3D QSAR studies based in silico screening of 4,5,6-triphenyl-1,2,3,4- tetrahydropyrimidine analogs for anti-inflammatory activity

Article abstract of DOI:10.1016/j.ejmech.2013.10.083

The 3D QSAR studies based on generation of common pharmacophore hypotheses (CPHs) were performed separately for the series of 1,2,3,4-tetrahydropyrimidin- 5-yl-acetic acid and 2-(4-sulfonylphenyl)pyrimidine analogs for their in-vivo anti-inflammatory acti

Full text of DOI:10.1016/j.ejmech.2013.10.083

European Journal of Medicinal Chemistry 73 (2014) 233e242
Contents lists available at ScienceDirect
European Journal of Medicinal Chemistry
journal homepage: http://www.elsevier.com/locate/ejmech
Original article
3D QSAR studies based in silico screening of 4,5,6-triphenyl-
1,2,3,4-tetrahydropyrimidine analogs for anti-inflammatory activity
,
Deepak K. Lokwani a, Santosh N. Mokale b, Devanand B. Shinde a
*
a Department of Chemical Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad 431004, M.S., India
b Dr. Rafiq Zakaria Campus, Y.B. Chavan College of Pharmacy, Aurangabad 431001, M.S., India
a r t i c l e i n f o
a b s t r a c t
Article history:
The 3D QSAR studies based on generation of common pharmacophore hypotheses (CPHs) were per-
formed separately for the series of 1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid and 2-(4-sulfonylphenyl)
pyrimidine analogs for their in-vivo anti-inflammatory activity and in-vitro COX-2 inhibitory activity
respectively. The main idea of selecting two different series was to develop two 3D QSAR models for
same scaffold (1,2,3,4-tetrahydropyrimidine/pyrimidine) for same target, but with different aspects of
activity. The aim of study was to screen designed compounds and select new compounds with increased
COX-2 selectivity. The best 3D QSAR model from both group was employed as 3D search query to screen
the designed 4,5,6-triphenyl-1,2,3,4-tetrahydropyrimidine derivatives. The new compounds showing
good predicted activity were selected for experimental studies. Among the synthesized compounds, 5c
and 5f showed highest anti-inflammatory activity.
Received 9 April 2013
Received in revised form
16 October 2013
Accepted 21 October 2013
Available online 25 December 2013
Keywords:
3D QSAR
Anti-inflammatory
COX-2
Ó 2013 Elsevier Masson SAS. All rights reserved.
1,2,3,4-Tetrahydropyrimidine
Common Pharmacophore Hypotheses
(CPHs)
1. Introduction
with coxib can only be reduced by development of new generation
of COX-2 inhibitors to avoid the unwanted cardiac effects.
The discovery of two distinct isoforms (COX-1 and COX-2) of
enzyme Cyclooxygenase (COX) in 1990s led to the development of a
new class of Nonsteroidal anti-inflammatory drugs (NSAIDs), se-
lective for COX-2, named coxibs [1]. COX-2 is primarily responsible
for proinflammatory conditions, while COX-1 is constitutive and
responsible for the maintenance of physiological homeostasis, such
as gastrointestinal integrity and renal function [2]. Thus the selec-
The search for COX selective inhibitors is somewhat complicated
by the close structural similarities between COX-1 and COX-2. Both
COX-1 and COX-2 are homodimers of 70 kDa subunits composed of
N-terminal epidermal growth factor like module, a-helical mem-
brane binding domain and a large C-terminal globular catalytic
domain with active site (Cyclooxygenase and peroxidase containing
heme cofactor) [5]. COX catalytic domain in COX-2 is 20% larger and
differs in the presence of side pocket when compared to COX-1. The
main and important difference in side pocket is the presence of
valine in COX-2 and isoleucine in COX-1 at position 523 which
enables interaction of the sulfonamide or sulfone group of the
coxibs with Arg 513 in the side pocket of COX-2 [6]. The X-ray
crystallography, kinetic studies, and molecular modeling are among
the most explored tools to understand both the selectivity and
binding mode of nonselective and selective inhibitors. Therefore,
these approaches constitute the primary source of information
toward the rational drug design of novel selective COX-2 inhibitors.
The major class of coxibs possess 1,2-diarylsubstitution on
a central hetero or carbocyclic ring system with a characteristic
methanesulfonyl, sulfonamido, or methanesulfonamide group
on one of the aryl rings that plays a crucial role for COX-2 selectivity
tive COX-2 inhibitors provided
a potential class of anti-
inflammatory agents which overcomes the gastrointestinal (GI)
side effects associated with use of traditional NSAIDs (t-NSAIDs).
However, the long-term use of both t-NSAIDs and coxibs has been
reported to cause significant cardiovascular effects, myocardial in-
farctions, and strokes. Unfortunately, the withdrawal of rofecoxib
from market in the fall of year 2004 after its clinical report of its
linkage to increased risk of cardiovascular toxicity has widely
affected the safety of coxib [3,4]. But it is still remains dubious
whether the observed cardiovascular toxicity of rofecoxib is a class
effect or individually drug specific. Hence, the conflict associated
* Corresponding author. Tel.: þ91 240 2403308.
[7e9]. Recently, we have reported
a series of 1,2,3,4-tetra
E-mail address: dbsdeepak10@rediffmail.com (D.B. Shinde).
0223-5234/$ e see front matter Ó 2013 Elsevier Masson SAS. All rights reserved.
http://dx.doi.org/10.1016/j.ejmech.2013.10.083

234
D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
hydropyrimidine analogs containing triaryl ring rather than diaryl
with good selectivity for COX-2 over COX-1 isoform [10].
I, percent inhibition of inflammation (i.e., reduction in rat paw
edema volume) by 1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid
derivatives was transformed [14,15] into the log activity using
Equation (1). Whereas pIC50 (log (1/IC50)) values of 2-(4-
sulfonylphenyl)pyrimidines derivatives against COX-2 inhibition
were used for generation of 3D QSAR model II.
