Synthesis, in vitro potential and computational studies on 2-amino-1, 4-dihydropyrimidines as multitarget antibacterial ligands

Article abstract of DOI:10.1007/s00044-016-1613-z

In this study, we have investigated small multitargeted molecules containing 2-aminopyrimidine scaffold that may further act as precursor for developing more potent antibacterials. An efficient route to 2-amino-1,4-dihydropyrimidines by using ultrasound i

Full text of DOI:10.1007/s00044-016-1613-z

MEDICINAL
CHEMISTRY
RESEARCH
Med Chem Res
DOI 10.1007/s00044-016-1613-z
ORIGINAL RESEARCH
Synthesis, in vitro potential and computational studies on 2-amino-1,
-dihydropyrimidines as multitarget antibacterial ligands
4
1 ●
2 ●
3 ●
Muhammad Jawad Ahmad Syed Fahad Hassan Riffat Un Nisa
3
4 ●
5 ●
●
Khurshid Ayub Muhammad Shahid Nadeem Samina Nazir
Farzana Latif Ansari Naveeda Akhtar Qureshi Umer Rashid
6 ●
7 ●
1,3
Received: 24 November 2015 / Accepted: 12 June 2016
©
Springer Science+Business Media New York
Abstract In this study, we have investigated small multi-
targeted molecules containing 2-aminopyrimidine scaffold
that may further act as precursor for developing more potent
antibacterials. An efficient route to 2-amino-1,4-dihy-
dropyrimidines by using ultrasound irradiation as the
energy source was developed. In silico density functional
theory calculations illustrated that tin chloride-mediated
Biginelli reaction to produce 2-amino-1,4-dihydropyr-
imidines has energetics quite accessible under the reaction
conditions. Calculated minimum inhibitory concentrations
against the various bacterial strains showed that compounds
potency in Escherichia coli strains. Further, we investigated
in silico ADMET profiling of synthesized compounds in
order to understand the mechanism of action that help in
explaining in vitro results. Lead compounds 3, 6, and 11 are
predicted to have acceptable pharmacokinetic/drug-like
properties. Data mining and computational analysis were
employed to derive compound promiscuity phenomenon.
All the compounds were found nonsubstrate towards var-
ious aminergic G-protein coupled receptors, ion-channels,
kinase inhibitor, nuclear receptor ligand, protease inhibitor,
and enzyme inhibitor. Compound 3 was further investigated
by in silico binding to different antibacterial targets. Bind-
ing energy data revealed that that these compounds have the
ability to bind with other bacterial targets. Hence, combined
in silico and in vitro studies shed insights into the
mechanism of synthesis and antibacterial activity of
3
and 11 displayed comparable in vitro activity to cipro-
floxacin in Staphylococcus aureus strains and reduced
Electronic supplementary material The online version of this article
(
doi:10.1007/s00044-016-1613-z) contains supplementary material,
2-amino-1,4-dihydropyrimidines. Results of this study are
which is available to authorized users.
promising and can be used for further investigation by
medicinal chemists to explore their chemical functionali-
zation and in vivo studies.
*
Umer Rashid
umer_rashid39@hotmail.com
umer.rashid@ciit.net.pk
1
2
3
4
5
6
7
Keywords 4-Arylated-2-aminopyrimidines Ultrasound
irradiation Dihydrofolate reductase Promiscuity binding
Density functional theory
●
Department of Chemistry, Hazara University, Mansehra, 21120,
Pakistan
●
●
●
Department of Pharmacy, The University of Lahore, Defense
Road Campus, Lahore, 53700, Pakistan
Department of Chemistry, COMSATS Institute of Information
Technology, Abbottabad, 22060, Pakistan
Department of Biochemistry, King Abdulaziz University, Jeddah,
Saudi Arabia
Introduction
Nanosciences & Catalyst Division, National Center for Physics,
Quaid-i-Azam University Campus, Islamabad, 44000, Pakistan
Resistance to current antimicrobial drugs has certainly
increased the global health concern. Bacteria have the
capacity to render all current treatments ineffective, which
create problems for medicinal chemists to develop new
antimicrobial agents. In recent years, the main focus of drug
Department of Chemistry, Quaid-i-Azam University, Islamabad,
4
5320, Pakistan
Department of Animal Sciences, Quaid-i-Azam University,
Islamabad, 45320, Pakistan

Med Chem Res
design and discovery has shifted away from one target-one
disease paradigm, and most of the strategies are now aimed
to develop drugs that can modulate multiple targets in
parallel fashion. These multitargeted treatments, referred as
pharmacological promiscuity, preclude rapid drug resis-
tance against the infectious diseases and inflammation
direct impact on potency (Ákos and Gyorgy, 2013; Haupt
et al., 2013).
Pyrimidines have a diverse range of pharmacological
applications and are found in numerous biologically active
natural products and drug candidates. 2-aminopyrimidine, a
guanidine-containing six-member heterocyclic structural
subunit, is contained in growing number of drugs such as
Rosuvastatin, imatinib (gleevec), sulfadiazine, and tri-
methoprim (Lagoja, 2005; Watanabe et al., 1997; Capdeville
et al., 2002). Trimethoprim (TMP) is a small drug molecule
containing 2-aminopyrimidine scaffold (Fig. 1). TMP was
initially considered as an antimalarial agent, but now con-
sidered as highly effective against bacterial infections,
especially in synergistic combination with sulfamethox-
azole (Co-trimoxazole). TMP binds to dihydrofolate
reductase (DHFR), and its affinity for bacterial DHFR are
thousands times greater than human DHFR (Brogden et al.,
1982).
We have previously synthesized and reported a set of
2-aminopyrimidines after our structure-based virtual screen-
ing experiment (Rashid et al., 2013). Our recent effort
towards the synthesis of 2-aminopyrimidine derivatives
through a multistep protocol provides the topic of this paper
(Rashid et al., 2015). The purpose of this study is to syn-
thesize small molecules containing 2-aminopyrimidine
scaffold, which may further act as a precursor for devel-
oping more potent molecules. As a starting point, we carried
out docking studies on our previously reported set of
2-amino-1,4-dihydropyrimidines. Surprisingly, we found a
resemblance in the fitting-in mechanism of the two com-
pounds with TMP. From the molecular docking study, it
was revealed that these compounds have the ability to act as
potential antibacterial agents. With these results in hands
and in continuation of our endeavor and considering the
pharmacological importance of the 2-amino-3,4-dihy-
dropyrimidine scaffold, it was planned to design and syn-
thesize a variety of 2-amino DHPMs via one-pot Biginelli
reaction. Mechanistic analysis of acid-catalyzed reaction
was also performed by using density functional theory
(
Stephen and Lynn, 2013). Interaction between the ligands
and their targets plays a vital role in the identification and
discovery of new drugs and their targets. In silico approa-
ches to predict drug-target interactions and ADMET pro-
filing at design stage provides significant insights to identify
lead compounds.
It is well recognized that due to the laborious and costly
experimental process of drug-target interaction prediction,
computational ADMET in combination with in vitro pre-
diction (Docking studies) as early as possible in the drug
discovery process helps us in weeding out of poor drug
candidates prior to laborious and costly experimental pro-
cesses. The main objective of the computational ADMET
property modeling is the prediction of the in vivo pharma-
cokinetics of a new potential drug molecule in man, while it
exists as only a virtual structure. Molecular properties and
chemical structure have a key impact on the efficacy and
safety of drug candidate and therefore, attracted consider-
able interest in recent years. An insight into the property-
promiscuity relationship at the earliest phase of drug
discovery can be useful for drug optimization. Over the last
1
0 years, the investigations are mainly focused on physi-
cochemical properties such as lipophilicity (calculated by
logP), molecular weight (MW), total polar surface area
(
TPSA) and basic character (pKa). The relation of MW to
the ADMET (absorption, distribution, metabolism, excre-
tion, and toxicity) features, promiscuity, and off-target
interaction is very important since molecules with high MW
possess more features to interact with a receptor. Lipophi-
licity is a principal determinant of promiscuity. A com-
pound with high lipophilicity is usually more promiscuous
than a compound with low logP since it effects membrane
permeability, solubility, and thus bioavailability with a
Fig. 1 Optimized geometries of
Int-1 and TS1. All bond
distances are in Å

