Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist: pharmacophore-based screening and structure-based optimization

Article abstract of DOI:10.1007/s00706-019-02442-2

Abstract: This study describes screening of muscarinic acetylcholine receptors (mAChR) antagonist by pharmacophore modeling and optimization by molecular docking. A series of molecules was synthesized and evaluated for preliminary pharmacological activity

Full text of DOI:10.1007/s00706-019-02442-2

Monatshefte für Chemie - Chemical Monthly
https://doi.org/10.1007/s00706-019-02442-2
ORIGINAL PAPER
Design and synthesis of muscarinic acetylcholine receptor (mAChR)
antagonist: pharmacophore‑based screening and structure‑based
optimization
1
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RamaRao Ghorpade · Deo Kumar · Sabita Nayak · Badri Narayan Acharya
Received: 1 February 2019 / Accepted: 6 May 2019
©
Springer-Verlag GmbH Austria, part of Springer Nature 2019
Abstract
This study describes screening of muscarinic acetylcholine receptors (mAChR) antagonist by pharmacophore modeling and
optimization by molecular docking. A series of molecules was synthesized and evaluated for preliminary pharmacological
activity on rat ileum. A molecule based on benzonitrile piperazine scaꢀold showed good tissue relaxation and blocking of
neurotransmitter ACh in the ex vivo experiment.
Graphical abstract
Keywords Pharmacophore · mAChR · Docking · Antagonist · Antidote · Benzonitrile piperazine
Introduction
the body, including brain [1, 2], eye [3], heart [4], vascu-
lature [5], lung [6], and bladder [7]. Acetylcholine acts on
muscarinic and nicotinic (nAChR) type receptors in central
and peripheral nervous systems and has two types of eꢀects
[8]. The ꢁrst type is termed as muscarinic, which is the para-
sympathetic eꢀect on the secretary exocrine glands, and on
smooth and cardiac muscles through their corresponding
receptors. The other type of eꢀect is termed as nicotinic,
which is on the skeletal muscles [9, 10]. Both mAChR and
nAChR are receptors of ACh, but they are structurally dif-
ferent from each other. Preferentially they bind two diꢀerent
alkaloids muscarine and nicotine respectively. Muscarinic
acetylcholine receptors play important role in various dis-
eases like chronic obstructive pulmonary disease (COPD),
asthma, irritable bowel syndrome (IBS), overactive bladder
(OAB), and nerve agent (NA) poisoning.
Muscarinic acetylcholine receptors (mAChR) are G-protein
coupled receptors (GPCRs) having seven transmembrane
helical domains connected by three extracellular and three
intracellular loops. These receptors act as the main end-
receptor stimulated by neurotransmitter acetylcholine (ACh)
released from postganglionic ꢁbers in the parasympathetic
nervous system. They are expressed normally throughout
Electronic supplementary material The online version of this
article (https://doi.org/10.1007/s00706-019-02442-2) contains
supplementary material, which is available to authorized users.
*
Badri Narayan Acharya
bnacharya@yahoo.com
Nerve agents are organophosphate (OP) esters chemi-
cally similar to organophosphate pesticides with higher
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Defence R&D Establishment, Jhansi Road, Gwalior, India
Revenshaw University, Cuttack, Odisha, India
Vol.:(0
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R. Ghorpade et al.
acute toxicity. They are colorless, odorless, tasteless,
and nonirritating to the skin. Hence exposure to a lethal
dose can occur without being perceived by the individual.
These agents show toxicity by inhibiting acetylcholinest-
erase (AChE), the enzyme which is required to break
down ACh and prevents its excess accumulation at nerve
endings. The symptoms resulting from NAs are primarily
the consequence of accumulation of excess ACh within
the nervous system controlling smooth muscle, cardiac
muscle and endocrine-exocrine functions leading to drool-
ing, increased bronchial secretions, bronchoconstriction,
miosis, excessive sweating, diarrhea, abdominal cramping,
vomiting, urination, and cardiac arrhythmia. The immedi-
ate death can occur due to respiratory failure of the vic-
tim [11]. The current treatment of nerve agent poisoning
includes administration of a mAChR antagonist (atropine)
followed by an oxime (2-PAM, obidoxime, HI6 etc.) to
reactivate the OP inhibited AChE and an anticonvulsant
drug (benzodiazepine) [11]. Atropine antagonizes mus-
carinic eꢀects of ACh by nonselectively blocking all sub-
types of mAChR. The usefulness of atropine is limited due
to its side eꢀects and toxicity [12]. Hence there is a need
for new eꢀective anticholinergic agents for the prophylaxis
and treatment against nerve agent poisoning.
Results and discussion
Pharmacophore models
Common feature pharmacophore modeling [15] requires
structure of active molecules to identify and enumerate
all possible pharmacophore conꢁgurations which are in
common within the training set molecules. With the aim
of deꢁning the pharmacophoric features needed to iden-
tify mAChR antagonists, two pharmacophore hypotheses
were generated using Catalyst HipHop algorithm, starting
from the set of known mAChR antagonists (Fig. 1a, b).
HipHop performs an exhaustive search starting with the
simplest two feature conꢁguration followed by more com-
plex conꢁgurations. The process continues until HipHop
no longer generates any new more complex pharmacoph-
ore conꢁgurations.
Atropine was chosen in both training sets, because it is
used as an antidote in treatment for nerve agent poison-
ing [12]. As it is a proven mAChR antagonist, it contains
all essential pharmacophores which can be elucidated by
pharmacophore modeling. Compounds structurally similar
to atropine like scopolamine, ipratropium, cyclopentolate,
solifenacin, and tropicamide were also chosen for training
set to generate model 1 (Fig. 1c). Model 1 consists of a
hydrogen bond donor (HBD), a hydrogen bond acceptor
(HBA), a positive ionizable (PI), and a hydrophobe (HY).
The distances between HBD-PI, HBD-HBA, HBD-HY,
HY-PI, HY-HBA, and HBA-PI are 7.896, 6.726, 4.103,
8.562, 6.487, and 3.103 Å, respectively. Another common
feature pharmacophore model (model 2) was generated
by taking a structurally diversiꢁed training set consisting
atropine, ꢃavoxate, pirenzapine, himbacine, 4-DAMP, and
pd102807. Model 2 contains three pharmacophoric fea-
tures HBA, HY, PI and ten excluded volumes (Fig. 1d).
Most of the excluded volumes are present near HBA and
PI features. Distances between HBA-HY, HBA-PI, and
HY-PI are 4.066, 8.551, and 8.734 Å, respectively. These
values are signiꢁcantly diꢀerent from respective values of
Model 1. HBA, HY, and PI features are common in model
1 and model 2. Hence it may be hypothesized that these
three features are most essential for a molecule to show
mAChR antagonist activity.