In this study, we have reported synthesis and biological evalu-
ation of new 4,5,6-triaryl-1,2,3,4-tetrahydropyrimidine analogs as
COX-2 inhibitors. On which aryl ring, p-methylsulfonyl or p-ami-
nosulfonyl is being to be substituted, based on this concept, new
analogs were designed. For the screening of designed compounds,
two 3D QSAR models were developed based on generation of
Common pharmacophore hypotheses (CPHs). The 3D QSAR model I
was developed for 1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid
reported for in-vivo anti-inflammatory activity and the 3D QSAR
model II was developed for 2-(4-sulfonylphenyl)pyrimidines ana-
logs for their in-vitro COX-2 inhibitory activity (Fig. 1). The aim of
selecting two different series with in-vivo and in-vitro anti-
inflammatory activity for 3D QSAR studies was to find new com-
pounds with high affinity for COX-2 enzyme. The generated models
were used as search query to virtually screen designed 4,5,6-triaryl-
1,2,3,4-tetrahydropyrimidine analogs. The ten new compounds
were selected, synthesized and evaluated for anti-inflammatory
activity.
Log Activity ¼ ꢀlog c þ log it
(1)
Where,
‘c’ (molar concentration) ¼ concentration (
mg/ml) ꢁ 0.001/mo-
lecular weight,
‘it’ stands for inhibition and log it ¼ log [% inhibition/100 ꢀ %
inhibition]
The variant CPHs were generated, examined and scored to
identify the common pharmacophore that yields the best align-
ment of the active compounds (log activity > 0.817 for QSAR model
I and pIC50 > 2.80 for QSAR model II). All CPHs were validated by
aligning and scoring the inactive compounds (log activity < 0.510
for QSAR model I and pIC50 < 1.60 for QSAR model II). The CPH's
models whose the survival-inactive scores ranked in the top 1% for
alignment of all compounds were selected for development of both
3D-QSAR model I and 3D-QSAR model II. The CPHs selected for
development of 3D QSAR model I and 3D-QSAR model II were
found to have the three-point features (one negatively charged
group (N) and two aromatic Rings (R) features) and the five-point
features (four hydrogen bond acceptor (A), and one aromatic
ring (R) features) respectively. The 3D QSAR model I and 3D QSAR
model II were constructed with twenty six and eighteen com-
pounds included in training set with diverse activity respectively
(Tables 1 and 2). The rest of compounds in both series were kept
aside as a test set for validation and testing of constructed 3D QSAR
models. The 3D QSAR models were generated using Partial Least
Square (PLS) regression method. One model in each category of 3D
QSAR model I and 3D QSAR model II was selected based on sta-
tistical results and comparison of experimental and predicted ac-
tivity (log activity for 3D QSAR model I and pIc50 for QSAR model II).
The R2, SD, F, P and stability results were used to evaluate the
training set predictions and the Q2, RMSE and Pearson-R values
were used to evaluate the test set prediction (Table 3).
2. Result and discussion
2.1. Development of QSAR model I and 3D QSAR model II
The thirty six 1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid de-
rivatives with their in-vivo anti-inflammatory activity [11,12] were
selected for 3D QSAR model I, based on the criteria that the
designed 4,5,6-triaryl-1,2,3,4-tetrahydropyrimidine derivatives are
the optimized analogs of this selected series. The 3D QSAR models
developed for this series will be helpful to predict correctly the
activity of new untested compounds. The twenty three 2-(4-
sulfonylphenyl)pyrimidine derivatives reported as COX-2 in-
hibitors [13] were selected for development of 3D QSAR model II
with aim to predict the COX-2 inhibiting activity of the new un-
tested compounds. For the sake of study to develop 3D QSAR model
2.2. Analysis of 3D QSAR models
The contribution map obtained from 3D QSAR models identifies
features of ligands for interaction with target protein. Thus map
identifies particular position in ligand that requires specific physi-
cochemical properties to enhance the bioactivity of ligands. A
pictorial representation of the contribution map is shown in
Fig. 2aed and 3aef. In these representations, blue cubes indicate
favorable features and red cubes represent unfavorable features in
compounds for activity. The equal positive and negative thresholds
were set while visualizing the 3D QSAR in context of all ligands.
2.2.1. 3D QSAR model I
Fig. 2aed shows the visualization of results of 3D QSAR model I
when applied to compounds in the series of 1,2,3,4-
tetrahydropyrimidin-5-yl-acetic acid derivatives (Table 1). As per
the common pharmacophore of 1,2,3,4-tetrahydropyrimidin-5-yl-
acetic acid derivatives, the changes in nature of substituents are
seen in combined hydrophobic and electronegative features at R1
position and hydrophobic features at R2 position. When these
above hydrophobic and electronegative features visualized indi-
vidually or combined in context of most active compound A27 and
Fig. 1. Flow chart of in silico screening using 3D QSAR studies.

D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
235
Table 1
Table 2
1,2,3,4-Tetrahydropyrimidin-5-yl-acetic acid derivatives selected for generation of
3D QSAR model I and their observed and predicted activity.
2-(4-Sulfonylphenyl)pyrimidine derivatives selected for generation of 3D QSAR
model II and their observed and predicted activity.
B1-B17, B19-B23: R4 = -CF3; B18: R4 = -OCH2CF3
A1-A18: R3= -NH; A19-A36: R3 = -S
Sr. no. R5
X
R6
Observed Predicted Residual
activity activity
Sr. no.