Med Chem Res
(
DFT) calculations. We also explored by computational
studies that the rate limiting step is nucleophilic addition of
means the promiscuity phenomenon of these synthesized
compounds.
urea on the electron-deficient carbon of aldehyde (Kappe,
1997). In our study, we have used SnCl as a Lewis acid
2
catalyst for Biginelli reaction of guanidine with aldehyde
and 1,3-dicarbonyl compounds. We report here detailed
DFT calculation pertaining to this reaction.
Results and discussions
Chemistry
Coordination of benzaldehyde with SnCl2 and con-
comitant interaction with guanidine generated a “V”-shaped
intermediate (Int-1) on Sn. The Cl–Sn–Cl angle is 96.67°
and the O-Sn bond distance is 2.25 Å. The chlorides on Sn
played an important role to hold the guanidine moiety in
close proximity (through dipole-dipole type interactions) of
benzaldehyde for nucleophilic attack. Cl–H1 and Cl–H2
bond distances are 2.57 and 3.15 Å respectively (Fig. 1). A
transition state for nucleophilic attack of guanidine on
As literature reveals that 2-amino-3,4-dihydropyrimidines
are best synthesized in the presence of a base as a catalyst,
we initiated our investigation by employing various condi-
tions, including classical Biginelli conditions (SnCl .2H O
2
2
as a catalyst) or modified Biginelli conditions (NaHCO ). A
3
set of fifteen 4-arylated-2-amino-pyrimidine (1–15) has
been synthesized by using a variety of aldehydes, guanidine
HCl, and 1,3-dicarbonyl compounds (Scheme 1).
It is well known that sonication results in acceleration of
the reaction rate and good yield in many chemical reactions
−1
benzaldehyde is located at a barrier of 9.43 kcal mol . The
N–C bond distance in the transition state is 1.93 Å which
reduced to 1.66 Å in the product, i.e. Int-2. This indicated a
late transition state. Moreover, the reaction was endother-
mic, which is consistent with the late nature of the transition
state. Int-2 was a zwitterionic species which after a proton
shuffle generates another intermediate (Int-3) which was of
comparable energy to Int-2.
(
Mason and Lorimer, 2002; Cravotto and Cintas, 2006). In
search of best reaction conditions for the synthesis of 2-
amino-1,4-dihydropyrimidine, ultrasound-assisted reaction
of guanidine HCl with benzaldehyde and ethyl acetoacetate
affording 1 was selected as model reaction (in supplemen-
tary Data). During this initial study, various conditions,
including classical Biginelli conditions (SnCl . 2H O as a
The Int-3 undergoes conformational changes to form
-1
Int-3′ with 5.08 kcal mol higher in energy on the potential
energy surface than Int-3. This higher energy of Int-3′ may
be explained on the basis of nonbonded interactions. In Int-3,
chlorides on stannous were interacting with the hydrogen on
guanidine part, whereas in Int-3′, the chlorides were in
interaction with ortho protons of the phenyl ring. Dipole-
dipole interactions of halides with NH protons are much
2
2
catalyst) and modified Biginelli conditions (NaHCO ) were
3
employed. To find the specific effect of ultrasound, this
reaction was also carried out under the same conditions in
the absence of ultrasound irradiation. The results are sum-
marized in Table S-1 (in supplementary Data).
2
stronger than the interactions with sp CH hydrogen.
Reaction mechanism analysis using DFT calculations
Moreover, nitrogen in Int-3 also coordinated with tin,
whereas this type of interaction was absent in Int-3′
(Fig. 2). This explains the difference in energies of different
conformers of Int-3. Int-3′ was obtained through intrinsic
reaction coordinate calculations on the transition state for
In the next step, we performed DFT calculations for the
detailed mechanistic analysis of this reaction. For the clas-
sical, acid-catalyzed Biginelli reaction, Sweet proposed a
mechanism where Aldol condensation of ethyl acetoacetate
and aryl aldehyde was the rate limiting step (Sweet and
Fissekis, 1973). However, in 1997, Kappe and coworkers
illustrated through nuclear magnetic resonance (NMR)
the cleavage of the hydroxyl group mediated by SnCl . The
2
difference in energies between Int-3 and Int-3′ did not
affect the activation barrier for the cleavage of the hydroxyl
group mediated by SnCl (the next step).
2
Scheme 1 Synthesis of 4-
arylated-2-aminopyrimidine
R1
R1
CHO
O
NaHCO , DMF
3
O
2
R2
N
NH .HCl
USI
2
R2
+
R3
N
NH2
H N
NH
2
H
R3
O
1
3
(1-15)

Med Chem Res
Fig. 2 Optimized geometries of
Int-3 and Int-3′, the difference
in energies is due to difference
in nonbonding interactions
Fig. 3 Energy profile of
SnCl2
NH
nucleophilic attack on Int-1 and
subsequent cleavage of OH to
give Int-4. All energies are in
HO
-1
18.33
TS2
kcal·mol relative to Int-1 and
include unscaled zero point
correction
H
NH
H N
SnCl2
H
2
O
TS-2
NH2
15.0
Int-3'
NH
9
10.35
H N
2
9.92
Int-3
.53
9
.43
Int-4
Int-2
TS-1
SnCl2
NH2
O
SnCl2
HO
H
H
NH
N
0
.0
H
H N
2
NH
Int-1
H N
2
SnCl2
O
NH2
NH
SnCl2
NH
HO
H
H N
2
H
NH
H N
2
Int-3
A transition state for tin chloride-mediated cleavage of
hydroxyl group to generate iminium species was located at
Coordination of ethyl acetoacetate (methyl acetoacetate
was taken to reduce the computational cost) with Int-4, and
the loss of a water molecule generated an intermediated Int-5.
Nucleophilic attack of methyl acetoacetate on iminium
species to make C–C bond was both kinetically and ther-
modynamically a favorable process. The C–C bond
−1
a barrier of 3.33 kcal mol from Int-3′. The cleavage of
hydroxyl group to generate iminium species was a ther-
modynamically favorable process where the product (Int-4)
−1
lies 4.65 kcal mol lower in energy than Int-3′ (Fig. 3).

Med Chem Res
SnCl2
O
In vitro results vs in silico molecular properties:
correlations and predictions
O
Pyrimidine nucleus is an integral part of DNA and RNA and
is vital in several biological processes and has significant
chemical and pharmacological importance. The anti-
bacterial activity data are tabulated in Table 1. It is evident
from Table 1 that some analogues were found to have
comparable potency to the standard drug ciprofloxacin.
Compounds 3, 6, and 11 are most potent for all bacterial
strains.
OCH3
H
N
SnCl2
O
H
O
NH
6.59
H N
2
H
OCH3
NH
N
H
Focusing on the importance of permeation through bac-
terial cell membrane, molecular descriptors like n-octanol-
water partition co-efficient (Log P), Log D at various phy-
siological pH, molecular weight of the compound, and
permeability of cell membrane (LogPer) were computed to
determine the absorption of compounds. Aqueous solubility
of a compound is another important factor linked to drug
absorption (Waterbeemd and Gifford, 2003; Johnson and
Zheng, 2006). Hence, the solubility of compounds was also
calculated as logS via MOE software and then converted to
mg/mL. The logD value at various physiological pH of the
gut was computed by using ChemAxon software, and their
results are shown in Table 2. The results suggest that
compound 3 with high log P (5.098) and LogPermeability
(−5.239) can be efficiently absorbed through bacterial cell
membrane (Table 2). Table 2 shows the predicted values of
solubility of compounds (Sw) and it is clear that despite low
solubility value for compound 3 (0.0021 mg/mL), more
than 50 % bioavailability of compound 3 was predicted due
to its improved logD7.4 and molecular weight distribution
(Waring, 2009; Hansen et al., 2006). Reduced logD values
of compounds 6 and 11 in the stomach (pH 1.5) correspond
to improved solubility. In contrast, the increasing trend of
logD values in the intestine is due to increased logP values
at pH 6.8. Likewise, all the other compounds can be
administered via intravenous route for optimum bioavail-
ability and therapeutic efficacy.
H N
2
0
.0
-
1.53
Int-5
Int-6
SnCl2
O
O
OCH3
H
-
8.74
N
H
Int-7
NH
H N
2
Fig. 4 Energy profile for the formation of aminopyrimidine from Int-5.
−
1
All energies are in kcal mol relative to Int-5 and include unscaled
zero point correction
formation was achieved through a kinetic barrier of
.59 kcal mol whereas the process was exothermic by
.53 kcal mol (Fig. 4). This observation of low kinetic
−
1
6
1
−
1
barrier for this step was consistent with the experimental
evidence through NMR by Kappe and coworkers that
nucleophilic attack of urea (guanidine in this case) on
benzaldehyde is the rate limiting step. Our calculations
clearly illustrated that the nucleophilic attack of guanidine
on benzaldehyde has a kinetic demand of 9.43 kcal mol
whereas the reaction of methyl acetoacetate with the
iminium species requires only 6.59 kcal mol to surpass the
barrier.
−
1
The distribution of drug, measured as volume of dis-
tribution (V ), has a direct relationship with physicochem-
d
−
1
ical descriptors (Smith et al., 1996). Plasma protein binding
(PPB), molecular weight, lipophilicity, and pKa value are
the important factors affecting distribution of drug from
plasma to target tissues. Compounds with logD > 3 and
molecular weights in the range of 500–700 Da were asso-
ciated with high PPB (90–98 %) (Waterbeemd et al., 2001;
Gleeson, 2008). The computed pKa of our designed com-
pounds (depicting basic character and reduced logD values)
conferred them to be well distributed in the tissues in
contrast to plasma protein and thus have higher values of
Vd. This was further supported by azithromycin, exhibited
Int-6 undergoes another nucleophilic attack by guani-
dino nitrogen on the keto carbon to generate Int-7, which
−
1
lies 7.21 kcal mol lower in energy than Int-6. Finally,
loss of a water molecule would deliver the final product. In
short, our calculations clearly illustrated that tin chloride-
mediated Biginelli reaction to produce amino pyrimidines
has energetics quite accessible under the reaction conditions
(
70 °C). The computed energies (Total, Zero Point
Corrected, and Gibbs-free energies) and Cartesian coordi-
nates of the optimized geometries are given in supplemen-
tary Data.
higher V of 31.1 L/kg due to its basic pKa (8.74 at 25 °C)
d
(Stopher et al., 1988). As a result, it pertained long-lasting