Structure-based drug designing (SBDD) is an eꢀec-
tive tool for discovery of potential bioactive molecules.
Based on the receptor structures, eꢀective inhibitors can
be designed. With improvement in crystallization pro-
tocols and crystallographic procedures, there have been
rapid growths in crystallographic structural information
of mAChRs [13]. Muscarinic AChRs are subdivided in
to ꢁve subtypes, M -M . Except M , three-dimensional
1
5
5
(
3D) structures of all other subtypes have been eluci-
dated. These structures show ligand-induced activation
and inhibition processes, receptor subtype selectivity and
binding pattern of ligands with the receptor. These crystal
structures can be used in structure-based design of new
inhibitors for mAChRs. Earlier we have demonstrated a
pharmacophore-based method to design dihydropyrimidi-
none (DHPM) based molecules showing mAChR antago-
nist activity [14]. The molecules were designed based on
three template molecules screened from NCI2000 database
by pharmacophore modeling. In continuation of our search
for potential mAChR antagonists, we used a combination
of pharmacophore modeling and structure-based recep-
tor–ligand docking to design a mAChR antagonist based
on a template molecule screened from Maybridge2004
database. The hit molecule was further optimized to
enhance the aꢂnity by receptor–ligand docking. The opti-
mized compound was synthesized, evaluated ex vivo on rat
ileum and found active by showing good tissue relaxation
and blocking of ACh binding with the receptor.
Docking studies
Receptor–ligand docking is a powerful tool to simulate
putative interactions between the two molecules. A vali-
dated docking protocol is useful to screen new inhibitors
and optimization of lead molecules. Aꢂnities and bind-
ing modes predicted by docking simulation provide key
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Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
Fig. 1 Structures of training set molecules (a, b) and pharmacoph-
ore model 1 (c), and model 2 (d). Model 1. Magenta: hydrogen bond
donor (HBD); blue: hydrophobe (HY); green: hydrogen bond accep-
tor (HBA); red: positive ionizable (PI); pharmacophore Model 2.
Red: positive ionizable (PI); blue: hydrophobe (HY); green: hydrogen
bond donor (HBD); grey: excluded volume (EV) (color ꢁgure online)
information for prioritizing compounds to be synthesized
and analyzed for structure activity relationship (SAR) and
binding site, calculation of interaction energy of the pre-
dicted binding conformation, and ranking of the ligand
conformation by a scoring function. AutoDock generates
molecular conformations in a wide range of energy land-
scape and searches conformational space by randomly modi-
fying the structural parameters of the ligands by Lamarckian
Genetic Algorithm (LGA). Scoring is done by force-ꢁeld
based method, considering sum of contributions of bonded
(stretching, bending and dihedral change) and non-bonded
(electrostatic and Van der Waals) interactions.
rational drug design. Crystal structures of mAChRs (M
3
and M ) elucidated by X-ray crystallography bound with
2
inhibitors tiotropium (TIO) (Fig. 2a) and 3-quinuclidinyl-
benzilate (QBZ) (Fig. 2e), respectively, have been reported
in literature [16, 17].
These crystal structures reveal important binding pattern
of the inhibitors in the orthosteric binding pocket of the
receptors. Similar interactions can be simulated by recep-
tor–ligand docking by standardizing simulation parameters
like binding site volume, locus of grid center, and selection
of ꢃexible residues.
First the docking protocol was examined by comparing
with the co-crystalized structure of M receptor with TIO
3
(pdb id: 4daj) [16] (Fig. 2b) and docked structure of the
In this study, receptor–ligand docking was carried out
by AutoDock 4.1 [18] and the parameters of docking pro-
tocol are described in material section. Docking calcula-
tions broadly comprise conformational sampling of ligand
molecule considering various binding modes in the receptor
receptor with TIO generated by AutoDock (Fig. 2c). The
TIO-M complex generated by AutoDock was superimposed
3
with crystal structure 4daj (Fig. 2d). Two strong hydrogen
bonds are reported in the crystal structure, between two oxy-
gen atoms of TIO and ASN 507 residue of M3 receptor.
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R. Ghorpade et al.
Fig. 2 Structure of tiotropium (a); X-ray structure of tiotropium with
M3 receptor (pdb id: 4daj) (b); tiotropium docked with A chain of
M3 receptor (4daj) by AutoDock 4.1 (c); Overlaying of crystal struc-
ture and receptor–ligand docking structure of tiotropium-M3 complex
(d); Structure of QBZ (e); X-ray crystal structure of QBZ with M2
receptor (pdb id: 3uon) (f); Overlaying of crystal structure and dock-
ing structure of QBZ and M2 receptor (g)
Similar hydrogen bonds were also predicted by AutoDock in
the receptor–ligand docking. The orientation of TIO in the
orthosteric binding pocket of M3 was predicted with similar
conformation compared with the crystal structure (Fig. 2d).
Two strong hydrogen bonds are reported in the crystal
structure, between two oxygen atoms of QBZ and ASN
The calculated rmsd values were 8.2 Å and 6.3 Å for QBZ
and TIO, respectively.
Within mAChR family, M3 subtype regulates glandu-
lar secretions and smooth muscle contractions. Experi-
mental inhibition constant (pK ) values of several mAChR
i
antagonists are reported for M3 receptor [19]. Hence, we
4
04 residue of M2 receptor (Fig. 2f) [17]. Similar hydro-
chose the structure of M3 (4daj) for validation of recep-
gen bonds were also predicted by AutoDock in the recep-
tor–ligand docking. The QBZ-M2 complex generated by
AutoDock was also superimposed on crystal structure
tor–ligand docking as a tool to estimate pK values of the
i
reported inhibitors. Twenty three known antimuscarinic
drug molecules were docked individually with M3 recep-
3
uon (Fig. 2g). The orientation of QBZ in the orthosteric
tor and respective pK values were calculated (Table S1,
i
binding pocket of M2 was predicted with similar con-
formation compared with the crystal structure (Fig. 2g).
The receptor–ligand complexes of TIO-M3 and QBZ-M2
were matched with pdb structures 4daj and 3uon, respec-
tively, to check the all atom root mean squire deviation
Supplementary Information). For several molecules, a
good agreement was observed between estimated and
reported pK values. This indicated that the docking pro-
i
tocol is suitable to generate receptor–ligand complex for
other ligands before their actual laboratory synthesis. The
(
rmsd) between simulated and reported conformations.