R1
R2
Observed
activity
Predicted
activity
Residual
(PIC50
)
(log activity)
B1
B2
B3a
B4
B5
B6
B7
B8
B9
eCH3 eNHe eC6H5
2.25
1.95
2.14
3.6
2.30
2.30
2.30
3.40
1.64
3.67
0.57
2.30
2.89
2.85
2.70
3.30
2.42
1.54
1.75
2.30
ꢀ0.05
ꢀ0.35
ꢀ0.16
0.20
eCH3 eNHe eC6H4, e4-CH3
eCH3 eNHe eC6H4-4-F
eCH3 eNHe eCH2C6H5
eCH3 eNHe eCH2C6H4-4-CH3
eCH3 eNHe eCH2C6H4-4-F
eCH3 eNHe eH
A1
eC6H5
H
H
H
H
H
H
Cl
Cl
Cl
Cl
Cl
Cl
CH3
CH3
CH3
CH3
CH3
CH3
H
H
H
H
H
H
Cl
Cl
Cl
Cl
Cl
Cl
CH3
CH3
CH3
CH3
CH3
CH3
0.64
0.64
0.82
0.51
0.55
0.30
0.78
0.74
0.92
0.64
0.56
0.54
0.82
0.68
0.88
0.64
0.54
0.58
0.52
0.88
0.92
0.64
0.57
0.46
0.65
0.82
1.02
0.54
0.24
0.35
0.82
0.72
0.96
0.28
0.31
0.11
0.7
0.51
0.9
ꢀ0.06
0.13
ꢀ0.08
ꢀ0.08
0.1
A2a
A3a
A4
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
e3-Pyridine
eC6H5
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
e3-Pyridine
eC6H5
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
e3-Pyridine
eC6H5
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
e3-Pyridine
eC6H5
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
e3-Pyridine
eC6H5
eC6H4-4-Cl
eC6H4-4-OCH3
e2-Thiophene
e2-Furan
2
0.36
0.59
0.45
0.32
0.73
0.78
0.89
0.63
0.58
0.51
0.81
0.78
0.93
0.63
0.53
0.5
A5a
A6
3.55
0.56
2.3
2.88
2.85
2.69
3.3
ꢀ0.12
0.00
ꢀ0.02
eCH3 eNHe eCH2CH3CH3
eCH3 eNHe en-CH2CH3CH3CH3
0.00
A7
0.05
A8a
A9
ꢀ0.04
0.03
0.01
ꢀ0.01
B10a eNH2 eNHe en-CH2CH3CH3CH3
0.00
B11
B12
eCH3 eNHe ei-CH2CH3CH3CH3
eCH3 eNHe eC6H11
ꢀ0.01
0.00
0.19
ꢀ0.01
ꢀ0.01
0.00
A10
A11
A12
A13
A14
A15
A16
A17
A18
A19a
A20
A21a
A22a
A23
A24
A25
A26
A27
A28
A29a
A30
A31
A32
A33a
A34
A35a
A36
ꢀ0.02
B13a eNH2 eNHe eC6H11
2.61
1.53
0.03
B14
B15
B16
eCH3 eNHe eCH2C6H11
eCH3 eNHe e4-Tetrahydro-2H-pyran 1.74
eCH3 eNHe e4-Methyltetrahydro-
2H-pyran
eCH3 eNCH3e eCH2C6H5
eCH3 eNHe eC6H11
0.01
ꢀ0.1
ꢀ0.05
0.01
0.01
0.08
2.3
B17
B18
2.3
2.52
1.80
1.67
1.20
1.48
1.66
1.35
ꢀ0.22
ꢀ0.01
ꢀ0.01
0.00
1.79
1.66
1.2
1.48
1.65
1.34
B19a eCH3 eOe
en-CH2CH3CH3CH3
ei-CH2CH3CH3
et-CH2CH3CH3CH3
eCH2C5H9
0.7
ꢀ0.18
B20
B21
B22
eCH3 eOe
eCH3 eOe
eCH3 eOe
0.77
0.85
0.51
0.55
0.34
0.72
0.79
1.00
0.56
0.47
0.26
0.72
0.79
0.86
0.29
0.47
0.34
0.11
0.00
0.07
0.13
0.02
0.12
ꢀ0.01
B23a eCH3 eOe
eCH2C6H11
ꢀ0.01
a
Compounds in test set.
ꢀ0.07
0.03
0.02
show any blue cubes (Fig. 2aed). This suggests the presence of
hydrophobic features at R2 position is important for activity.
ꢀ0.02
ꢀ0.23
0.09
0.1
2.2.2. 3D QSAR model II
ꢀ0.07
Fig. 3aef shows the visualization of results of 3D QSAR model II
when applied to compounds in the series of 2-(4-sulfonylphenyl)
pyrimidines derivatives (Table 2). For the simplicity and for
comparing the inhibitory activity of compounds, H-bond donor and
hydrophobic features were selected and visualized in the context of
active, moderate and inactive compounds in the series. When
visualizing the H-bond donor features in context of compounds, the
blue cubes were seen around eNH group at X position in com-
pounds B1eB16 and no blue or red cubes were seen around eNCH3
and eO group at X position in compounds B17 and B19eB23
respectively (Fig. 3aec). This suggests that H-bond donor features
at X position are important for activity. Similarly when visualizing
the hydrophobic features in the context of compounds, the blue
0.1
ꢀ0.01
ꢀ0.16
ꢀ0.23
e3-Pyridine
a
Compounds in test set.
least active compound A36, the blue cubes were observed around
methoxy group of phenyl ring at R1 position and chloro group at R2
position in compound A27. Whereas red cubes were seen around
pyridine ring at R1 position in compound A36 (Fig. 2a and b). This
suggested that the phenyl ring (hydrophobic features) with elec-
tron donating groups at R1 position is important for activity. The
less hydrophobic features or changing in the position of electro-
negative groups decreases the activity of compounds. Thus the
compound A36 show red cubes around pyridine ring. Similarly
other compounds A4, A5, A6 and many more in the series con-
taining hetero ring at R1 position shows the red cubes (Fig. 2c) and
thus the less active as compared to the compounds containing
phenyl ring or substituted phenyl ring at R1 position. While
comparing the substitution pattern at R2 position, some blue cubes
are found around chloro and methyl group in compounds A27, A11,
A15, A34 and many more in series. But replacement of these groups
by hydrogen in compounds A3, A5 and many more in series, not
Table 3
Statistical results for QSAR model I and QSAR model II.
Sr. no.
Statistical parameters
QSAR model I
QSAR model II
1
2
3
4
5
6
7
8
SD
0.0841
0.8733
36.2
0.2613
0.8139
19
R2
F
P
3.87E-09
0.5073
0.1346
0.6512
0.8114
4.987e-05
0.3688
0.1203
0.955
Stability
RMSE
Q2
Pearson-R
0.9793

236
D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
Fig. 2. Pictorial representation of the cubes generated using the 3D QSAR model I. Blue cubes indicate favorable regions, while red cubes indicate unfavorable region for the activity.
QSAR model visualized in the context of favorable and unfavorable feature for (a) compound A27, (b) compound A36, (c) compound A5 and (d) compound A34. (For interpretation of
the references to color in this figure legend, the reader is referred to the web version of this article.)
cubes were found around phenyl ring or substituted phenyl ring at
R6 position in compounds B1eB6 and many more in series (Fig. 3d).