Med Chem Res
1
2
3
a
Table 1 Antibacterial activity
No.
R
R
R
MIC values (µg/mL)
of 2-amino-1,4-DHPMs
Gram positive
Gram negative
S. aureus
B. subtilis
E. coli
S. typhi
1
2
3
4
5
6
7
8
9
H
OEt
Me
Me
Me
Ph
19.95
34.67
8.21
25.24
45.11
14.58
24.64
29.81
15.97
69.74
55.19
59.74
20.37
19.45
34.77
29.94
54.55
45.44
8.74
15.12
56.68
10.11
19.47
20.43
9.98
40.37
61.24
25.11
34.47
40.28
25.44
80.41
90.61
75.47
40.14
15.11
60.14
54.71
84.86
65.19
8.53
H
H
Ph
H
OEt
OEt
OEt
OEt
OEt
Me
OEt
OEt
OEt
Me
Me
Me
Me
OEt
Me
Me
Me
Me
24.95
20.12
14.26
49.68
39.52
54.81
14.79
8.38
4-OMe.C
6
H
4
6
2-Cl.C H
4
3-OMe, 4-OH C
4-OH C
3-O Me,4-OH C
6
H
3
3
64.87
64.84
60.39
15.17
10.46
50.24
14.81
59.41
39.15
5.27
6 4
H
6
H
1
1
1
1
1
1
1
a
0
1
2
3
4
5
6
4-Cl.C
4-Cl.C
6
H
H
4
OEt
OEt
OEt
Me
6
4
3-OH.C
6
H
4
35
3-CH .C
3
6
H
4
25.24
40.17
24.89
8.62
3,4-di OMe. C
3,4-di OMe. C
Ciprofloxacin
6
H
H
3
3
Me
6
OEt
Average of three readings
MIC minimum inhibitory concentration
effects and reduced dosing frequency (once a day) as a
positive outcome in clinical prescribing (McFarland et al.,
compounds to fetus environment and ameliorates the safety
criteria for designed/synthesized compounds as obvious
from literature (Pacifici and Nottoli, 1995; Reynolds and
Knott, 1989). Increased log P and improved logPer of
comounds 3, 6, and 11 have direct effect with reduced MIC
values against all the strains of bacteria (Fig. 5). Due to
neutral charge and reduced log P values, all compounds had
the ability to enter the bacterial cytoplasm and even to cross
nuclear envelope.
1
997). S. aureus is responsible for about 20–25 % the most
common cause of endocarditis that is often associated with
the i.v. drug abuse. This is already being treated with the
administration of aminoglycosides such as amikacin (V =
d
24 L/kg and pKa = 9.79) for 3–6 weeks. Furthermore, mer-
openem being prescribed for the management of acute
pancreatitis for 10–14 days therapy also has basic pKa of
9
.39 and has bactericidal effect against gram-positive and
Propensity towards the P-glycoprotein (P-gp) efflux
transporter was computed and used as a criterion to predict
central nervous system (CNS) penetration. The results
suggest that all the compounds were found to be less sub-
strate at P-gp efflux transporter due to their reduced
MW < 400 Da, logP < 5, hydrogen bond donor (HBD)
count and increased basic pKa values (Table 2). However,
gram-negative bacteria. Encouragingly, the percentage of
unbound drug present in the plasma for compound 3 (34.94
%
2
) revealed its sustained action in the body (Yang et al.,
012). Furthermore, increased logP of 5.098 and highest
predicted LogPer (−5.239) may further compel the com-
pound 3 to pass through deep aprotic environments and
enter various gram-negative strains of bacteria. This was
further proved by our in vitro results against various gram-
positive and gram-negative strains of bacteria with potent
minimum inhibitory concentration (MIC) values as shown
in Table 1/Fig. 5. Administration of drug to pregnant
women is a critical scenario as distribution and entrance of
compounds into placenta may aggravate fetus deformities.
For this, the designed compounds should not cross the
placental barrier of pregnant women. Increased pKa of all
the compounds, i.e., >6 further negates the entry of
2
slightly increasing TPSA > 90 Å for compounds 5, 7, 8, 9,
12, and 15 may increase the liability towards the ATP gated
efflux transporter and reduce the CNS penetration to minor
extent as shown in Fig. 6. Negative logD values may reduce
the blood brain barrier (BBB) penetration of synthesized
drug entities. Compounds 3, 6, and 11 exhibit good BBB
penetration due to their logD values ranging from 0 to 3.
Likewise, compounds having sum of nitrogen and oxygen
(N+O) < 5 (in some studies <6) and the logP − [N+O] > 0
are more likely to penetrate the BBB (Norinder and

Med Chem Res
Bergström, 2006). Therefore, compounds 5, 7, 9, and 15
do not exhibit high BBB penetration. The literature
example of antibiotic exhibiting good CNS penetration is
chloramphenicol with logD7.4 = 0.66, logP = 0.88, MW
=
323.129 and TPSA = 115.38 (Yogev et al, 1981). In all
the correlations,
compounds 6 and 11 were only liable to enter CNS and
cross BBB efficiently than other compounds. Although in
the conditions like meningitis or encephalopathy where
the number of perforations in brain blood vessels is
increased, compounds with poor CNS penetration can
enter the CNS to treat the brain infections. Compounds
with MW < 300 Da (except compounds 3, 5, 6, 7, 11, and
15) were predicted to cross BBB via trans-cellular path-
way squeezing along the junctions of BBB.
After absorption of the drug following oral adminis-
tration, the drug becomes available to the liver via portal
vein. Major portion of the drug is metabolized here to its
oxidized form or conjugated and termed as first-pass
metabolism. Therefore, the prefect strategy to protect the
drug entity from the first-pass effect is to either modify
the metabolic “soft spot” on the molecule that is more
liable to oxidation or change the route of administration.
The oxidations are driven by the presence of hepatic
microsomal isoforms of cytochromes-P450 enzymes.
Besides, the function of the gut-wall CYP3A4 and P-gp to
act in the synergic way to control absorption of their
substrates is highlighted repeatedly in the literature
(Hebert, 1997). Reduced liability of our designed com-
pounds to P-gp transporter complied with the reduced
liabilities towards the CYP3A4 isoform of the liver and
gut. Furthermore, specie difference exists between phase-
II metabolism reactions in humans and preclinical animals
like Guinea pigs that have an unusual high capacity for
methylation as compared to that in humans (Williams,
1978). Low HBD count may assure decreased phase-II
metabolism for all the compounds (Proudfoot, 2005).
Moreover, all compounds have fewer tendencies to
eliminate via bile canaliculi and may not opt to eliminate
via fecal route due to their reduced propensity towards
P-gp. Furthermore, reduced logD values of compounds
were responsible for decreased metabolic clearance
(
(
except compound 3) as obvious from the literature
Smith et al., 1996).
Excretion via renal corpuscle is solely responsible for
most of the compounds as they have MW < 350 Da
Egan, 2010). Compound 3 may partially excrete via renal
(
route and partially via fecal route (Smith, 1997). The
fraction of compounds 3, 6, and 11 being excreted via
kidney can be reabsorbed from the distal parts of the
nephron due to their increased logP values (5.098, 3.125,
and 3.127 respectively). Moreover, as S. aureus is mostly
concerned with inducing toxic shock syndrome, these