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Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
docking protocol was further used to optimize the struc-
ture of ligand shortlisted through virtual screening.
inhibited acetylcholinesterase (AChE) enzyme. If a single
molecule shows both mAChR inhibition and reactivation
of NA inhibited AChE then it would have a great value as
antidote against NAs.
Virtual screening and structure optimization
CD02464 mapped with corresponding pharmacophore
model 1 and model 2 is represented by Fig. 3c, d. The mol-
ecule has all the requisite features. Interaction of CD02464
with M3 receptor was determined by AutoDock with same
protocol developed for TIO. Docking of CD02464 with M3
receptor (pdb id: 4daj) is represented in Fig. 3e. A strong
hydrogen bond was observed between oxime –OH of
CD02464 and THR231 of M3 receptor. However, it showed
inferior binding energy of − 32.3 kJ/mol (Table 1) with
the receptor in comparison to atropine (− 43.05 kJ/mol,
Table S1, sl no 1) and TIO (− 53.84 kJ/mol, Table S1, sl
no 5). A good inhibitor must show strong binding with its
Pharmacophore-based virtual screening is a quick and eꢀec-
tive screening method to search putative antagonists from
larger databases. The burden of experimentation could be
reduced many-fold by receptor–ligand docking in combi-
nation with pharmacophore screening. Pharmacophore
model 1 and model 2 were used sequentially to screen May-
bridge2004 database to identify 81 hit molecules (Fig. 3a).
CD02464 (1-[4-methoxy-3-(morpholimethyl)phenyl]
ethane-1-one oxime, Fig. 3b) was cherry picked from the
hit molecules because it contains an oxime moiety. Oxi-
mes, especially aldoximes are used as reactivators for OP
Fig. 3 Screening of Maybridge database by pharmacophore mod-
els (a); structure of CD02464 (b); Pharmacophore model 1 mapping
of CD02464 (c); pharmacophore model 2 mapping CD02464 (d);
CD02464 docked with M3 receptor (e); structure of 2-chloro-4-(3,5-
dimethylpiperazin-1-yl)benzonitrile (11) (f); 2-chloro-4-(3,5-dimeth-
ylpiperazin-1-yl)benzonitrile mapped with pharmacophore model 2
(g); 2-chloro-4-(3,5-dimethylpiperazin-1-yl)benzonitrile (11) docked
with M3 receptor (h); structure of 2-chloro-4-(3,5-dimethylpiperazin-
1-yl)-N-hydroxybenzamidine (12) (i); 2-chloro-4-(3,5-dimethylpiper-
azin-1-yl)-N-hydroxybenzamidine (12) docked with M3 receptor (j);
2-chloro-4-(3,5-dimethylpiperazin-1-yl)-N-hydroxybenzamidine (12)
mapped on model 2 (k)
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R. Ghorpade et al.
Table 1 Binding energy of
compounds modiꢁed from
CD02464 estimated by
AutoDock
Binding
a
−1
energy /kJ mol
Code
CD02464
R1
R2
H
R3
R4
H
HO
N
N
N
OMe
− 32.3
N
N
N
N
O
O
O
HO
HO
HO
NH2
NH2
NH2
1
2
3
H
H
− 36.65
− 35.64
− 37.40
− OMe
H
N
H
NH
HO
N
NH2
4
H
H
− 40.20
NH
HO
N
NH2
5
6
−OMe
H
− 38.03
− 40.29
NH
HO
N
NH2
H
H
− OMe
NH
HO
N
NH2
NH2
N
7
F
− 43.97
NH
HO
N
8
9
H
H
H
H
F
− 39.78
− 39.70
− 39.91
− 57.36
NH
NH
HO
N
− OMe
HO
N
NH2
NH2
1
0
1
Cl
Cl
NH
N
1
− CN
NH
HO
N
12
H
Cl
N
− 48.28
NH
aEstimated by AutoDock
receptor. To improve the binding energy, the structure of
CD02464 was modiꢁed on the basis of molecular docking
with the receptor.
(12, Fig. 3f) were selected with nitrile and amidoxime
groups respectively. Later on, both the target molecules
were synthesized in accordance to Scheme 1 and evaluated
ex vivo to check the antagonistic potency of the synthe-
sized molecules on rat ileum.
A systematic modification of side groups was car-
ried out and binding energy was estimated by AutoDock
(
Table 1). When ketoxime group was modiꢁed to ami-
doxime, an improvement in binding energy was observed
Table 1, code 1). By introduction of 3,5-dimethylpipera-
Antimuscarinic activity
(
zine a signiꢁcant improvement of binding energy was esti-
mated (Table 1, code 7). Further improvement in binding
energy was observed when 3,5-dimethylpiperazine was
placed at para position and amidoxime was replaced by
nitrile group (Table 1, code 11). Binding energy decreased
when nitrile group was replaced again by amidoxime
group (Table 1, code 12). Finally 2-chloro-4-(3,5-dimeth-
ylpiperazin-1-yl)benzonitrile (11, Fig. 3i) and 2-chloro-
Compounds 11 and 12 were converted to their respec-
tive hydrochloride salts to make them soluble in KRS
(Krebs–Ringer solution) and evaluate their antimuscarinic
activity in a rat ileum model.
Control response of the mounted rat ileum was meas-
ured by adding cumulative dose (2.75 to 22 μM) of ACh.
Then the tissue was washed with KRS and treated with
11 (56 μM) for 10 min. Response was measured again by
adding cumulative dose (2.75 to 22 μM) of ACh. Percent
4
-(3,5-dimethylpiperazin-1-yl)-N-hydroxybenzamidine
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Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
Scheme 1
inhibitory activity for 11 was calculated as described in
materials and methods section. Similar experiment was
carried out for 12 (72 μM) to determine its inhibitory
activity. Compound 11 showed 33% inhibitory activity at
compound 11. A series of benzonitrile derivatives were syn-
thesized and evaluated for antimuscarinic activity (Table 2).
To study the eꢀect of position of piperazine group on activ-
ity, we synthesized compound 13 with a change of position
of piperazine from para to ortho position. The molecule was
found active (44% inhibition at 119 µM) but much lesser
than 11 (74% inhibition at 84 µM). So the position of pip-
erazine group plays an important role for inhibitory activ-
ity of muscarinic receptors. As per receptor–ligand docking
(Fig. 3k), piperazine forms a strong H-bond with TYR506
residue of the receptor through 4-NH group.