Whereas the mixed blue and red cubes were found when R6 po-
sition is unsubstituted as in compound B7 (Fig. 3e) or substituted by
aliphatic chain or hetero ring as in compounds B8eB11, B15, B16
and B19eB21 (Fig. 3f). This indicated that presence of phenyl ring
or substituted phenyl ring at R6 position is important for activity.
The small hydrophobic features at R4 position are also important
for activity, as the presence of eCF3 group shows blue cubes around
it in compounds, whereas the replacement of this group by e
OCH2CF3, shows the red cubes around it.
These compounds were selected based on criteria that compounds
showed good predicted activity against either both QSAR models or
individual QSAR model.
The synthetic route of selected designed 4,5,6-triphenyl-1,2,3,4-
tetrahydropyrimidine derivatives is outlined in Schemes 1 and 2.
The compounds 5aeg were synthesized in major four steps. The
starting material, 1-(4-(methylthio)phenyl)-2-phenylethanone (3a)
was synthesized in two steps using intermediate phenyl acetyl
chloride (2) which was prepared by chlorination of phenyl acetic
acid (1) using thionyl chloride. The synthesized phenyl acetyl
chloride was then made to react with thioanisole in dichloro-
methane in the presence of anhydrous AlCl3 to undergo Friedele
Crafts acylation which gave 1-(4-(methylthio)phenyl)-2-
phenylethanone (3a) [10]. The methylthio group in compound 3a
was then oxidized by oxane in presence of acetone-water to
methylsulfonyl group which gave 1-(4-(methylsulfonyl)phenyl)-2-
phenylethanone (4a) [16]. The final compounds 5aeg were then
synthesized using one pot Biginelli reaction of 4a, substituted
aldehyde and urea/thiourea/guanidine hydrochloride in the pres-
ence of potassium carbonate and ethanol as solvent [10e12].
2.3. Screening of designed compounds and their synthesis
All designed compounds were first screened by predicting their
ADMET properties using Qikprop v3.5 (Schrödinger, LLC, New York,
NY, 2012). The compounds following Lipinski’s rule and other
ADMET properties were selected further for the prediction of their
activity using QSAR Model I and QSAR model II. The ten designed
compounds were selected for experimental validation (Table 4).

D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
237
Fig. 3. Pictorial representation of the cubes generated using the 3D QSAR model II. Blue cubes indicate favorable regions, while red cubes indicate unfavorable region for the activity.
QSAR model visualized in the context of favorable and unfavorable H-bond donor features for (a) compound B8, (b) compound B17 and (c) compound B22. QSAR model visualized in
the context of favorable and unfavorable hydrophobic features for (d) compound B6, (e) compound B7 and (f) compound B15. (For interpretation of the references to color in this
figure legend, the reader is referred to the web version of this article.)
1-(4-Chlorophenyl)-2-phenylethanone (3b) was prepared as
described for the synthesis of compounds 3a and was further used
for synthesis of final compounds 5hej. The treatment of compound
3b with chlorosulfonic acid yielded their corresponding sulfonyl
chloride derivative (4b) which was subsequently triturated with
ammonium carbonate to yield the sulfonamide derivative (4e). The
methyl sulfonamide derivative (4d) was obtained by methylation of
the sodium salt of compound 4b with methyl iodide in tetrahy-
drofuron as demonstrated in Scheme 2. The final compounds 5hej
were then synthesized from compounds 4d and 4e by reaction with
substituted aldehyde and urea/guanidine hydrochloride in the
presence of potassium carbonate and ethanol as solvent.
anti-inflammatory compound. The reduction of electron donating
features at R7 position in 4,5,6-triphenyl-1,2,3,4-tetrahydropyri
midine derivatives decrease the anti-inflammatory activity. How-
ever we found compound 5f with unsubstituted phenyl ring at R7
position showed similar anti-inflammatory activity as that of
compound 5c. Compound 5h with OCH3 group at R7 position and e
SO2CH3 group at R8 position was also found to show increased anti-
inflammatory activity after 3 h which continued up to 24 h. The
compounds 5c and 5f were further tested for COX-2 selectivity and
it was found from in vitro COX-2 assay that both compounds
showed good COX-2 inhibiting activity at 20 mM concentration with
minimal inhibition of COX-1 enzyme (Table 6).
2.4. Biological screening
3. Conclusion
Anti-inflammatory activity of the all synthesized compounds
was evaluated by carrageenan-induced rat paw edema model
(Table 5). The onset of action was evident during 1 h in various test
groups. All the tested compounds showed reasonable percentages
of reduction of edema up to 4 h. Among the tested compounds, 5c
and 5f showed highest percent inhibition of edema up to 4 h which
was comparable to percent inhibition of edema induced by cele-
coxib. It was observed from in vivo results that the presence of e
SO2CH3 at R9 position is important for anti-inflammatory activity
whereas compounds with eSO2CH3 at R8 position showed reduced
anti-inflammatory activity. The presence of electron donating
group (eN(CH3)2) at R7 position in compound 5c proves the pre-
diction of 3D QSAR model I that presence of combined phenyl ring
(hydrophobic features) with electron donating groups at R1 posi-
tion of 1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid derivatives
showed increased anti-inflammatory activity (Table 1). Thus in
synthesized series, the compound 5c was found to be more potent
The development of two 3D QSAR models, QSAR model I for
1,2,3,4-tetrahydropyrimidin-5-yl-acetic acid for in-vivo anti-
inflammatory activity and QSAR model II for 2-(4-sulfonylphenyl)
pyrimidines analogs for in-vitro COX-2 inhibitory activity has been
described with aim to screen designed 4,5,6-triphenyl-1,2,3,4-
tetrahydropyrimidine derivatives. The ten new compounds were
selected on the basis of activity predicted by both models, syn-
thesized and screened for their anti-inflammatory activity. The
compounds 5c and 5f were found to be potent with highest in vivo
anti-inflammatory activity. It was also found that presence of
electron donating moiety at R7 and SO2CH3 group at R9 position of
4,5,6-triphenyl-1,2,3,4-tetrahydropyrimidine derivatives is neces-
sary for anti-inflammatory activity. The compounds 5c and 5f
further showed comparable COX-2 inhibition with that of celecoxib.