Med Chem Res
Fig. 5 Correlation between logP values and antibacterial activity
CNS Penetration Critera
potassium channel (Pearlstein et al., 2003). hERG potas-
sium channel is associated with electrical activity of
heart that coordinates with heart’s beating and its inhibition
leads to major consequences of prolonged QT-syndrome
provoking cardiac arrhythmia and sudden death. While
highlighting the importance of human immune-deficiency
virus, the protease inhibition potential was additionally
computed by utilizing the free online programming of
molinspiration. The more positive E-values direct the pro-
neness of compound to be liable to the specific receptor.
However, the negative E-values ensured the safety predic-
tion towards specific receptor family as toxicological point
of view. The overall toxicity of all compounds against
diverse receptor families, required for the normal func-
tioning of the body, was found safe as shown by the
negative values in Table 3. These results were further found
in accordance with the charge distribution on individual
chemical entity. As compounds bearing positive charge are
more likely to be the substrate at aminergic GPCRs and
various other off-target receptors that may confiscate the
drug to enter the market, as obvious from the recent study
(Peters et al., 2012).
4
3
3
2
2
1
1
00
50
00
50
00
50
00
5
0
0
0
20
40
60
80
100
120
TPSA A2
Fig. 6 Estimation of blood brain barrier penetration for designed
compounds
compounds could be considered important against bacterial
strains in vaginal regions of women. As all the compounds
are weak bases and have pKa in the range of 8.94–10.85,
hence, will tend to secrete in the lacteal secretions of
women and may treat the invading bacteria, i.e. S. aureus.
G-protein coupled receptors (GPCRs) and various pro-
tein kinases are among the two largest target families that
are linked frequently with promiscuity. They are also highly
safety-relevant. Further, the compounds being prone to
the serotonergic receptor type 5-HT2B may elevate the
heart valve damage (Hutcheson et al., 2011). These seven
transmembrane helical proteins preferably bind to the
basic compounds; therefore, liabilities of synthesized com-
pounds towards these GPCRs were assessed (Table 3).
The bioactivity analysis for all compounds against GPCRs to
act as ligand, ion channel modulator, protease inhibitor, kinase
inhibitor, enzyme inhibitor, and nuclear receptor ligand
were ruled out (Table 3). The importance of ion channels
in medicinal chemistry point of view relates with the inhi-
bition of human Ether-à-go-go Related Gene (hERG)
These above-mentioned results of in vitro antibacterial
activity, computational pharmacokinetics, and toxicology
studies suggest that these synthesized small molecules can be
used as good starting point for further chemical functionali-
zation and designing of new 2-aminopyrimidine derivatives.
In silico promiscuity binding
In an attempt to gain insights and to explore the probable
binding modes of synthesized compounds, we extended our

Med Chem Res
Table 3 Bioactivity predictions
and liabilities of designed
Compd. GPCR
ligand
Ion channel
modulator
Kinase
inhibitor
Nuclear
receptor ligand inhibitor
Protease
Enzyme
inhibitor
compounds towards various
G-protein coupled receptors
1
2
3
4
5
6
7
8
9
1
1
1
1
1
1
−0.58
−0.82
−0.19
−0.41
−0.39
−0.39
−0.43
−0.46
−0.42
−0.52
−0.37
−0.47
−0.76
−0.57
−0.44
−0.06
−0.24
−0.15
−0.11
−0.18
−0.15
−0.11
−0.01
−0.09
−0.07
−0.12
−0.02
−0.31
−0.29
−0.15
−1.09
−1.26
−0.49
−0.71
−0.65
−0.79
−0.84
−0.94
−0.86
−1.02
−0.68
−0.96
−1.18
−0.89
−0.83
−0.89
−1.23
−0.60
−0.63
−0.54
−0.56
−0.62
−0.62
−0.64
−0.82
−0.59
−0.62
−1.12
−0.86
−0.66
−0.77
−1.02
−0.29
−0.32
−0.30
−0.40
−0.65
−0.67
−0.67
−0.74
−0.32
−0.68
−0.98
−0.75
−0.60
−0.59
−0.78
−0.34
−0.35
−0.37
−0.43
−0.49
−0.48
−0.46
−0.59
−0.37
−0.49
−0.79
−0.64
−0.53
(
GPCRs), ion channels, kinases,
nuclear receptors, proteases, and
various enzymes
0
1
2
3
4
5
study to investigate in silico promiscuity binding to differ-
ent bacterial targets via MOE docking program. Different
bacterial targets were screened using docking simulations.
These 15 synthesized compounds were docked at four dif-
ferent classes of enzymes containing 11 different receptors.
These four classes that were screened in this study are:
DHFR (2W9S), bacterial DNA gyrase (Gyr, PDB ID 3G7E,
from Escherichia coli and 3G75, from S. aureus),
aminoacyl-tRNA synthetases (PDB ID 1QU3, 1PFY,
aaRS inhibition has been shown as the specific mode of
action for many natural antimicrobial agents synthesized by
bacteria and fungi. Therefore, aaRSs have the potential to be
targeted by novel agents either from synthetic or natural
sources to yield specific and selective anti-infective (Ruan
et al., 2005). β-ketoacyl-acyl carrier protein (ACP) synthase
III (EC 2.3.1.180, also known as FabH or KAS III) is an
essential target for novel antibacterial drug design. The
enzyme initiates the fatty acid elongation cycles and is
involved in the feedback regulation of the biosynthetic
pathway via product inhibition (Qiu et al., 2001).
1
EUQ, 1VBM, 1KMM, 1EVL, 1COA, 1EIT), β-ketoacyl
carrier protein synthase III (KAS III, 1HNJ).
Dihydrofolate reductase (DHFR, EC 1.5.1.3) is a critical
enzyme that catalyzes the reduction of dihydrofolate to tet-
rahydrofolate using nicotinamide adenine dinucleotide
phosphate (NADPH) as a cofactor. DHFR has been the
subject of much research as the target of antimicrobial
agents. Methotrexate, trimethoprim, and pyrimethamine,
having 2-aminopyrimidine moiety, are the selective inhibi-
tors of DHFR (Capdeville et al., 2002). DNA gyrase is a
bacterial enzyme that introduces negative supercoils into
DNA, and it is considered as the attractive target for anti-
bacterial drug research. However, resistance is now a pro-
blem for this class of antibacterials in addition to most other
classes (Ho et al., 1999). Gyrase consists of two hetero-
dimeric subunits, GyrA and GyrB. The fluoroquinolone
class of drugs such as ciprofloxacin inhibits GyrA and
induces cell death by trapping the gyrase–DNA complex,
inducing oxidative damage, and preventing DNA replication
The observed negative fitness values of binding inter-
actions of all targets were tabulated (Table 4) and have
shown a rational correlation between the docking scores and
MIC values of compounds found experimentally as shown
in Fig. 7. In Fig. 7, specific target refining technique was
utilized by extrapolating the MIC of compounds in accor-
dance with in silico docking scores at various target proteins
of both S. aureus (Fig. 7b1) and E. coli in (Fig. 7b2). The
compounds are arranged in the ascending order of their
MIC values that complies with the docking score patterns.
Compound named as 0 depicts the standard drug
ciprofloxacin.
It was found in Fig. 7 that compounds 3 and 11 per-
taining to reduced docking scores in gram-positive strains of
S. aureus also possess reduced MIC values as compared
with ciprofloxacin. Whereas compound 6 has slightly raised
docking score (Table 4, −11.8555 and −10.8594 kcal/mol)
in S. aureus strains that was also validated experimentally
and is shown by a slight increase in MIC diameter in
Fig. 7a1. Contrary to this, in the E. coli or gram-negative
strains the lead compounds 3, 6, and 11 had docking scores
(
Drlica et al., 2008). Aminoacyl-tRNA synthetases (aaRSs)
are among the less exploited, but still promising targets that
are essential for the protein biosynthesis of all living
organisms. These targets have been validated in nature as