5
6 μM concentration (Fig. 4a). However, compound 12 did
not show any inhibition even at higher (72 μM) concentra-
tion (Fig. 4b). Receptor–ligand docking studies revealed
that the binding energy of 11 was more negative than that
of 12 (Table 1). Compound 12 binds with the receptor with
two strong hydrogen bonds with THR234 and TYR506
(
Fig. 3g). Compound 11 shows two hydrogen bonds with
SER151 and TYR506 of the receptor (Fig. 3k). Compound
To establish the role of piperazine and corresponding
hydrogen bonding, three molecules (14, 15, and 16) were
synthesized with benzyl groups (Table 2) in place of pipera-
zine. As expected, all of them did not show activity and thus
validated the hypothesis. To further strengthen the H-bond
hypothesis between receptor and ligand for activity, we
synthesized N-4 substituted analogs (17, 18, and 19) and
evaluated (Table 2). Due to substitution at N-4 of pipera-
zine, H-bond formation was not possible and the molecules
did not show inhibitory activity. Replacement of chlorine
with ꢃuorine (Table 2, 20) and piperazine with morpholine
(Table 2, 21) resulted into a decreased activity.
1
1 and 12 possess all required pharmacophores, but only
compound 11 was found active. Hence shape and size of
the molecules may play important roles besides pharma-
cophores. This can be explained by mapping compounds
1
1 and 12 with pharmacophore model 2. According to
Model 2, there should not be much steric crowding at PI
and HBA features because most of the excluded volumes
are placed near to those two features (ꢁve near HBA and
three near PI). Both 11 and 12 bind with TYR506 through
the piperazine NH group which is the PI feature of both
molecules. The HBA features of 11 and 12 are nitrile and
amidoxime groups, respectively. The –NH group of the
Activity of compound 11 was determined at diꢀerent con-
centrations as given in Table 3. At 14 μM concentration the
activity was very low at 16% only. However, with increase
in dose, activity also increased and 77% inhibition was
achieved at 112 μM concentration (Table 3). However, with
increase in ACh concentration, eꢂcacy of 11 decreased.
Atropine sulfate showed 100% antagonistic activity at
0.3 μM concentration [14].
2
amidoxime does not participate in hydrogen bonding with
any residue. Amidoxime exerted more steric hindrances
than a smaller nitrile group, which may reduce the binding
eꢂciency of the ligand with the receptor. Based on above
observation we hypothesized that due to steric crowding,
compound 12 did not show any activity although it pos-
sesses all the required pharmacophoric features.
According to a report by Fleming et al. [20], nitrile con-
taining pharmaceuticals are getting attention as they are pre-
scribed for various medical indications. Nitrile group is sta-
ble, biocompatible and, in most cases passed through body
unchanged [21]. This perspective encourages us to investi-
gate the structure activity relationship of nitrile containing
Activity of compound 11 followed a sigmoid curve
(Fig. 5), but could not attend 100% inhibition. It showed
74% and 77% inhibition at 84 μM and 112 μM concentra-
tion, respectively. This indicates that compound 11 may be
selective for certain subtype of the muscarinic receptor. To
validate the hypothesis, molecular docking was implemented
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R. Ghorpade et al.
Fig. 4 Antimuscarinic activity of 2-chloro-4-(3,5-dimethylpiperazin-1-yl)benzonitrile hydrochloride (11) at 56 μM concentration (a) and
2
-chloro-4-(3,5-dimethylpiperazin-1-yl)-N-hydroxybenzamidine (12) at 72 μM concentration (b)
again. There are five subtypes of mAChR and they are
broadly classiꢁed as odd (M , M , and M ) and even num-
class of mAChR antagonist has been designed with the help
of computer aided drug designing techniques followed by wet
lab synthesis and pharmacological analysis. The molecule
showed 77% blocking at 112 μM concentration in the ex vivo
evaluation on rat ileum. Molecular docking indicated that the
1
3
5
bered (M and M ) subtypes.
2
4
Structures of M and M subtypes are reported in litera-
2
3
ture [16, 17], hence we took them as representatives of even
and odd subtypes of mAChR. Selectivity of 11 as an antago-
nist between M2 and M3 receptors was determined by dock-
ing with the validated protocols. The binding energy with
M2 and M3 was found to be − 63.88 kJ/mol and − 57.3 kJ/
mol, respectively. From binding energy calculation, it may
be hypothesized that 11 is partially more active on M2 than
M3 (Fig. 6).
designed molecule could be selective for M . This preliminary
2
ꢁnding supports the virtual screening techniques to ꢁnd poten-
tial antagonists for mAChR which can be used as antidotes for
NAs. Experimental conꢁrmation of selectivity between vari-
ous subtypes of mAChR receptors are required to ensure its
pharmacological application as antidote against NA poisoning.
Experimental
Conclusion
Pharmacophore modeling
Antimuscarinic agents are useful drug candidates for anti-
dote application against nerve agents. With a combination of
pharmacophore and docking protocols, new candidates can
be found and developed as next generation antidotes against
nerve agents. In the current work a benzonitrile piperazine
Pharmacophore hypotheses were generated using HipHop
algorithm as present in DiscoveryStudio™ 2.0 [22]. In
brief, training set molecules shown in Scheme 1 were
drawn and geometry optimized. Input parameters include
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3

Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
Binding energya Test
%Inhibitionb
Table 2 Binding energy
estimated by AutoDock and
antimuscarinic activity of
compounds modiꢁed from 11
kJ mol− 1
/
conc./μ
M
Code R1
R2
N
R3
H
R4
H
11
13
14
Cl
− 57.36
− 45.73
− 39.74
84
74
NH
N
H
H
NO
H
H
119
132
44
2
NH
Cl
− OCH
3
No activity
NH
15
16
17
Cl
H
H
H
H
F
− 38.99
− 40.25
− 44.64
121
87
No Activity
No activity
No activity
NH
H
H
NH
− OCH
3
77
N
N
NO2
Cl
1
8
H
H
NO
2
− 45.18
91
No activity
N
N
1
9
0
Cl
N
N
H
H
H
H
− 39.20
− 56.27
102
98
No activity
22
2
F
N
NH
2
1
N
H
NO
2
H
− 36.27
83
29
O
a
b
3
Calculated by AutoDock; Inhibition experimentally determined in presence of 0.5 μg/cm acetylcholine
concentration on rat ileum
Table 3 Antimuscarinic
activity of 2-chloro-4-(3,5-
dimethylpiperazin-1-yl)
benzonitrile (11) at diꢀerent
concentrations
Conc. of 113/μM ACh/μM %Blocka ACh/μM %Blocka ACh/μM %Blocka ACh/μM %Blocka
1
2
5
8
1
4
8
6
4
2.75
2.75
2.75
2.75
2.75
2.75
16
23
33
74
77
5.5
5.5
5.5
5.5
5.5
5.5
6
10
20
44
59
11
11
11
11
11
11
3
7
7
33
44
100
22
22
22
22
22
22
0
0
0
19
23
100
12
b
Control
100
100
a
Response measured from organogram on fresh tissues
Atropine sulfate 0.3 μM
b
features hydrogen bond donor (HBD), hydrogen bond accep-
tor (HBA), positive ionizable (PI), hydrophobe (HY) and
ring aromatic (RA), maximum 10 and minimum 1 features,
minimum inter feature distance 2.97 Å, maximum confor-
mations 255, energy threshold 83.68 kJ/mol and maximum
excluded volume limit was ꢁxed at 100. Poling algorithm
was used to generate conformations for each molecule in
Docking studies
Structures of M3 receptor (pdb id: 4daj) [16] and M2 recep-
tor (pdb id 3uon) [17] were downloaded from protein data
bank and the A-chains of the respective structures were
used for receptor–ligand interaction studies. Structures were
cleaned from water molecules and ligand molecules namely
tiotropium (TIO) and 3-quinuclidinyl-benzilate (QBZ) and
imported to MGLTools-1.5.4. TYR 426 (M2) and TYR
529 (M3) were selected as ꢃexible residues. Docking stud-
ies were carried out by AutoDock 4.1 [17]. For docking of
QBZ with M2 grid center was set at 9.962, − 0.679, − 8.229
and for TIO with M3, grid center was set at 6.597, 22.082,
‘
fast mode’. HipHop conducts an exhaustive search starting
with the simplest to more complicated pharmacophores. The
process continues until common pharmacophore combina-
tions can no longer be generated. The ꢁnal HipHop output
was top ten unique pharmacophores sorted from highest to
lowest scoring. Then the top ranked hypotheses were used
to screen Maybridge2004 database to shortlist template mol-
ecules [23].
