverdin/bilirubin, which are cytoprotective (Wang et

al., 2011) and anti-inflammatory (Itoh et al., 2004). While curcumin, DHPO and

DMFO increased HO1 expression significantly by 16, 6 and 5 –fold respectively,

DMPI and DHFO completely failed to induce HO1 expression.

HO1 inhibits TNFα expression (Itoh et al., 2004). This is consistent with our finding

that DMFO, the most potent HO1 activator among compounds tested, reduced TNFα

to undetectable levels in-vivo (Section 4.3.3). Although there were large variations

between samples, the order of efficacy in TNFα inhibition fairly matched the order of

HO1 expression.


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Although we did not find direct HO1 stimulation by DMPI at the single tested dose,

there is a hint that DMPI influences events downstream HO1 expression. DMPI

moderately reduced NO and TNFα levels in-vivo, which is consistent with HO1

stimulation. Being non-ulcerogenic, in vivo, coupled with TH cell modulatory effect

at low doses (50 and 10µM), it is worth exploring the role of DMPI in Nrf2

activation/HO1 expression at lower doses, particularly in the gastric epithelium.

H. pylori infection (believed to infect 50% of world population) and the use of

NSAIDs, are the two most common causes of gastric ulcer (Arroyo et al., 2004)

(Bergman et al., 2004). H. pylori eradication reduces NSAID-induced peptic ulcers

(Chan et al., 1997). Owing to the fact that H.pylori induces pro-inflammatory TH1/

TH17 (Shi et al., 2010) and inhibits nuclear translocation of Nrf2 (Buommino et al.,

2012), coupled with the fact that test compounds modulate TH cell toward anti-

inflammatory phenotype, together suggest an additional advantage for test compounds

in comparison to NSAIDs.

The non-ulcerogenic nature of test compounds could be similar to that of the proton

PPIs such as pantoprazole (Hahm et al., 2012), which have also been shown to

upregulate HO1. Our compounds also seem to share some common features with

PPIs, that irreversibly block H+/K

+ ATPase (gastric proton pump) of the

gastric parietal cells, the final stage in gastric acid production. PPIs are prescribed for

GERD, PUD, H. pylori eradication and mucosal protection when given with NSAIDs.

Additionally PPIs are pleiotropic showing anti-inflammatory, anti-apototic, anti-

oxidant activities, etc (Schulz-Geske et al., 2009).

Nrf2 and NFκB reciprocally cross-regulate each other (Piao et al., 2011) (Li et al.,

2008). Therefore, inhibiting proinflammatory mediators via NFκB, coupled with

upregulating antioxidant enzyme expression via Nrf2, constitute a rational two-

http://en.wikipedia.org/wiki/Hydrogen_potassium_ATPase

http://en.wikipedia.org/wiki/Parietal_cells


133 | P a g e

pronged strategy to tackle inflammation. For instance, the most effective compound

tested, namely, DMFO exhibited this dual mechanism, similar to many natural

products such as curcumin, melatonin, resveratrol, sulforaphane, etc (Ganesh Yerra et

al., 2013).

5.4.3 AMPK activation

Docking studies confirmed the binding of test compounds to AMPKα. In the induced

fit docking studies, binding of DMPI exhibited least overall energy, comparable to

curcumin followed by DHFO and DMFO which had similar energy scores, binding of

DHPO had the highest energy. DMPI, DHFO and DMFO showed better binding score

than the established AMPK activator, namely, DHPO. All four test compounds had

lower XP Gscore than metformin. AMPKα phosphorylation, evaluated by western

blot, demonstrated a similar order of efficacy.

Docking studies revealed that valine 96 was a common residue involved in the

binding for all compounds (including metformin and curcumin) except for DHFO and

DMPI. Hydrogen bond was the common mode of binding, while DHPO also formed

an additional salt bridge. Val24, Glu143 residues were involved in the binding of

DHFO, DMFO and DMPI, while Glu100 was common to DHPO, metformin and

curcumin. Binding of test compounds to the catalytic unit of AMPK could have

played a role in either inducing phosphorylation of the kinase domain or protecting it

from dephosphorylation (Chandrashekarappa et al., 2013).

Literature reports that AMPK activation can inhibit NFκB translocation and induce

Nrf2 activation (Salminen and Kaarniranta, 2012). Accordingly we demonstrated that

DHPO, DHFO, DMFO and DMPI (at 100µM) increased phosphorylation of Thr172


134 | P a g e

of the α-subunit by 2, 4, 5 and 7 fold respectively. AMPKα phosphorylation

demonstrated a similar order of efficacy as predicted by docking studies. AMPK

activation plays a vital role in TH cell polarization, probably through mTOR (O’Neill

and Hardie, 2013, Chi, 2012). AMPK activation can also inhibit TH1 & TH17 cell

differentiation (Bai et al., 2010a). AMPKα1, being predominantly expressed in

immune cells, such as T cells and APC, involved in several autoimmune conditions

(Nath et al., 2009), coupled with the evidence for a recent surge in autoimmune

disorders (Okada et al., 2010), together suggest that the overnourished modern man

suffers from a heightened immune response, owing to the chronic underactivation of

AMPK (Mor and Unnikrishnan, 2011).