Med Chem Res
Table 4 MOE docking scores (in kcal/mol) of retrieved hits showing promiscuity binding with different antibacterial targets
MOE Docking Scores (Kcal/mol)
Compound No.
2
W9S
3G7E/3G75
-12.0003
-9.6002
-13.7275
-11.9722
-11.6750
-11.9639
-8.1459
-8.0963
-
1KMM
1QU3
-10.2101
-8.8052
-11.3751
-10.3651
-10.7963
-10.8594
-
1HNJ
1
2
3
4
5
6
7
8
9
1
1
1
1
1
1
-11.5908
-9.8605
-12.6242
-11.3136
-11.5574
-11.8555
-
-12.2795
-9.2039
-
-
-12.8243
-10.7789
-10.9400
-10.0934
-11.0147
-9.9970
-12.3303
-10.3730
-
-
-10.0022
-
-
-8.1491
-
-
-
-
0
1
2
3
4
5
-11.0081
-12.0512
-10.0139
-10.9954
-9.8980
-11.6619
-16.8511
-12.4957
-11.2563
-12.8627
-
-12.1157
-10.8469
-10.8938
-8.9470
-9.9579
-8.0048
-10.1230
ND
-10.3065
-11.9946
-10.9406
-
-
-11.7841
-
-11.8641
-10.4812
-
-
-
-
-11.5161
ND
Trimethoprim
Ciprofloxacin
ND
ND
-14.1588
-13.6731
ND
-11.0798
For better visualization, a color map is used; for compounds having docking scores in the range of −8 to −9 kcal/mol are indicated with red color.
In the range of −10 to −11 kcal/mol are colored with yellow. Values higher than −12 kcal/mol are colored with green. Docking scores for standard
drugs are indicated with orange color. Compound that are not fit well in binding cavity are indicated with white color
MOE Molecular Operating Environment, ND not determined
close to that of ciprofloxacin and is also obvious from the
experimental MIC circles (shown in Fig. 7a2). It was further
seen in Fig. 7a2 that synthesized compounds with reduced
potency showed increasing MIC diameter and this may
explain the good correlation with the improved activity of
these compounds against gyrase-β over E. coli strains.
Docking studies on DHFR from S. aureus (PDB ID:
trimethoprim, and compound 3 are overlayed. Close
inspection of 3D structure revealed that the docking poses
of ciprofloxacin (cyan), trimethoprim (green), and com-
pound 3 (yellow) are almost similar (Fig. 8b-c). Analysis of
the 2D interactions of the compound 3 showed that oxygen
of the C-5 carbonyl group acts as a side chain acceptor and
formed hydrogen bond with thr46. Similarly, amino group
at C-2 position and N-3 of the cyclic guanidine moiety
2
W9S) was carried out. In Fig. 8a, ciprofloxacin,

Med Chem Res
Fig. 7 a1, a2 Minimum inhibitory concentration (MIC) of compounds
is depicted in circles. Increasing diameter of MIC corresponds to loss
or reduced activity of compound over specific strain. Alongside the
docking scores in Kcal/mol are depicted that are predicted by MOE
software. b1, b2 The yellow circle is rendered as ciprofloxacin. The
small circle in size relates to the more potent entity against specific
strain and vice versa
showed hydrogen bond interactions with Ser49. Phenyl ring
at C-4 formed strong π-π interactions with Phe92. In tri-
methoprim, pyrimidine nitrogen pointed towards Thr46 and
act as side chain acceptor. Amino group at the C-2 of
pyrimidine ring acts as HBD and forms interactions with
Asn18. Similarly, piperazinyl-NH group in ciprofloxacin
points towards Ala7 and carboxylic acid group towards
Ser49. The observed negative fitness values of binding
interactions (i.e. docking score) revealed that these hits were
tightly fitted into the active sites (Table 4).
E. coli and one from S. aureus). Initially, MOE docking
performance was assessed by selecting co-crystal structure
from PDB (PDB entry code 1KMM). The co-crystallized
ligand, namely HAM was docked into the active site of
1KMM to ensure that the docking program regenerates the
bound conformation correctly. The binding pattern of the
most active compound 3 showed that they involved in
hydrogen bonding with three amino acids (Arg311, Tyr264,
and Arg113) as shown in Fig. 10. Docking analysis on
aminoacyl-tRNA synthetases from S. aureus (PDB ID:
1QU3) was also performed. The most active compounds 3,
6, and 11 exhibited the highest docking scores of −11.3751,
−10.8594, and −10.8938 kcal/mol respectively. Docking
orientation of lead compound 3 is shown in Fig. 11.
The docking studies were carried out using MOE
between 2-amino-1,4-dihydropyrimidines and ß-ketoacyl-
acyl carrier protein synthase III receptor (1HNJ). The cal-
culated interaction energies for all the compounds are
shown in Table 4. The amino acid residues to which the
most active compound 3 binds are: Gly152, Phe213,
Asn247, and Arg249. 2-Amino group was observed in HBD
interaction with Gly152. C-5 carbonyl oxygen of the pyr-
imidine acts as a strong hydrogen bond acceptor and formed
strong hydrogen bond with Asn247. Similarly, arene-arene
interactions were also observed between Phe213 and phenyl
ring at C-5 position. Furthermore, C-5 phenyl ring oriented
In the next step, we analyzed DNA gyrase. Crystal
structure of DNA gyrase (PDB ID 3G7E, from E. coli and
3
G75, from S. aureus) with MTX as the co-crystallized
ligand was selected for these studies. We analyzed the
computer-generated molecular models of compound 3 and
reference standard ciprofloxacin. The key residues of
interaction were Thr165, Asp73 (E. coli) and highly con-
served structural water molecule Fig. 9a-b. Superimposed
model of compound 3 with ciproflaoxacin into the binding
site of DNA gyrase from S. aureus and E. coli (as viewed in
Chimera 1.8.1 (Pettersen et al., 2004) is shown in Fig. 9c-d.
The computed docking scores are tabulated in Table 4.
In order to assess the binding affinity of 2-amino-1,
4
-dihydropyrimidines with aminoacyl-tRNA synthetases,
molecular docking studies were carried out within the
aminoacylation sites of eight different aaRSs (seven from

Med Chem Res
Fig. 8 a Superposition of ciprofloxacin (cyan), trimethoprim (green), and compound 3 (yellow) docked into the binding site of DHFR from
S. aureus (PDB ID: 2W9S); 2D view of ciprofloxacin (b) trimethoprim (c) and compound 3 (d) in the active site of 2W9S
Fig. 9 Modeled mode of binding of compound 3 into the active site of
DNA gyrase from E. coli (PDB ID 3G7E) and from S. aureus (PDB ID
compound 3 with Asp73, Thr165 and conserved water molecule in
E. coli GyrB; c, d 3D modeled mode of binding of compound 3 into
the active site of 3G75 and 3G7E respectively
3
G75); a, b 2D and 3D binding interactions showing interaction of

Med Chem Res
Fig. 10 2D view of compound 3 (left) and ciprofloxacin (right) in the active site of 1KMM
Fig. 11 3D modeled mode of binding of compound 3 in active site of a 1HNJ; b 1PFY; c 1QU3 and d 1VBM