1
3

R. Ghorpade et al.
3
8.793. Both the grid centers are present on the TYR 104
and TYR148 residues of M and M receptors, respectively.
2
3
Number of grid points in each direction was 60 and grids
were generated for each ligands before docking. Ligands
were prepared with Gastegier’s charges at prescribed tor-
sions. Lamarckian Genetic Algorithm (LGA) was used for
conformation generation and determination of best inter-
actions between receptor and ligand. Seed population was
1
50, number of evaluations was 2,500,000, and number of
generation was set at 27,000. Rate of mutation and crosso-
ver were 0.02 and 0.8, respectively. Top ten conformations
were returned after each run. Binding energy (kJ/mol) and
predicted inhibition constant (K ) were recorded.
i
Chemistry
Fig. 5 Antimuscarinic activity of 2-chloro-4-(3,5-dimethylpiperazin-
-yl)-N-hydroxybenzamidine (11) in presence of diꢀerent concentra-
tion of Ach
1
All the ꢁne chemicals and reagents were purchased from
Sigma-Aldrich and used without further puriꢁcation. Syn-
theses of compounds were carried out by a previously
Fig. 6 Structure of 11 (a); 11 docked with M receptor (c); 11 docked with M receptor; overlaying of M and M receptors docked with 11 (d)
3
2
2
3
1
3

Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
reported method [24]. Thin-layer chromatography was per-
formed using precoated TLC plates from Merck. Chromato-
graphic puriꢁcation of products was accomplished by ꢃash
column chromatography using 200–400 mesh silica. The
IR spectra of the synthesized compounds were recorded on
(KBr): ̄ꢀ=3460, 2942, 2729, 2556, 2222, 1657, 1600, 1507,
−
1
+
1459, 1266 cm ; ESI–MS: m/z=283.1319 (MH ).
2‑(3,5‑Dimethylpiperazin‑1‑yl)‑5‑nitrobenzonitrile (13,
3
C H N O ) In a round bottom ꢃask, 5 cm water, 0.498 g
1
3 16 4 2
1
13
Bruker TENSOR27 using KBr pellets. The H and C NMR
spectra of the synthesized compounds were recorded at
of 2-fluoro-5-nitrobenzonitrile (0.003 mol), 0.342 g of
2,6-dimethyl-1,4-piperazine (0.003 mol), 0.387 g of DIPEA
(0.003 mol), 0.096 g of TBAB (0.0003 mol), and 0.318 g
of Na CO (0.003 mol) was taken. Reaction was carried
4
00 MHz and 100 MHz on Bruker AVANCE 400 MHz and
JEOL 400 YH FT-NMR spectrometers respectively using
2
3
CDCl . Chemical shifts were reported in ppm with tetra-
out at reꢃux for 3 h. Then reaction mixture was cooled
and extracted with ethyl acetate. Product was puriꢁed by
ꢃash chromatography on silica using hexane–ethyl acetate
mobile phase to aꢀord 0.32 g 13 (42%). M.p.: 118–120 °C;
3
methylsilane (δ=0 ppm) as internal standard and chemical
shifts in Hz. Spin multiplicities are described as s (singlet),
t (triplet), q (quartet), and m (multiplet). Mass analysis was
performed on quadruple-time of ꢃight (Q-Tof) mass spec-
trometer (Agilent, USA) and quadruple mass spectrometer
1
H NMR (400 MHz, CDCl ): δ = 1.158 (s, 3H), 1.174 (s,
3
3H), 2.676–2.733 (m, 2H), 3.089–3.169 (m, 2H), 3.806–
3.838 (m, 2H), 6.956 (d, J = 8.0 Hz, 1H), 8.231–8.262
(dd, J = 12.0 Hz, 2.4 Hz, 1H), 8.421–8.414 (m, 1H) ppm;
(
Teledyne PURION™ S) using electrospray ionization (ESI)
in positive mode. Characterization data of synthesized mol-
ecules are provided in the supplementary information.
1
3
C NMR (100 MHz, CDCl ): δ = 19.1 (CH ), 50.7 (CH),
3
3
5
6.9 (CH ), 101.3 (CCN), 117.0 (CN), 117.6(CH), 128.8
2
2
‑Chloro‑4‑(3,5‑dimethylpiperazin‑1‑yl)benzonitrile (11,
(CH), 131.4 (CH), 139.1 (CNO ), 157.9 (C) ppm; FT-IR
2
C H ClN ) Brieꢃy, 0.465 g of 2-chloro-4-ꢃuorobenzoni-
(KBr): ̄ꢀ=3229, 2965, 2658, 2445, 2221, 1604, 1512, 1429,
1
3
16
3
−
1
+
trile (0.003 mol), 0.342 g of 2,6-dimethyl-1,4-piperazine
0.003 mol), 0.387 g of N,N-diisopropylethylamine (DIPEA,
.003 mol), 0.096 g of tetrabutylammonium bromide
TBAB, 0.0003 mol), and 0.318 g of Na CO (0.003 mol)
1347 cm ; ESI–MS: m/z=261 (MH ).