The overall results of experimental studies thus suggested that
ligand based 3D QSAR study could be useful method for lead
optimization. The pharmacophoric features obtained from both 3D

238
D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
Table 4
data used for 3D QSAR studies was divided into a training set and a
test set in such a way that they contained information in terms of
both their structural features and biological activity ranges. The
most active molecules, moderately active, and less active molecules
were included in training set to spread out the range of activities
whereas the test compounds were selected in such a way that they
truly represent the training set. The structure of each compounds
were cleaned and optimized using Ligprep v2.4 (Schrödinger, LLC,
New York, NY, 2012).
Structures of selected designed compounds for experimental studies along with
their predicted activity.
Phase provide a built-in set of six pharmacophore features such
as hydrogen bond acceptor (A), hydrogen bond donor (D), hydro-
phobic group (H), negatively charged group (N), positively charged
group (P), and aromatic ring (R), defined by a set of chemical
structure patterns as SMARTS queries. Common pharmacophoric
features were then identified from a set of variants (set of feature
types) that define a possible pharmacophore using a tree based
partitioning algorithm with maximum tree depth of four with the
requirement that all actives must match. After applying default
feature definitions to each ligand, CPHs were generated using a
Comp. R7
R8
R9
R10 Predicted activity
QSAR model I QSAR model 2
5a
5b
5c
5d
5e
5f
e3,4-OCH3 eH
e2,5-OCH3 eH
e4-N(CH3)2 eH
e2,5-OCH3 eH
e2,4-OCH3 eH
eSO2CH3 eNH 0.74
eSO2CH3 eNH 0.52
eSO2CH3 eO 0.78
eSO2CH3 eO 0.47
eSO2CH3 eO 0.52
NPa
1.8
1.6
ꢀ
final box of 1 A. All generated CPHs were examined and selected
based on a scoring function to yield the best alignment of the active
ligands using an overall maximum Root Mean Square Deviation
1.82
1.82
1.4
1.51
NP
ꢀ
(RMSD) value of 1.2 A with default options for distance tolerance.
H
eH
eSO2CH3 eS
eSO2CH3 eS
0.52
0.54
eNH 0.73
eO 0.71
eO 0.5
The quality of alignment was measured by a survival score.
5g
5h
5i
e2,4-OCH3 eH
e4-OCH3
e4-N(CH3)2 eSO2CH3 eCl
e2,5-OCH3 eSO2NH2 eCl
Atom-based 3D QSAR models were developed using Partial
Least Squares (PLS) regression analysis. In atom-based 3D QSAR in
Phase, each molecule was treated as a set of overlapping Vander
Waals spheres. Each atom (and hence each sphere) was placed into
one of six categories according to a simple set of rules: hydrogens
attached to polar atoms were classified as hydrogen bond donors
(D); carbons, halogens, and CeH hydrogens are classified as
hydrophobic/non-polar (H); atoms with an explicit negative ionic
charge are classified as negative ionic (N); atoms with an explicit
positive ionic charge were classified as positive ionic (P); non-ionic
atoms were classified as electron-withdrawing (W); and all other
types of atoms were classified as miscellaneous (X). For Construc-
eSO2CH3 eCl
NP
1.69
5j
a
NP e not predicted.
QSAR models and structure activity relationship of experimental
studies will be useful further to optimize 1,2,3,4-tetrahydropy
rimidine scaffold.
4. Experimental studies
ꢀ
tion of atom-based 3D QSAR model, a rectangular grid of cubes (1 A
4.1. Generation of 3D QSAR model
on each side) were defined for aligned training set for occupation of
all atoms. Each occupied cubes were allotted one or more volume
bits to represent the molecules by string of zero and ones. This
representation gives rise to binary-valued occupation patterns that
Phase v3.3 (Schrödinger, LLC, New York, NY, 2012) implemented
in Maestro v9.2 (Schrödinger, LLC, New York, NY, 2012) was used for
the pharmacophore generation and 3D QSAR studies [6]. Biological
Scheme 1. Synthesis of compounds 5aeg.

D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
239
Scheme 2. Synthesis of Compounds 5hej.
was used as independent variables to create PLS QSAR models. The
PLS regression was carried out with maximum of N/5 PLS factors,
N ¼ number of ligands in training set.
dried over anhydrous sodium sulfate, filtered and concentrated to
give the title compound.
Yield (solid): 70.8%; M.P.: 161.3e163.1 ꢂC; FT-IR (neat) cmꢀ1
:
3008, 2962, 1680, 1270; 1H NMR (400 MHz, CDCl3):
d
¼ 3.23 (s, 3H),
4.26 (s, 2H), 7.20e7.32 (m, 6H), 7.97e8.03 (m, 3H); 13C NMR
4.2. Synthesis
(400 MHz, CDCl3):
d
¼ 40.80, 44.12, 117.43, 123.76, 127.28, 130.30,
132.45, 190.10; AP-MS: m/z ¼ 275.3 [M þ H]þ.
The purities of all the synthesized compounds have been
checked by thin-layer chromatography (TLC) using various non-
aqueous solvents. Melting points were determined on SRS OPTI-
MELT and were uncorrected. 1H NMR spectra and 13C NMR were
recorded on a Bruker DXM-400 spectrometer (400 MHz) with
CDCl3 as a solvent. Mass spectra were recorded on time of flight
mass spectrometer.
4.2.2. Synthesis of 1-(4-chlorophenyl)-2-(4-(methylsulfonyl)
phenyl)ethanone (4d)
1-(4-Chlorophenyl)-2-phenylethanone (3b) (0.05 mol) was
added slowly to chlorosulfonic acid (0.25 mol) at 10e15 ꢂC and
reaction mixture was stirred for about 18 h. The reaction mixture
then poured onto ice/water (200 ml). The product was extracted
with ether. The ethereal solution was washed with water, dried
over sodium sulfate and evaporated to give 4-(2-(4-chlorophenyl)-
2-oxoethyl)benzene-1-sulfonyl chloride (4b). To a stirred solution
of sodium sulfite (12.6 mmol) and sodium hydrogen carbonate
(13.56 mmol) in water (25 ml) was added the compound 4b
(9.03 mmol) in tetrahydrofuran (10 ml). The reaction mixture was
heated at 75 ꢂC for 2 h and cooled to 30 ꢂC and methyl iodide
(45.2 mmol) was added. After being stirred at 50 ꢂC for 24 h, the
reaction mixture was cooled to room temperature and partitioned
between water (50 ml) and ethyl acetate (100 ml). The aqueous
4.2.1. Synthesis of 1-(4-(methylsulfonyl)phenyl)-2-phenylethanone
(4a)
To a suspension of 1-(4-(methylthio)phenyl)-2-phenylethanone
(3a) (2.43 mmol) in acetone-water (2:1), Oxone (4.03 mmol) was
added and the mixture was stirred at RT for 2 h. After completion of
the reaction, acetone was removed under low vacuum and the
resulting mixture was diluted with cold water (25 ml). The mixture
was then extracted with ethyl acetate (3 ꢁ 25 ml). The organic layer
was collected, combined and washed with cold water (2 ꢁ 25 ml),

240
D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
Table 5
In vivo anti-inflammatory activity of compounds.