Med Chem Res
in such a way to form arene-π interactions with Arg249
Fig. S-1 in supplementary Data). The top-scoring binding
Elma E 30 H and E 60 H (Germany) ultrasonic cleaner with
a nominal power of 250 and 500 W respectively.
(
models of compound 3 into the active sites of various tar-
gets are illustrated in Fig. 11.
General procedure for the acid-catalyzed synthesis of
2-amino-1,4-dihydropyrimidines under conventional heating
Conclusions
A mixture of an appropriate aldehyde (10 mmol), guanidine
hydrochloride (12 mmol), 1,3-dicarbonyl compound (10
mmol), SnCl .2H O (10 mol %), and DMF (10 mL) as
In conclusion, we have developed an effective methodology
for the base-catalyzed synthesis of some novel 2-amino-1,
2
2
solvent was heated to reflux in a 100 mL round bottom
flask. The reaction was monitored by TLC. After the
completion of the reaction, the mixture was poured in ice
and the resulting precipitate was filtered and the crude
product was recrystallized from an appropriate solvent or
purified with silica gel chromatography. The purity of
compounds was checked by TLC in different solvent sys-
tems. All the products were confirmed by comparing their
4-dihydropyrimidines under ultrasonic irradiation. This one-pot
procedure provides several advantages such as operational
simplicity, high yield (71–89 %), short reaction time (within
an hour) as compared to conventional heating. Because of the
limited availability of substituted guanidines, the results of
this study will help the medicinal chemist researchers to
design biologically active molecules to establish SAR. We
also performed DFT calculations for the detailed mechanistic
analysis of this reaction. Although acid-catalyzed synthesis
of 2-aminopyrimidines required longer reaction time and low
yield as compared to base-catalyzed synthesis, however, DFT
calculations clearly illustrate that tin chloride-mediated
Biginelli reaction to produce amino pyrimidines has ener-
getics quite accessible under the reaction conditions (70 °C).
Furthermore, lead compounds 3, 6, and 11 are predicted to
have acceptable pharmacokinetic/drug-like properties. Based
on ADME/toxicity predictions and binding orientations, we
are convinced that these small molecules could help the
medicinal chemist to design future chemotherapeutic strategy
to avoid rapid drug resistance against bacterial infections.
The efforts to design new and promiscuous chemical scaf-
folds with improved effect on their biological activity and
pharmacokinetic properties are the future perspectives for
antibacterial treatment.
1
13
melting points, GC/MS, LCMS and HNMR and C NMR.
General procedure for the base-catalyzed synthesis of
2-amino-1,4-dihydropyrimidines under conventional
heating
A mixture of an aldehyde (10 mmol), guanidine hydro-
chloride (12 mmol), 1,3-dicarbonyl compound (10 mmol),
and sodium bicarbonate (3.35 gm, 40 mmol) in DMF
(20 mL) was taken in a round bottom flask and stirred at
60–70 °C. The reaction was monitored by TLC. After
cooling, the mixture was poured onto crushed ice. The
precipitate was filtered and thoroughly washed with water.
The crude product was recrystallized from an appropriate
solvent or purified with silica gel column chromatography.
The purity of compounds was checked by TLC in different
solvent systems. All the products were confirmed by com-
1
paring their melting points, MS, and HNMR data.
Experimental
Chemistry
Synthesis of 2-amino-1,4-dihydropyrimidines under
ultrasonic irradiation (1–15)
A mixture of an aldehyde (10 mmol), guanidine hydro-
chloride (12 mmol), 1,3-dicarbonyl compound (10 mmol),
and sodium bicarbonate (3.35 gm, 40 mmol) in DMF
(20 mL) was taken in a Pyrex tube and irradiated in an
ultrasonic bath at 60–70 °C. The reaction was monitored by
TLC. After cooling, the mixture was poured onto crushed ice.
The precipitate was filtered and thoroughly washed with
water. The crude product was recrystallized from an
appropriate solvent or purified with silica gel column
chromatography. The purity of compounds was checked by
TLC in different solvent systems (A: petroleum ether: ethyl
acetate (3:2), B: chloroform: methanol (5:1)). All the pro-
ducts were confirmed by comparing their melting points,
All building blocks were purchased from commercial
sources and were used without any further purification.
Solvents were purified and dried according to the literature
procedure. All other anhydrous solvents were obtained from
standard commercial vendors and were used without any
further purification. They were stored over molecular sieves
1
13
(
4 Å). Melting points are uncorrected. H and C-NMR
spectra were recorded on a Bruker spectrometer at 300 and
5 MHz respectively using TMS as internal standard and
7
CDCl or dimethylsulphoxide (DMSO) as solvent. Mass
3
spectra were recorded on Agilent technologies 6890N Gas
chromatography (GC) and an inert mass selective detector
1
5
973 GC-mass spectrometer. Sonication was performed in
elemental analysis, MS, and HNMR data.