(
0
2‑(2‑Chlorobenzylamino)‑6‑methoxybenzonitrile (14,
3
(
C H ClN O) In a round bottom ꢃask, 5 cm water, 0.453 g
2
3
15 13
2
3
were taken in 5 cm water, in an oven dried round bottom
ꢃask. Reaction was carried out at reꢃux for 3 h. Then reac-
tion mixture was cooled and extracted with ethyl acetate.
Product was puriꢁed by ꢃash chromatography on silica
of 2-ꢃuoro-6-methoxybenzonitrile (0.003 mol), 0.423 g
of 2-chlorobenzylamine (0.003 mol), 0.387 g of DIPEA
(0.003 mol), 0.096 of TBAB (0.0003 mol), and 0.318 g of
Na CO (0.003 mol) was taken. Reaction was carried out
2
3
using hexane–ethyl acetate (8:2) as mobile phase aꢀorded
at reꢃux for 3 h. Then reaction mixture was cooled and
extracted with ethyl acetate. The product was puriꢁed by
ꢃash chromatography on silica using hexane–ethyl acetate
mobile phase to aꢀord 0.26 g 14 (33%). M.p.: 116–118 °C;
1
0
.41 g 11 (56%). M.p.: 140–142 °C; H NMR (400 MHz,
CDCl ): δ=1.165 (s, 3H), 1.181 (s, 3H), 2.446–2.503 (m,
3
2
6
H), 2.958–3.007 (m, 2H), 3.624–3.661 (m, 2H), 6.740–
1
.769 (dd, J=8.0 Hz, 2.4 Hz, 1H), 6.879 (m, 1H), 7.453 (d,
H NMR (400 MHz, CDCl ): δ = 3.894 (s, 2H), 3.972 (s,
3
1
3
J=8.8 Hz, 1H) ppm; C NMR (100 MHz, CDCl ): δ=19.5
3H), 4.541–4.553 (m, 1H), 6.175–6.264 (dd, J= 24.0 Hz,
3
(
CH ), 50.3 (CH), 55.6 (CH ), 100.2 (C), 112.1 (CN),
8.0 Hz, 1H), 6.800–6.806 (m, 2H), 7.239–7.284 (m, 2H),
3
2
1
3
1
17.3 (CH), 134.5 (CH), 136.0 (CCl), 153.6 (C) ppm; IR
7.336–7.424 (m, 1H), 7.499–7.558 (m, 1H) ppm; C NMR
(
KBr): ̄ꢀ=3443, 2942, 2730, 2556, 2222, 1600, 1508, 1458,
(100 MHz, CDCl ): δ = 45.1 (OCH ), 56.6 (CH ), 99.2
3
3
2
−
1
+
1
266 cm ; ESI–MS: m/z=250.1108 (MH ).
(CCN), 103.5 (CH), 106.8 (CH), 107.9 (CH), 108.1 (CN),
1
27.0 (CH), 128.4 (CH), 128.7 (CH), 129.6 (CH), 134.8
2
‑Chloro‑4‑(3,5‑dimethylpiperazin‑1‑yl)‑N‑hydroxybenza‑
(CCl), 151.1 (CCH ), 162.3 (CNH), 165.3 (CO) ppm; IR
2
midine (12, C H ClN ) Compound 12 was synthesized by
(KBr): ̄ꢀ=3352, 3037, 2849, 2222, 1611, 1508, 1479, 1298,
1
3
19
3
−
1
+
reꢃuxing 0.25 g of 11 (0.001 mol) with excess of hydroxy-
lamine hydrochloride in ethanol for 6 h in presence of a
base Na CO . Then ethanol was evaporated and the reac-
1083 cm ; ESI–MS: m/z=273.0783 (MH ).
4‑(Benzylamino)‑2‑chlorobenzonitrile(15, C H ClN ) In
2
3
14 11
2
3
tion mixture was reconstituted in ethyl acetate followed by
a round bottom ꢃask, 5 cm water, 0.465 g of 2-chloro-
4-ꢃuorobenzonitrile (0.003 mol), 0.321 g of benzylamine
(0.003 mol), 0.387 g of DIPEA (0.003 mol), 0.096 g of
TBAB (0.0003 mol), and 0.318 g of Na CO (0.003 mol)
washing with water. Organic layer was dried by sodium
sulfate and evaporated to dryness at reduced pressure to get
1
0
.23 g of 12 (83%). M.p.: 120–122 °C; H NMR (400 MHz,
2
3
CDCl ): δ=1.162 (s, 3H), 1.177 (s, 3H), 2.445–2.503 (m,
was taken. Reaction was carried out at reꢃux for 3 h. Then
reaction mixture was cooled and extracted with ethyl ace-
tate. Product was puriꢁed by ꢃash chromatography on silica
using hexane–ethyl acetate mobile phase to aꢀord 0.26 g
3
2
2
6
H), 2.954–3.003 (m, 2H), 3.619–3.656 (dd, J= 12.0 Hz,
.4 Hz, 2H), 6.735–6.763 (dd, J= 12.0 Hz, 2.4 Hz, 1H),
.872 (d, J=2.4 Hz, 1H), 7.466 (d, J=8.8 Hz, 1H) ppm; IR
1
3

R. Ghorpade et al.
1
1
5 (37%). Viscous liquid; H NMR (400 MHz, CDCl ):
of 1-phenylpiperazine (0.003 mol), 0.387 g of DIPEA
(0.003 mol), 0.096 g of TBAB (0.0003 mol), and 0.318 g
of Na CO (0.003 mol) was added. Reaction was carried
3
δ = 4.377 (d, J = 4 Hz, 2H), 4.825–4.849 (m, 1H), 6.497–
6
.524 (m, 1H), 6.670–6.676 (m, 1H), 7.326–7.412 (m, 6H)
2
3
1
3
ppm; C NMR (100 MHz, CDCl ): δ = 47.3 (CH ), 99.5
out at reꢃux for 3 h. Then reaction mixture was cooled and
extracted with ethyl acetate. The product was puriꢁed by
ꢃash chromatography on silica using hexane–ethyl acetate
mobile phase to aꢀord 0.46 g 18 (52%). M.p.: 142–144 °C;
3
2
(
CCN), 111.0 (CH), 112.5 (CH), 117.5 (CN), 127.2 (CH),
1
27.7 (CH), 128.8 (CH), 134.7 (CH), 137.1 (CH), 138.0
(
CCl), 151.9 (CNH) ppm; IR (KBr): ̄ꢀ=3369, 3032, 2908,
−
1
1
2
221, 1620, 1577, 1482, 1366, 1294, 1180 cm ; ESI–MS:
H NMR (400 MHz, CDCl ): δ = 3.343–3.369 (m, 4H),
3
+
m/z=243.0674 (MH ).