Treatmenta
Mean paw volume (ml) ꢃ SEMb
% Inhibition of edema
1 h
2 h
3 h
4 h
24 h
1 h
2 h
3 h
4 h
24 h
Control
5a
5b
5c
5d
5e
5f
5g
2.22 ꢃ 0.071
1.67 ꢃ 0.015
1.66 ꢃ 0.071
1.18 ꢃ 0.060
1.43 ꢃ 0.077
1.74 ꢃ 0.034
1.18 ꢃ 0.057
1.88 ꢃ 0.080
1.55 ꢃ 0.073
1.82 ꢃ 0.041
1.82 ꢃ 0.040
1.15
2.10 ꢃ 0.111
1.71 ꢃ 0.071
1.59 ꢃ 0.075
1.23 ꢃ 0.062
1.70 ꢃ 0.046
1.51 ꢃ 0.013
1.45 ꢃ 0.071
1.54 ꢃ 0.085
1.67 ꢃ 0.015
1.52 ꢃ 0.060
1.51 ꢃ 0.061
1.22
1.97 ꢃ 0.002
1.24 ꢃ 0.090
1.57 ꢃ 0.064
1.44 ꢃ 0.019
1.49 ꢃ 0.061
1.20 ꢃ 0.092
1.12 ꢃ 0.091
1.77 ꢃ 0.083
1.11 ꢃ 0.080
1.40 ꢃ 0.042
1.49 ꢃ 0.042
1.33
1.68 ꢃ 0.101
1.49 ꢃ 0.021
1.50 ꢃ 0.071
1.52 ꢃ 0.021
1.39 ꢃ 0.086
1.71 ꢃ 0.038
1.37 ꢃ 0.098
1.76 ꢃ 0.036
1.20 ꢃ 0.093
1.41 ꢃ 0.034
1.44 ꢃ 0.030
1.38
1.54 ꢃ 0.056
1.48 ꢃ 0.050
1.65 ꢃ 0.045
1.59 ꢃ 0.088
1.77 ꢃ 0.047
1.88 ꢃ 0.089
1.81 ꢃ 0.101
1.79 ꢃ 0.039
1.30 ꢃ 0.066
1.66 ꢃ 0.065
1.69 ꢃ 0.07
1.44
e
e
e
e
e
24.77
25.23
46.85
35.59
21.62
46.85
15.32
30.18
18.02
18.02
48.20
18.57
24.29
41.43
19.05
28.10
30.95
26.67
20.48
27.62
28.10
41.90
37.06
20.30
26.90
24.37
39.09
43.15
10.15
43.65
28.93
24.37
32.49
11.31
10.71
9.52
17.26
e
3.90
e
e
e
e
18.45
e
e
e
5h
5i
5j
28.57
16.07
14.29
17.86
15.58
e
e
Celecoxib
6.49
a
Compounds were administered at a dose of 20 mg kgꢀ1
n ¼ 6.
.
b
layer was then separated and further extracted with ethyl acetate
(2 ꢁ 80 ml). The combined extracts were then dried over anhydrous
Sodium sulfate, and the solvent was evaporated under vacuum to
give compound 4d.
4.2.4.1. 4-(3,4-Dimethoxyphenyl)-6-(4-(methylsulfonyl)phenyl)-5-
phenyl-3,4 dihydropyrimidin-2(1H)-imine (5a). Yield (solid): 69%;
M.P.: 97.2e99.7 ꢂC; FT-IR (neat) cmꢀ1: 3344, 3029, 2923,1260,1220,
1150; 1H NMR (400 MHz, CDCl3):
d
¼ 2.95 (s, 3H), 3.64 (s, 3H), 3.80
Yield (solid): 46.4%; M.P.: 157e159 ꢂC; FT-IR (neat) cmꢀ1: 3012,
(s, 3H), 5.14 (s, 1H), 6.67e7.05 (m, 5H), 7.26e7.44 (m, 7H), 7.65e7.67
2958, 1678, 1284; 1H NMR (400 MHz, CDCl3):
d
¼ 3.30 (s, 3H), 4.32
(d, 2H), 9.85 (s, 1H); 13C NMR (400 MHz, CDCl3):
d
¼ 44.42, 55.86,
(s, 2H), 7.12 (d, 2H), 7.38e7.41 (m, 4H), 7.93 (d, 2H); 13C NMR
76.71, 119.16, 128.35, 130.40; AP-MS: m/z ¼ 464.5 [M þ H]þ;
Elemental Anal. Calcd for C25H25N3O4S (463.55), requires (Found):
C 64.78 (64.77); H, 5.44 (5.41); N 9.06 (9.04).
(400 MHz, CDCl3):
d
¼ 41.57, 43.30, 119.24, 124.14, 127.56, 131.10,
133.15, 189.24; AP-MS: m/z ¼ 309.1 [M þ H]þ.