Med Chem Res
Ethyl 2-amino-6-methyl-4-phenyl-1,4-dihydropyrimidine-
HCl, diethylmalonate. R 0.57 (B). Yield 77 %; m.p. 217 °C.
f
1
5
-carboxylate (1) 1 was prepared according to the general
H NMR (300 MHz, DMSO-d ): δ 1.18 (t, 6H, J = 7.1 Hz,
6
procedure by using benzaldehyde, guanidine HCl, ethyl
OCH CH ), 3.90 (q, 4H, J = 7.1 Hz, OCH ), 3.72 (s, 3H,
2
3
2
1
acetoacetate. R 0.63 (A). Yield 79 %. m.p. 205 °C. H
OCH ), 3.73 (s, 3H, OCH ), 4.01 (q, 4H, OCH ), 4.98 (s,
f
3 3 2
NMR (300 MHz, DMSO-d ): δ 1.09 (t, 3H, J = 7.2 Hz,
1H, CH), 5.87 (s, 2H, NH ), 6.66 (d, 1H, Ar–H), 7.00 (d,
2
6
1
3
OCH CH ), 2.24 (s, 3H, CH ), 4.10 (q, 2H, J = 7.2 Hz,
1H, Ar–H), 9.43 (s, 1H, NH). C–NMR (75 MHz, DMSO-
d ): δ 12.4, 14.7 (OCH CH ), 17.9 (CH ), 54.8 (CH–Ar),
2
3
3
OCH ), 5.24 (s, 1H, CH), 7.08 (m, 5H, Ar–H), 5.83 (s, 2H,
2
6
2
3
3
1
3
NH ), 9.23 (bs, 1H, NH). C–NMR (75 MHz, DMSO-d6):
56.7 (OCH ), 59.4, 60.1 (OCH ), 100.2 (C–COOEt), 126.7-
3 2
2
δ 14.4 (OCH CH ), 18.5 (CH ), 54.4 (CH–Ar), 59.6
139.0 (C-aromatic), 147.9 (CH C=C), 150.3 (C-aromatic-
2
3
3
3
(
OCH ), 98.5 (C–COOEt), 126.7–145.3 (C-aromatic),
OCH ), 160.5 (C–NH ), 165.1 (COOEt); EIMS calculated
2
3
2
(
148.9 (CH C=C), 160.3 (C–NH ), 165.1 (COOEt); EIMS
for C H N O (M+•) 319.
16 21 3 4
3
2
calculated for C H N O (M+•) 259. CHNS analysis
calculated for C H N O , C = 64.85; H = 6.61; N =
1
1
1
4 17 3 2
Ethyl
2-amino-4-(2-chlorophenyl)-6-ethoxy-1,4-dihydro-
1
4 17 3 2
pyrimidinie-5-carboxylate (6) 6 was prepared according
to the general procedure by using 2-chlorobenzal-
dehyde, guanidine HCl, diethylmalonate. R 0.67 (B). Yield
6.20; O = 12.34, Found: C = 64.77 %; H = 6.65 %; N =
6.29 %; O = 12.29 %.
f
1
-(2-Amino-6-methyl-4-phenyl-1,4-dihydropyrimidine-5-yl)
7
3 %; m.p. 232 °C; 1H NMR (300 MHz, DMSO-d ): δ 1.19
6
ethanone (2) 2 was prepared according to the general
(
t, 6H, J = 7.1 Hz, OCH CH ), 4.11 (q, 4H, J = 7.1 Hz,
2 3
procedure by using benzaldehyde, guanidine HCl, acet-
OCH ), 5.60 (s, 1H, CH), 5.93 (s, 2H, NH ), 7.1-7.3 (m,
4H, Ar–H), 9.57 (bs, 1H, NH) . 13C-NMR (75 MHz,
DMSO-d ): δ 12.8, 14.6 (OCH CH ), 17.9 (CH ), 53.6
2
2
1
ylacetone. R 0.69 (A). Yield 83 %; m.p. 214 °C. H NMR
f
(
300 MHz, DMSO-d ): δ 2.14 (s, 3H, CH ), 2.35 (s, 3H,
6 3
6
2
3
3
CH CO), 5.15 (s, 1H, CH), 5.66 (s, 2H, NH ), 7.0 (m, 5H,
3
2
(CH–Ar), 59.8, 60.2 (OCH ), 99.7 (C–COOEt), 126.7-
2
1
3
Ar–H), 9.69 (br s, 1H, NH),; C–NMR (75 MHz, DMSO-
d ): δ 17.4 (CH ), 29.7 (CH CO), 53.8 (CH–Ar), 110.5
1
39.0 (C-aromatic), 148.9 (CH C=C), 161.5 (C–NH ), 165.7
3 2
6
3
3
(COOEt); EIMS calculated for C H N O Cl (M+•) 323.
1
5 18 3 3
(
C–COMe), 126.6–142.9 (C-aromatic), 149.6 (CH C=C), 160.3
3
Ethyl 2-amino-4-(4-hydroxy-3-methoxyphenyl)-6-methyl-
,4-dihydropyrimidine-5-carboxylate (7) 7 was prepared
(
C–NH ), 194.9 (COMe); EIMS calculated for C H N O
2
13 15 3
1
(
M+•) 229.
according to the general procedure by using vanillin, gua-
(
2-Amino-4,6-diphenyl-1,4-dihydropyrimidin-5-yl)(phenyl)
nidine HCl, ethyl acetoacetate. R = 0.61 (A). Yield 77 %;
f
methanone (3) 3 was prepared according to the general
1
m.p. 196 °C. H NMR (300 MHz, DMSO-d ): δ 1.11 (t, 3H,
6
procedure by using benzaldehyde, guanidine HCl, diben-
J = 7.1 Hz, CH3), 2.25 (s, 3H, CH ), 3.71 (s, 3H, OCH ),
3
3
1
zoylmethane. R 0.50 (A). Yield 80 %; m.p. 213 °C. H
f
4
.01 (q, 2H, J = 7.1 Hz, OCH CH ), 5.24 (s, 1H, CH), 5.78
2 3
NMR (300 MHz, DMSO-d ): δ 5.14 (s, 1H, CH), 5.89 (s,
6
(
s, 2H, NH ), 6.40 (s, 1H, Ar–H), 6.45 (d, 1H, H-aromatic),
2
2
H, NH ), 7.10 (m, 10H, Ar–H), 7.42 (m, 5H, Ar–H), 9.73
2
6
.50 (d, 1H, Ar–H), 9.27 (br s,1H, NH), 10.51 (s, 1H OH).
1
3
(
br s, 1H, NH). C–NMR (75 MHz, DMSO-d ): δ 53.6
13
6
C-NMR (75 MHz, DMSO-d ): δ 14.7 (OCH CH ), 18.5
6
2
3
(
CH–Ar), 101.4 (C–COPh), 120.2–142.7 (C-aromatic),
(
(
CH ), 54.6 (CH–Ar), 56.2 (OCH3), 60.4 (OCH2), 100.8
C–COOEt), 119.7–144 (C-aromatic), 144.3 (C-aromatic-
3
1
47.6 (CH C=C), 164.1 (C–NH ), 192.4 (COPh); EIMS
3 2
calculated for C H N O (M+•) 353.
2
3 19 3
OH), 147.2, (CH3C=C), 151.2 (C-aromatic-OCH ), 161.5
3
(C–NH2), 164.1 (COOEt); EIMS calculated for
Ethyl 2-amino-6-ethoxy-4-phenyl-1,4-dihydropyrimidine-5-
C H N O (M+•) 305.
15 19 3 4
carboxylate (4) 4 was prepared according to the general
procedure by using benzaldehyde, guanidine HCl, diethyl
Ethyl 2-amino-4-(4-hydroxyphenyl)-6-methyl-1,4-dihydro-
pyrimidine-5-carboxylate (8) 8 was prepared according to
the general procedure by using 4-hydroxybenzaldehyde,
1
malonate. R 0.59 (A). Yield 73 %; m.p. 210 °C. H NMR
f
(
300 MHz, DMSO-d6):
δ
1.10 (t, 6H, J = 7.2 Hz,
OCH CH ), 4.11 (q, 4H, J = 7.2 Hz, OCH ), 5.21 (s, 1H,
2
3
2
guanidine HCl, ethyl acetoacetate. R 0.66 (B). Yield 75 %.
f
CH), 5.87 (s, 2H, NH ), 6.90 (m, 5H, Ar–H), 9.32 (bs, 1H,
2
1
m.p. 218 °C. H NMR (300 MHz, DMSO-d ): δ 1.14 (t, 3H,
1
3
6
NH).
C–NMR (75 MHz, DMSO-d ): δ 12.6, 14.4
6
J = 7.2 Hz, CH ), 2.17 (s, 3H, CH ), 4.01 (q, 2H, J = 7.2
3
3
(
(
OCH CH ), 53.7 (CH–Ar), 59.6, 60.4 (OCH ), 100.3
2 3 2
Hz, OCH CH ), 5.24 (s, 1H, CH), 5.81 (s, 2H, NH ), 6.67
2
3
2
C-COOEt), 126.6–142.1 (C-aromatic), 152.7 (CH C=C),
3
(
9
d,1H, J = 8.4 Hz, Ar–H), 7.11 (d,1H, J = 8.4 Hz, Ar–H),
.29 (br s, 1H, NH), 10.04 (s, 1H, OH). C-NMR (75 MHz,
1
60.0 (C–NH ), 165.9 (COOEt); EIMS calculated for
2
13
C H N O (M+•) 289.
1
5 19 3 3
DMSO-d ): δ 14.4 (OCH CH ), 17.9 (CH ), 53.9 (CH–Ar),
6
2
3
3
Ethyl 2-amino-6-ethoxy-4-(4-mothoxyphenyl)-1,4-dihydro-
pyrimidine-5-carboxylate (5) 5 was prepared according to
the general procedure by using anisaldehyde, guanidine
59.8 (OCH
2
), 99.8 (C–COOEt), 126.7–134.0 (C-aromatic),
C=C), 157.7 (C–OH), 161.7 (C–NH ), 164.3
(COOEt); EIMS calculated for C14 (M+•) 275.
148.9 (CH
3
2
H N O
17 3 3