3.518–3.544 (m, 4H), 6.799–6.827 (m, 1H), 6.930–6.993
(
m, 4H), 7.311–7.351 (m, 2H), 7.497–7.519 (m, 1H) ppm;
1
3
2
(
0
0
‑Methoxy‑6‑[4‑(4‑nitrophenyl)piperazin‑1‑yl]benzonitrile
C NMR (100 MHz, CDCl ): δ=46.9 (CH ), 49.3 (CH ),
3
2
2
3
16, C H N O ) In a round bottom flask, 5 cm water,
100.8 (CCN), 112.2 (CH), 114.4 (CH), 116.3 (CH), 117.2
(CN), 120.4 (CH), 129.2 (CH), 134.6 (CH), 138.0 (CCl),
150.5 (C), 153.7 (C) ppm; IR (KBr): ̄ꢀ=2967, 2841, 2210,
1
8 18 4 3
.453 g of 2-ꢃuoro-6-methoxybenzonitrile (0.003 mol),
.621 g of 1-(4-nitrophenyl)piperazine (0.003 mol), 0.387 g
−
1
+
of DIPEA (0.003 mol), 0.096 g of TBAB (0.0003 mol), and
1602, 1499, 1382, 1231 cm ; ESI–MS: m/z=298 (MH ).
0
.318 g of Na CO (0.003 mol) was taken. Reaction was
2 3
carried out at reꢃux for 3 h. Then reaction mixture was
cooled and extracted with ethyl acetate. The product was
puriꢁed by ꢃash chromatography on silica using hexane–
2‑Fluoro‑4‑(3,5‑dimethylpiperazin‑1‑yl)benzonitrile (19,
3
C H FN ) In a round bottom ꢃask, 5 cm water, 0.417 g of
1
3
16
3
2,4-diꢃuorobenzonitrile (0.003 mol), 0.342 g of 2,6-dimeth-
ylpiperazine (0.003 mol), 0.387 g of DIPEA (0.003 mol),
0.096 g of TBAB (0.0003 mol), and 0.318 g of Na CO
ethyl acetate mobile phase to aꢀord 0.42 g 16 (42%). M.p.:
1
1
60–164 °C; H NMR (400 MHz, CDCl ): δ=3.939 (s, 4H),
3
2
3
3
.649 (s, 4H), 3.953 (s, 3H), 6.630 (d, J=4 Hz, 2H), 6.893
(0.003 mol) was taken. Reaction was carried out at reꢃux
for 3 h. Then reaction mixture was cooled and extracted
with ethyl acetate. The product was puriꢁed by ꢃash chro-
matography on silica using hexane–ethyl acetate mobile
(
d, J=8 Hz, 2H), 7.460 (t, J=8 Hz, 1H), 8.165 (d, J=8 Hz,
13
2
H) ppm; C NMR (100 MHz, CDCl ): δ=46.1 (CH ), 46.8
3 2
(
CH ), 47.2 (CH ), 50.9 (CH ), 56.1 (OCH ), 104.8 (CCN),
2
2
2
3
1
1
10.5 (CH), 112.9 (CH), 115.7 (CN), 129.9 (CH), 134.4
phase to aꢀord 0.4 g 19 (59%). M.p.: 82–84 °C; H NMR
(
CH), 138.8 (CNO ), 154.7 (C), 156.6 (C), 163.0 (CO) ppm;
(400 MHz, CDCl ): δ=1.160 (s, 3H), 1.177 (s, 3H), 2.421–
2
3
IR (KBr): ̄ꢀ = 2886, 2215, 1594, 1480, 1322, 1600, 1508,
2.480 (m, 2H), 2.880–2.930 (m, 2H), 3.773–3.810 (m, 2H),
−
1
+
13
1
458, 1266 cm ; ESI–MS: m/z=339 (MH ).
6.753–6.819 (m, 2H), 7.421–7.463 (m, 1H) ppm; C NMR
(
100 MHz, CDCl ): δ=19.3 (CH ), 50.1 (CH), 53.4 (CH ),
3 3 2
5
(
0
‑[4‑(2‑Chlorophenyl)piperazin‑1‑yl]‑2‑nitrobenzonitrile
100.2 (CCN), 109.6 (CH), 115.3 (CN), 133.7 (CH), 154.9
3
17, C H ClN O ) In a round bottom ꢃask, 5 cm water,
(CH), 163.4 (C), 165.9 (CF) ppm; IR (KBr): ̄ꢀ=2961, 2219,
1
7
15
4 2
−
1
.498 g of 5-ꢃuoro-2-nitrobenzonitrile (0.003 mol), 0.588 g
1628, 1518, 1455, 1330, 1256 cm ; ESI–MS: m/z = 234
+
of 1-(2-chlorophenyl)piperazine (0.003 mol), 0.387 g of
DIPEA (0.003 mol), 0.096 g of TBAB (0.0003 mol), and
(MH ).
0
.318 g of Na CO (0.003 mol) was taken. Reaction was car-
2‑(Morpholin‑4‑yl)‑5‑nitrobenzonitrile (20, C H N O ) In
2
3
11 11 3 3
3
ried out at reꢃux for 3 h. Then reaction mixture was cooled
and extracted with ethyl acetate. The product was puriꢁed by
ꢃash chromatography on silica using hexane–ethyl acetate
mobile phase to aꢀord 0.38 g 17 (38%). M.p.: 158–160 °C;
a round bottom ꢃask, 5 cm water, 0.261 g of morpho-
line (0.003 mol), 0.498 g of 2-ꢃuoro-5-nitrobenzonitrile
(0.003 mol), 0.387 g of DIPEA (0.003 mol), 0.096 g of
TBAB (0.0003 mol), and 0.318 g of Na CO (0.003 mol)
2
3
1
H NMR (400 MHz, CDCl ): δ = 3.262–3.327 (m, 4H),
was taken. Reaction was carried out at reꢃux for 3 h. Then
reaction mixture was cooled and extracted with ethyl acetate.