4.2.4.2. 4-(2,5-Dimethoxyphenyl)-6-(4-(methylsulfonyl)phenyl)-5-
4.2.3. Synthesis of 4-(2-(4-chlorophenyl)-2-oxoethyl)
benzenesulfonamide (4e)
phenyl-3,4-dihydropyrimidin-2(1H)-imine
69.91%; M.P.: 81.4e83.6 ꢂC; FT-IR (neat) cmꢀ1: 3360, 3015, 2880,
1258,1210,1134; 1H NMR (400 MHz, CDCl3):
(5b). Yield
(Solid):
4-(2-(4-chlorophenyl)-2-oxoethyl)benzene-1-sulfonyl chloride
(4b) (0.0525 mol) was grinded with ammonium carbonate in a
mortar until a fine uniform powder was obtained. The mixture was
heated in an evaporating dish on water bath for 1e2 h and stired
frequently with glass rod. The mixture was then Allowed to cool
and extracted with little cold water to remove the excess of
ammonium salts. The product obtained was then recrystallized
from ethanol.
d
¼ 2.97 (s, 3H), 3.71 (s,
3H), 3.77 (s, 3H), 5.60 (s, 1H), 6.76e6.91 (m, 5H), 7.03e7.26 (m, 5H),
7.53e7.55 (d, 2H), 7.71e7.73 (d, 2H), 10.44 (s, 1H); 13C NMR
(400 MHz, CDCl3):
d
¼ 44.49, 55.63, 76.72, 114.88, 128.13, 130.57,
153.92; AP-MS: m/z ¼ 464.5 [M þ H]þ; Elemental Anal. Calcd for
C25H25N3O4S (463.55), requires (Found): C, 64.78 (64.75); H, 5.44
(5.43); N, 9.06 (9.03).
Yield (solid): 73.6%; M.P.: 192e194 ꢂC; FT-IR (neat) cmꢀ1: 3410,
4.2.4.3. 4-(4-(Dimethylamino)phenyl)-6-(4-(methylsulfonyl)phenyl)-
5-phenyl-3,4-dihydropyrimidin-2(1H)-one (5c). Yield (solid): 51.4%;
M.P.: 80.1e82.9 ꢂC; FT-IR (neat) cmꢀ1: 3295, 3034, 2912, 1642, 1275,
3385, 3010, 2951, 1682, 1280; 1H NMR (400 MHz, CDCl3):
d
¼ 2.44
(s, 2H), 4.40 (s, 2H), 7.22e7.36 (m, 6H), 7.88 (d, 2H); 13C NMR
(400 MHz, CDCl3):
d
¼ 42.12, 119.30, 122.43, 128.35, 130.40, 134.50,
1145; 1H NMR (400 MHz, CDCl3):
d
¼ 3.29 (s, 6H), 3.36 (s, 3H), 5.77
(s, 1H), 7.27e7.33 (m, 8H), 8.02e8.10 (m, 5H), 8.26e8.28 (d, 2H); 13
NMR (400 MHz, CDCl3):
¼ 39.06, 56.28, 126.64, 129.22, 140.31;
AP-MS: m/z 448.2 [M
H]þ. Elemental Anal. Calcd for
25H25N3O3S (447.55); requires (Found): C, 67.09 (67.06); H, 5.63
(5.61); N, 9.39 (9.9.37).
191.20; AP-MS: m/z ¼ 310.2 [M þ H]þ.
C
d
¼
þ
4.2.4. General procedure for synthesis of final compounds (5aej)
A mixture of compound 4a/4d/4e (0.06 mol), urea/thiourea/
guanidine hydrochloride (0.06 mol), aldehyde (0.06 mol) and
K2CO3 (0.06 mol) in 100 ml ethanol was refluxed in oil bath for 8e
12 h. The completion of reaction was monitored on TLC. The re-
action mixture was then poured onto iceewater mixture and the
solid obtained was filtered. The product obtained was filtered,
dried and recrystallized from ethanol.
C
4.2.4.4. 4-(2,5-Dimethoxyphenyl)-6-(4-(methylsulfonyl)phenyl)-5-
phenyl-3,4-dihydropyrimidin-2(1H)-one (5d). Yield (solid): 52%;
M.P.: 62.5e64.0 ꢂC; FT-IR (neat) cmꢀ1: 3348, 3095, 2984,1632,1212,
1140; 1H NMR (400 MHz, CDCl3):
d
¼ 3.05 (s, 3H), 3.68 (s, 3H), 3.72
(s, 3H), 5.15 (s, 1H) 6.68e6.80 (m, 3H), 6.84e6.96 (m, 3H), 7.02e7.28
(m, 6H), 9.02 (s, 2H); 13C NMR (400 MHz, CDCl3):
d
¼ 45.12, 56.72,
77.18, 115.52, 128.24, 130.15, 140.78; AP-MS: m/z ¼ 465.4 [M þ H]þ.
Elemental Anal. Calcd for C25H24N2O5S (464.53); requires (Found):
C, 64.64 (64.61); H, 5.21 (5.19); N, 6.03 (6.00).
Table 6
In vitro COX-2 and COX-1 enzymes inhibition data.
Sr. no.
Compound
COX-2 inhibition (%)a
COX-1 inhibition (%)
1
2
3
5c
5g
Celecoxib
46.23 ꢃ 0.38
39.45 ꢃ 0.15
49.23 ꢃ 0.23
2.36
1.67
NIb
4.2.4.5. 4-(2,4-Dimethoxyphenyl)-6-(4-(methylsulfonyl)phenyl)-5-
phenyl-3,4-dihydropyrimidin-2(1H)-one (5e). Yield (solid): 51.6%;
M.P.: 84.3e84.1 ꢂC; FT-IR (neat) cmꢀ1: 3405, 3078, 2905,1640,1224,
a
Data are indicated as percentage of inhibition at 20
No inhibition obtained.
m
M ꢃ SEM.
1120; 1H NMR (400 MHz, CDCl3):
d
¼ 2.51 (s, 3H), 3.24 (s, 3H), 3.26
b

D.K. Lokwani et al. / European Journal of Medicinal Chemistry 73 (2014) 233e242
241
(s, 3H), 5.41 (s, 1H), 6.80e7.31 (m, 8H), 7.35e7.78 (m, 4H), 10.12 (s,
compounds at the same dose orally. All the suspensions for oral
dose were prepared in the vehicle mentioned above and adminis-
tered in a constant volume of 0.5 ml per rat. After 1 h of the
administration of the test compound and celecoxib, 0.1 ml of 1% w/
v suspension of carrageenan was injected in to the subplanatar of
left paw of control and test animals. Immediately, the paw volume
was measured using Plethysmometer (initial paw volume), there
after the paw volume was measured every 1 h till 4 h. The differ-
ence between initial and subsequent readings gave the edema
volume for the corresponding time. Percentage inhibition was
calculated.
2H); 13C NMR (400 MHz, CDCl3):
d
¼ 43.12, 55.38, 76.21, 126.54,
130.40, 144.31; AP-MS: m/z ¼ 465.4 [M þ H]þ. Elemental Anal.