Med Chem Res
1
-(2-Amino-4-(4-hydroxy-3-methoxyphenyl)-6-methyl-1,4-
(C–OH), 160.5 (C NH ), 164.5 (COOEt); EIMS calculated
2
dihydropyrimidine-5-yl) ethanone (9) 9 was prepared
according to the general procedure by using vanillin, gua-
for C H N O (M+•) 275.
1
4 17 3 3
1-(2-amino-6-methyl-4-m-tolyl-1,4-dihydropyrimidin-5-yl)
nidine HCl, acetylacetone. R 0.73 (A). Yield 73 %; m.p.
f
ethanone (13) 13 was prepared according to the general
procedure by using 3-methylbenzaldehyde, guanidine HCl,
1
2
00 °C. H NMR (300 MHz, DMSO-d ): δ 2.07 (s, 3H,
6
CH ), 2.32 (s, 3H, CH CO), 3.83 (s, 3H, OCH ), 5.10 (s,
3
3
3
1
acetylacetone. R 0.72 (A). Yield 81 %; m.p. 253–254 °C. H
f
CH), 5.88 (s, 2H, NH ), 6.40 (s, 1H, Ar–H), 6.45 (d, 1H, H-
2
NMR (300 MHz, DMSO-d ): δ 1.17 (s, 3H, CH3), 2.29 (s,
6
aromatic), 6.50 (d, 1H, Ar–H), 9.69 (br s, 1H, NH), 10.59
6H, CH ), 5.06 (s, 1H, CH), 6.01 (s, 2H, NH ), 7.0–7.6 (m,
3 2
1
3
(
s, 1H OH). C–NMR (75 MHz, DMSO-d ): δ 17.9 (CH ),
6 3
13
4H, Ar–H), 9.17 (bs, 1H, NH). C–NMR (75 MHz, DMSO-
2
1
8.9 (CH CO), 53.4 (CH–Ar), 101.2 (C–COMe), 121.8-
39.1 (C-aromatic), 144.8 (C-aromatic-OH), 149.0,
3
d ): δ 18.1 (CH ), 26.1 (C-aromatic-CH ), 29.3 (CH CO),
6
3
3
3
5
1
4.0 (CH–Ar), 101.1 (C–COMe), 125.0-139.0 (C-aromatic),
47.9 (CH C=C), 151.8 (C=O), 162.1 (C–NH ), 194.4
(
CH C=C), 151.7 (C-aromatic-OCH ), 161.1 (C–NH ),
3 3 2
3
2
1
2
94.9 (COMe); EIMS calculated for C H N O (M+•)
1
4 17 3 3
(COMe); EIMS calculated for C H N O (M+•) 243.
1
4 17 3
75.
1
-(2-amino-4-(3,4-dimethoxyphenyl)-6-methyl-1,4-dihy-
Ethyl
2-amino-4-(4-chlorophenyl)-6-methyl-1,4-dihydro-
dropyrimidin-5-yl)ethanone (14) 14 was prepared accord-
ing to the general procedure by using 3,4-dimtoxyben-
zaldehyde, guanidine HCl, acetylacetone. R 0.53 (A). Yield
pyrimidine-5-carboxylate (10) 10 was prepared according
to the general procedure by using 4-chlorobenzaldehyde,
guanidine HCl, ethyl acetoacetate. R 0.71 (A). Yield 78 %.
m.p. 188 °C. H NMR (300 MHz, DMSO-d ): δ 1.09
f
f
1
71 %; m.p. 221 °C; H NMR (300 MHz, DMSO-d ): δ 2.09
1
6
6
(s, 3H, CH ), 3.69 (s, 6H, OCH ), 5.22 (s, 1H, CH), 5.73 (s,
3 3
(
(
(
t, 3H, J = 7.1 Hz, OCH CH ), 2.24 (s, 3H, CH ), 4.10
q, 2H, J = 7.1 Hz, OCH ), 5.01 (s, 1H, CH), 5.83
2 3 3
2H, NH ), 6.40 (s, 1H, Ar–H), 6.45 (d, 1H, H-aromatic),
2
2
13
6.50 (d, 1H, Ar–H), 9.31 (br s, 1H, NH). C–NMR
s, 2H, NH ), 7.14–7.24 (m, 4H, Ar–H), 9.79 (bs, 1H, NH).
2
(
(
75 MHz, DMSO-d ): δ 17.9 (CH ), 30.3 (CH CO), 53.1
6 3 3
CH–Ar), 56.2 (OCH ),105.3 (C–COMe), 122.1-144.1 (C-
1
3
C–NMR (75 MHz, DMSO-d ): δ 14.9 (OCH CH ), 18.3
6
2
3
3
(
CH ), 53.7 (CH–Ar), 59.8 (OCH2), 98.5 (C–COOEt),
3
aromatic), 144.8 (C-aromatic-OH), 149.0, (CH C=C),
1
EIMS calculated for C H N O (M+•) 289.
3
1
26.7-137.0 (C-aromatic), 148.9 (CH C=C), 160.7 (C–
3
51.7 (C-aromatic-OCH ), 161.1 (C–NH ), 194.9 (COMe);
3 2
NH ), 164.9 (COOEt); EIMS calculated for C H N O Cl
2
14 16 3 2
1
5 19 3 3
(
M+•) 293.
Ethyl 2-amino-4-(3,4-dimethoxyphenyl)-6-methyl-1,4-dihy-
dropyrimidine-5-carboxylate (15) 15 was prepared
according to the general procedure by using 3,4-dimtox-
Ethyl
2-amino-4-(4-chlorophenyl)-6-ethoxy-1,4-dihydro-
pyrimidine-5-carboxylate (11) 11 was prepared according
to the general procedure by using 4-chlorobenzaldehyde,
guanidine HCl, diethyl malonate. R 0.64 (A). Yield 73 %;
m.p. 172 °C. H NMR (300 MHz, DMSO-d ): δ 1.14 (t, 6H,
ybenzaldehyde, guanidine HCl, ethyl acetoacetate. R 0.74
f
f
(B). Yield 77 %. m.p. 230–232 °C. 1H NMR (300 MHz,
1
6
DMSO-d ): δ 0.99 (t, 3H, J = 7.2 Hz, CH3), 2.24 (s, 3H,
6
J = 7.2 Hz, OCH CH ), 4.13 (q, 4H, J = 7.2 Hz, OCH ),
2
3
2
CH ), 3.71 (s, 6H, OCH ), 4.12 (q, 2H, J = 7.2 Hz,
3
3
5
9
1
.24 (s, 1H, CH), 5.97 (s, 2H, NH ), 7.13 (m, 4H, Ar–H),
.32 (bs, 1H, NH). C–NMR (75 MHz, DMSO-d ): δ 12.6,
4.7 (OCH CH ), 17.6 (CH ), 54.1 (CH–Ar), 59.2, 60.6
2
OCH CH ), 5.36 (s, 1H, CH), 5.89 (s, 2H, NH2), 6.40 (s,
1
3
2
3
6
1
9
H, Ar–H), 6.55 (d, 1H, H-aromatic), 6.79 (d, 1H, Ar–H),
2
3
3
13
.80 (br s, 1H, NH). C–NMR (75 MHz, DMSO-d ): 14.7
6
(
OCH ), 101.1 (C–COOEt), 126.7–139.2 (C-aromatic),
2
(
(
OCH CH ), 17.9(CH3), 53.0 (CH–Ar), 59.6 (OCH ), 99.7
2 3 2
C–COOEt), 120.7–144.4 (C-aromatic), 151.7 (C-aromatic-
1
48.5 (CH C=C), 161.1 (C–NH ), 164.9 (COOEt); EIMS
3 2
calculated for C H N O Cl (M+•) 323.
1
5 18 3 3
OCH ), 148.3 (CH C=C), 151.2 (C=O), 164.1 (COOEt);
3
3
EIMS calculated for C H N O (M+•) 319.
16 21 3 4
Ethyl 2-amino-4-(3-hydroxyphenyl)-6-methyl-1,4-dihydro-
pyrimidine-5-carboxylate (12) 12 was prepared according
to the general procedures by using 3-hydroxybenzaldehyde,
In vitro antibacterial studies
guanidine HCl, ethyl acetoacetate. R 0.62 (B). Yield 89 %;
f
m.p. 160–162 °C. 1H NMR (300 MHz, DMSO-d ): δ 1.14
2-Amino-1,4-dihydropyrimidine derivatives were tested for
their antibacterial activity. The bacterial strains used in this
study were chosen primarily based on their importance as
opportunistic human pathogens. Antibacterial assay was
used to find the effectiveness of newly synthesized com-
pounds for inhibition of bacterial growth. This antibacterial
activity was checked by agar well diffusion method with six
bacterial strains included: two gram-positive strains,
6
(
t, 3H, J = 7.2 Hz, OCH CH ), 2.13 (s, 3H, CH ), 4.07
2 3 3
(
q, 2H, J = 7.2 Hz, OCH ), 5.19 (s, 1H, CH), 5.73 (s, 2H,
2
NH ), 6.89–6.97 (m, 3H, Ar–H), 7.15 (t, 1H, 8.1 Hz,
2
1
3
Ar–H), 9.10 (br s, 1H, NH), 9.3 (s, 1H, OH). C–NMR
(
(
(
75 MHz, DMSO-d ): δ 14.1 (OCH CH ), 18.0 (CH ), 54.9
6 2 3 3
CH–Ar), 59.2 (OCH ), 98.7(C–COOEt), 126.7–129.0
2
C-aromatic), 147.6 (CH C=C), 152.1 (C=O), 157.3
3

Med Chem Res
S. aureus and B. subtilis and two gram-negative strains, E.
coli and S. typhi. The compounds having antibacterial
activity were then subjected to determine MIC. MIC is the
concentration of test compound at which the minimum or
least inhibitory zone was detected.
bonds (NOR), and Lipinski’s rule of five are predicted by
MOE software package. Partition coefficients pKa of
compounds and distribution coefficient logD at various
physiological pH of 1.5, 5, 6.5, and 7.4 were predicted by
ChemAxon software package (Marvin v15.4.6, 2015).
Acknowledgments The Higher Education Commission (HEC),
Pakistan is thankfully acknowledged for providing financial support to
Umer Rashid for startup grant under IPFP program (HEC No: PM-
IPFP/HRD/HEC/2011/346).
In silico DFT calculation
All calculations were performed with Gaussian 09 (Frisch
et al., 2009). Geometries of the structures were optimized
without any symmetry constraints at hybrid B3LYP
method. The B3LYP method that consists of parameter
hybrid functional of Becke three in conjunction with the
correlation functional of Lee, Yang, and Parr provides a
nice balance between cost and accuracy (Becke, 1993; Lee
et al., 1988). For geometries optimization, 6-31G* basis set
was used for C, H, N, O, and Cl atoms and LANL2DZ
pseudo-potential for Sn (Hariharan and Pople, 1973; Hay
and Wadt 1985a, b). Each optimized structure was con-
firmed by frequency analysis at the same level as a true
minimum (no imaginary frequency) or a transition state
Compliance with ethical standards
Competing interest The author declares that they have no com-
peting interests.
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