The product was puriꢁed by ꢃash chromatography on silica
using hexane–ethyl acetate mobile phase to aꢀord 0.35 g
3
3
.682–3.733 (m, 4H), 6.979–7.000 ( m, 1H), 7.048–7.130
(
m, 2H), 7.389–7.572 (m, 2H), 8.321–8.348 (m, 1H), 8.351–
1
3
8
.354 (m, 1H) ppm; C NMR (100 MHz, CDCl ): δ=50.8
3
1
(
CH ), 50.9 (CH ), 102.5 (CCN), 117.9 (CN), 120.6 (CH),
20 (52%). M.p.: 118–120 °C; H NMR (400 MHz, CDCl ):
2
2
3
1
21.8 (CH), 124.5 (CH), 127.7 (CH), 128.8 (CH), 129.0
δ = 3.498–3.552 (m, 4H), 3.914–3.938 (m, 4H), 7.012 (d,
(
CCl), 130.7 (CH), 131.2 (CH), 133.1 (CH), 139.8 (CNO ),
J=9.2 Hz, 1H), 8.328 (dd, J=6.4 Hz, 2.8 Hz, 1H), 8.791 (d,
2
13
1
58.5 (C) ppm; IR (KBr): ̄ꢀ=2839, 2227, 1597, 1443, 1341,
J=2.8 Hz, 1H) ppm; C NMR (100 MHz, CDCl ): δ=50.6
3
−
1
+
1
230 cm ; ESI–MS: m/z=343.0944 (MH ).
(CH), 66.3 (CH ), 102.4 (CCN), 116.7 (CH), 117.5 (CN),
2
1
28.9 (CH), 131.1 (CH), 139.9 (CNO ), 158.3 (C) ppm; IR
2
−
1
2
‑Chloro‑4‑(4‑phenylpiperazin‑1‑yl)benzonitrile (18,
(KBr): ̄ꢀ=2861, 2218, 1678, 1602, 1509, 1447, 1346 cm ;
3
+
C H ClN ) In a round bottom ꢃask, 5 cm water, 0.465 g
ESI–MS: m/z=234 (MH ).
1
7
16
3
of 2-chloro-4-fluorobenzonitrile (0.003 mol), 0.486 g
1
3

Design and synthesis of muscarinic acetylcholine receptor (mAChR) antagonist:…
2
‑(Benzylamino)‑6‑fluorobenzonitrile (21, C H FN ) In
interest and encouragement in the present work. The authors thank Ms.
Tara Yadav for characterizing the synthesized molecules.
1
4
11
2
3
a round bottom flask, 5 cm water, 0.321 g of ben-
zylamine (0.003 mol), 0.417 g of 2,6-diꢃuorobenzonitrile
(
0.003 mol), 0.387 g of DIPEA (0.003 mol), 0.096 g of
TBAB (0.0003 mol), and 0.318 g of Na CO (0.003 mol)
References
2
3
was taken. Reaction was carried out at reꢃux for 3 h. Then
reaction mixture was cooled and extracted with ethyl acetate.
The product was puriꢁed by ꢃash chromatography on silica
1
.
Yamada M, Lamping K, Duttaroy A, Zhang W, Cui Y, Bymaster
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using hexane–ethyl acetate mobile phase to aꢀord 0.27 g
2
3
.
.
Khurana S, Chacon I, Xie G, Yamada M, Wess J, Raufman JP,
Kennedy RH (2004) Eur J Pharmacol 493:127
1
2
1 (41%). M.p.: 96–98 °C; H NMR (400 MHz, CDCl ):
3
Gil D, Krauss H, Bogardus A (1997) Invest Ophthalmol Vis Sci
δ = 4.467 (s, 2H), 6.418–6.476 (m, 2H), 7.276–7.417 (m,
3
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1
3
6
1
H) ppm; C NMR (100 MHz, CDCl ): δ = 47.6 (CH ),
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4
5
.
.
Wang Z, Shi H, Wang H (2004) Br J Pharmacol 142:395
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03.2 (CCN), 103.4 (CH), 106.5 (CH), 113.3 (CN), 127.1
(
CH), 127.8 (CH), 128.7 (CH), 128.9 (CH), 135.1 (CH),
37.6 (CH), 151.3 (C), 162.6 (CNH), 165.2 (CF) ppm;
FT-IR (KBr): ̄ꢀ=3369, 3032, 2221, 1620, 1577, 1526, 1482,
6
7
8
9
.
.
.
.
Fryer A, Jacoby D (1998) Am J Respir Crit Care Med 158:S154
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1
−
1
+
1
308, 1294 cm ; ESI–MS: m/z=227 (MH ).
Malbon C (2005) Nat Rev Mol Cell Biol 6:689
1
1
1
0. Bonner T, Buckley N, Young A (1987) Science 237:527
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4. Acharya BN, Rao GBD, Kumar D, Kumar P, Kaushik MP (2015)
Med Chem Res 24:1763
In a typical experimental protocol [25] male rats were killed
by decapitation. Two-centimeter long of terminal ileum was
dissected out proximal to 5 cm from the ileum–cecum junc-
tion and mounted in organ bath containing Krebs–Ringer
solution (KRS) at 35 °C and aerated with 95% oxygen and
1
5. Kurogi Y, Güner OF (2001) Curr Med Chem 8:1035
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(2012) Nature 482:547
5
% carbon dioxide in an automatic organ bath (Panlab, Har-
3
vad). Composition of 1 dm KRS was: 6.9 g NaCl (118 mM),
18. Morris GM, Huey R, Lindstorm W, Sanner MF, Belew RK, Good-
shell DS, Olson AJ (2009) J Comput Chem 16:2785
3
2
.1 g NaHCO (2.5 mM), 3.6 cm 10% KCl (4.8 mM), 2.9
3
1
9. IUPHAR/BPS Guide to pharmacology https://www.guidetopha
rmacology.org/GRAC/ReceptorFamiliesForward?type=GPCR.
Accessed 28 Nov 2016
3
3
cm 10% MgSO .7H O (1.2 mM), 3.6 cm 10% KH PO
4
2
2
4
3
(
(
1.2 mM), 3.7 cm 10% CaCl (2.5 mM), 2 g glucose
2
3
11 mM) in 1 dm water. Stock solution of all the compounds
20. Fleming FF, Yao L, Ravikumar PC, Funk L, Shook BC (2010) J
Med Chem 53:7902
were prepared in KRS and kept at room temperature. Con-
tractions induced by acetylcholine (ACh) (2.75, 5.5, 11,
and 22 μM) in the mounted strip of ileum was recorded on
Powerlab 4/30 (AD Instruments) using isometric transducer
2
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TRI 201 AD). Tissues were stabilized for 30 min and con-
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various concentrations of the test compounds for 10 min fol-
lowed by recording of a cumulative dose–response curve
of ACh in the presence of the compound. Responses were
expressed as a percentage of the maximal responses obtained
in the control dose–response curve by following equation:
2
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Publisher’s Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional aꢂliations.
ꢀ
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%
Inhibition = {response}treated/{response}control × 100.
Acknowledgements This manuscript is assigned DRDE accession no.
DRDE/SC/002/2018. We thank Director, DRDE, Gwalior for his keen
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