Calcd for C25H24N2O5S (464.53); requires (Found): C, 64.64 (64.63);
H, 5.21 (5.20); N, 6.03 (6.01).
4.2.4.6. 6-(4-(Methylsulfonyl)phenyl)-4,5-diphenyl-3,4-
dihydropyrimidine-2(1H)-thione (5f). Yield (solid): 55.2%; M.P.:
117.6e118.8 ꢂC; FT-IR (neat) cmꢀ1: 3356, 3055, 2925, 1144, 1085; 1H
NMR (400 MHz, CDCl3):
d
¼ 2.68 (s, 3H), 5.28 (s, 1H), 6.77e6.78 (d,
2H), 7.04e7.32 (m, 8H), 7.34e7.49 (m, 4H), 7.79e7.87 (d, 2H); 13C
NMR (400 MHz, CDCl3):
d
¼ 43.77, 61.32, 115.16, 127.84, 129.54,
141.00; AP-MS: m/z ¼ 421.3 [M þ H]þ. Elemental Anal. Calcd for
4.3.2. In vitro cyclooxygenase (COX) inhibition assays
C
23H20N2O2S2 (420.55); requires (Found): C, 65.69 (65.53); H, 4.79
The assay was performed using colorimetric COX (ovine) in-
hibitor screening assay kit (Cayman chemical, MI, USA). The assay
utilizes the peroxidase activity of ovine cyclooxygenase to oxidize
the colorimetric substrate, N,N,N0,N0-tetramethyl-p-phenylenedi-
amine (TMPD). Enzyme assays were performed with total volume
(4.65); N, 6.66 (6.54).
4.2.4.7. 4-(2,4-Dimethoxyphenyl)-6-(4-(methylsulfonyl)phenyl)-5-
phenyl-3,4-dihydropyrimidine-2(1H)-thione (5g). Yield (solid):
54.2%; M.P.: 84.0e86.1 ꢂC; FT-IR (neat) cmꢀ1: 3345, 3025, 2943,
of 220 ml. The mixture in background wells, 100% initial activity
1223, 1134, 1074; 1H NMR (400 MHz, CDCl3):
d
¼ 2.68 (s, 3H), 3.87
wells and inhibitor wells were prepared according to the in-
structions provided by the manufacturers and preincubated for
(s, 3H), 3.90 (s, 3H), 5.86 (s, 1H), 7.17e7.49 (m, 6H), 7.51e7.80 (m,
6H), 10.28 (s, 2H); 13C NMR (400 MHz, CDCl3):
d
¼ 44.40, 55.48,
5 min at 25 ꢂC. The reaction was initiated by addition of 20
ml of
77.04, 124.10, 128.86, 140.82; AP-MS: m/z ¼ 481.2 [M þ H]þ.
Elemental Anal. Calcd for C25H24N2O4S2 (480.60); requires (Found):
C, 62.48 (62.33); H, 5.03 (4.95); N, 5.83 (5.74).
TMPD solution followed by 20
ml of arachidonic acid in all the wells.
The assay mixture was mixed thoroughly and incubated at 25 ꢂC for
5 min. The enzyme activity was determined by measuring absor-
bance at 590 nm in a microplate reader.
4.2.4.8. 6-(4-Chlorophenyl)-4-(4-methoxyphenyl)-5-(4-(methyl-
sulfonyl)phenyl)-3,4-dihydropyrimidin-2(1H)-imine
(solid): 64.1%; M.P.: 122.0e124.1 ꢂC; FT-IR (neat) cmꢀ1: 3395, 3043,
2958, 1215, 1130; 1H NMR (400 MHz, CDCl3):
(s, 3H), 5.51 (s, 1H), 7.24e7.31 (m, 7H), 7.42e7.49 (m, 5H), 8.75e8.78
(d, 2H),10.31 (s,1H); 13C NMR (400 MHz, CDCl3): 39.21, 55.84, 76.91,
112.80, 124.99, 134.55, 153.21; AP-MS: m/z ¼ 468.3 [M þ H]þ.
Elemental Anal. Calcd for C24H22ClN3O3S (467.11); requires (Found):
C, 61.60 (61.56); H, 4.74 (4.65); N, 8.98 (8.84).
(5h). Yield
Acknowledgments
d
¼ 3.29 (s, 3H), 3.67
The authors are thankful to University Grant Commission (UGC),
New Delhi for financial assistance. The authors are also thankful to
the Head, Department of Chemical Technology, Dr. Babasaheb
Ambedkar Marathwada University, Aurangabad 431004 (MS), India
for providing the laboratory facility.
Appendix A. Supplementary data
4.2.4.9. 6-(4-Chlorophenyl)-4-(4-(dimethylamino)phenyl)-5-(4-
(methylsulfonyl)phenyl)-3,4-dihydropyrimidin-2(1H)-one
Yield (solid): 61.2%; M.P.: 108.2e110.0 ꢂC; FT-IR (neat) cmꢀ1: 3380,
3058, 2930,1635,1256,1138; 1H NMR (400 MHz, CDCl3):
(5i).
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.ejmech.2013.10.083.
d
¼ 2.79 (s,
6H), 3.09 (s, 3H), 5.39 (s, 1H), 7.02e7.18 (m, 4H), 7.22e7.42 (m, 4H),
7.90e7.96 (m, 4H), 9.78 (s, 2H); 13C NMR (400 MHz, CDCl3): 40.12,
56.82, 123.12, 132.56, 141.10; AP-MS: m/z ¼ 482.1 [M þ H]þ.
References
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P. Isakson, Pharmacological and biochemical demonstration of the role of
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(1994) 12013e12017.
Elemental Anal. Calcd for
C25H24 ClN3O3S (481.12); requires
(Found): C, 62.30 (62.26); H, 5.02 (4.96); N, 8.72 (8.66).
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4.2.4.10. 4-(6-(4-Chlorophenyl)-4-(2,5-dimethoxyphenyl)-2-oxo-
1,2,3,4-tetrahydropyrimidin-5-yl)benzenesulfonamide
(solid): 51.2%; M.P.: 105.8e107.1 ꢂC; FT-IR (neat) cmꢀ1: 3375, 3284,
3032, 2956,1638,1219,1129; 1H NMR (400 MHz, CDCl3):
(5j). Yield
d
¼ 2.98 (s,
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