Several natural products such as resveratrol (Yi et al., 2011), quercetin, curcumin,

berberine (Mo et al., 2014), etc (Hardie, 2013) are AMPK activators with anti-

inflammatory activity. Natural products are known to be pleiotropic, exerting a

holistic action, which may explain fewer adverse effects in comparison to synthetic

drugs (Unnikrishnan et al., 2014). The test compounds also showed a pleiotropic

mechanism of action across several targets, which is rarely addressed by synthetic

compounds. AMPK is an upstream nodal point that orchestrates the regulation of

complex multiple metabolic pathways that sustain the delicate homeostasis on the

face of unremitting environmental flux. The oldest and most commonly prescribed

anti-diabetic drug, metformin, is also an AMPK activator derived from a plant product

(Unnikrishnan et al., 2014). Interestingly, metformin is also anti-inflammatory

(Salminen and Kaarniranta, 2012).


135 | P a g e

AMPK activation by test compounds was further confirmed by demonstrating

enhanced glucose uptake in L6 myotubes. 2NBDG uptake into skeletal muscle is

mediated via GLUT4 expression and translocation, which is enhanced by the AMPK

activator, for instance, AICAR. Thus, glucose uptake is a reflection of AMPK

activation (Park et al., 2009, Zou et al., 2005, Ojuka et al., 2002). The NBDG uptake

by all test compounds was fairly consistent with the docking score. Further, the

highest glucose uptake by DMPI is in agreement with its lowest XP Gscore. Glucose

uptake enhancement in skeletal muscle (DMFO=DHPO[20.5%]<

DHFO[22.2%]<DMPI[51.1%]), matched the NO levels in LPS-stimulated

macrophages treated with test compounds (DMFO<DHPO<DHFO<DMPI). Since

AMPK-induced GLUT4 expression operates via NO (Lira et al., 2007), the above

results is consistent with the AMPK activating potential of test compounds. However,

this correlation was not in harmony with in-vivo NO levels in the inflammatory air

pouch, probably suggesting a different order of AMPK activation in-vivo. (Being a

patent-filed molecule, we also conducted a preliminary pharmacokinetic evaluation of

DMPI, as a candidate prototype. (Appendix I))

Though most effective in both cell-based and in-vivo models of inflammation, DMFO

was uniformly moderate in mechanistic studies, further demonstrating the value of

moderation in modulating inflammatory pathways. Quite by contrast, the remaining

compounds (DMPI, DHPO, DHFO), which seemed more effective and potent

individually in different mechanistic studies, were not as effective in cell-based and

in-vivo models. A portion of DMFO being identical to one half of curcumin molecule

(dehydrozingerone), it is probably not surprising that it shares the pleiotropism seen in

curcumin.


136 | P a g e

Thus the test compounds may possess a TH cell modulatory activity mediated via

AMPK and NFκB. Further, Nrf2 activation appears to be the key principle in the non-

ulcerogenicity of DMFO and DHPO. Thus, the test compounds may indeed be a novel

“first-in-class” category of non-ulcerogenic anti-inflammatory agents targeting

immune, redox and metabolic processes associated with a very complex inflammatory

pathology.

5.5 Conclusions

The major findings from this chapter are as follows:

The anti-inflammatory action of test compounds, at the cellular level, may be

attributed to inhibiting TH1/TH17 and/or enhancing TH2 differentiation.

DHFO, DMFO and DMPI dose-dependently increased anti-inflammatory TH2

polarization. DHPO, an established AMPK activator, dose-dependently

decreased pro-inflammatory TH1 and TH17 polarization.

DHFO was a potent inhibitor of COX2 expression, while DMFO showed

moderate inhibition. COX2 expression being regulated by NFκB, test

compounds possibly targeted NFκB.

Only DHPO and DMFO enhanced HO1 expression, indicating Nrf2

activation. As NFκB and Nrf2 are reciprocally-regulated targets for anti-

inflammatory activity, the COX2 and HO1 expression studies suggest a

mechanism that targets both NFκB and Nrf2.

All the four test compounds activated AMPKα. DMPI binding exhibited least

overall energy (XP Gscore) which was comparable to curcumin, followed by

DHFO and DMFO which showed similar energy scores. This was consistent


137 | P a g e

with AMPK phosphorylation and cellular uptake of NBDG by test

compounds.

Non-ulcerogenic anti-inflammatory activity of DMFO consistently

demonstrated in all cell-based and in-vivo models of inflammation probably

validates the hypothesis that TH cell modulatory agents that activate AMPK,

thereby stimulating Nrf2 and inhibiting NFkB, may work as non-ulcerogenic

anti-inflammatory agents.

By modulating multiple molecular mechanisms of inflammation

simultaneously in moderation, the success of DMFO further substantiates our

earlier argument that addressing multiple targets of inflammation more

holistically, in moderation, is probably a more viable strategy

The test compounds may indeed be a novel “first-in-class” category of non-

ulcerogenic anti-inflammatory agents targeting immune, redox and metabolic

processes associated with the very complex inflammatory pathology.

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