Design and synthesis of 2-quinolones as antioxidants and antimicrobials: A rational approach

Article abstract of DOI:10.1007/s00044-009-9184-x

As an important class of compounds, 2-quinolones are isomeric to 4-quinolones and isosteric to coumarins. The compounds that have 2-quinolone moiety are associated with interesting biologic activities such as antibacterial, anticancer, antiviral, cardiotonic, and N-methyl-D-aspartate receptor inhibitor functions, among others. In the current study, based on the rational approach, lead molecules of the 2-quinolone skeleton were designed for binding to the bacterial DNA gyrase subunit A. Docking simulations and quantitative structure activity relationship (QSAR) analysis were performed using the Molegro Virtual Docker and Sarchitech softwares. Based on these studies, the 7-amino-4-methylquinolin-2(1H)-one parent compound and its carboxamides (JST 1-15) were synthesized using Conrad Limpach synthesis. The synthesized test compounds then were characterized by thin-layer chromatography and melting point determination, as well as by ultraviolet, infrared (IR), ¹H-NMR, and MS studies. All synthesized and purified compounds were tested for antioxidant and antibacterial activity. Birkhaeuser Boston 2009.

Full text of DOI:10.1007/s00044-009-9184-x

MEDICINAL
CHEMISTRY
RESEARCH
Med Chem Res (2010) 19:193–209
DOI 10.1007/s00044-009-9184-x
ORIGINAL RESEARCH
Design and synthesis of 2-quinolones as antioxidants
and antimicrobials: a rational approach
B. S. Jayashree Æ Seeja Thomas Æ Yogendra Nayak
Received: 11 December 2008 / Accepted: 15 March 2009 / Published online: 25 April 2009
¨
ꢀ Birkhauser Boston 2009
Abstract As an important class of compounds, 2-quinolones are isomeric to
4-quinolones and isosteric to coumarins. The compounds that have 2-quinolone
moiety are associated with interesting biologic activities such as antibacterial,
anticancer, antiviral, cardiotonic, and N-methyl-D-aspartate receptor inhibitor
functions, among others. In the current study, based on the rational approach, lead
molecules of the 2-quinolone skeleton were designed for binding to the bacterial
DNA gyrase subunit A. Docking simulations and quantitative structure activity
relationship (QSAR) analysis were performed using the Molegro Virtual Docker
and Sarchitech softwares. Based on these studies, the 7-amino-4-methylquinolin-
2(1H)-one parent compound and its carboxamides (JST 1–15) were synthesized
using Conrad Limpach synthesis. The synthesized test compounds then were
characterized by thin-layer chromatography and melting point determination, as
well as by ultraviolet, infrared (IR), 1H-NMR, and MS studies. All synthesized and
purified compounds were tested for antioxidant and antibacterial activity.
Keywords Antibacterial ꢀ Antioxidant ꢀ Carboxamides ꢀ Docking simulations ꢀ
QSAR analysis ꢀ 2-Quinolones
Introduction
Ever since the discovery of Nalidixic acid in the early 1960s, DNA gyrase, a
prokaryotic-specific type 2 topoisomerase enzyme, has attracted considerable
B. S. Jayashree (&) ꢀ S. Thomas
Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences,
Manipal 576104, India
e-mail: jesolar2001@yahoo.co.in
Y. Nayak
Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal 576104, India

194
Med Chem Res (2010) 19:193–209
attention from the pharmaceutical industry (Cooper et al., 1992). It belongs to a
superfamily of ATPases known as GHKL (gyrase, Hsp90, histidine, kinase, MutL),
which consists of several important targets for infectious and cancer treatments.
Although similar to eukaryotic topoisomerase 2, DNA gyrase has many differences
such that certain antibiotics act specifically against it (Pan and Fisher, 1998).
Bacterial DNA gyrase is involved in the vital processes of DNA replication,
transcription, and recombination (Heddle and Maxwell, 2002). It has the ability to
catalyze the ATP-dependent introduction of negative supercoils into bacterial DNA
and to unknot DNA. This enzyme consists of two subunits, A and B, of molecular
masses 97 and 90 kDa, respectively, with the active enzyme being an A2B2
complex. A subunit of DNA gyrase is involved in DNA breakage and reunion,
whereas the B subunit catalyzes the hydrolysis of ATP (Jain et al., 2006).
The structure activity relationships of compounds based on nalidixic acid have
led to a large group of synthetic antibacterial agents known collectively as
quinolones. The 4-quinolones such as ciprofloxacin, ofloxacin, lomefloxacin,
enoxacin (Fig. 1), are established synthetic antibacterial agents as DNA gyrase
inhibitors (Boehm et al., 2000). The benzopyrone ring in compounds of coumarins
and flavones is isosteric to quinolones and has shown DNA gyrase inhibition. The 2-
quinolones, also called carbostyrils or 1-aza coumarins, are isosteric to coumarins
and isomeric to 4-quinolones and could become a potential candidate for
antibacterial activity (Schechner et al., 2004).
Reports are available on DNA gyrase inhibition by quinolones, coumarins
(chlorobiocin, novobiocin), and cyclothialidines (Chatterji et al., 2001). Quinolones
are known to inhibit the DNA breakage–reunion cycle by binding to the subunit A
and by blocking the gyrase–DNA complex, whereas the latter act on subunit B
(Joseph et al., 2002). A 2-quinolone core is found widely in various alkaloids,
especially the in the Rutaceae family, many of which possess interesting biologic
activity (Dodia and Shah, 2001).
CH3
H2N
N
H
O
2-Quinolone (JST)
O
O
N
HN
HO
N
N
N
CH3
O
F
CH3
Nalidixic acid
O
OH
Ciprofloxacin
Fig. 1 Structures of 2-quinolone and 4-quinolone

Med Chem Res (2010) 19:193–209
195
There has been a considerable interest in developing 2-quinolones as anticancer,
antiviral, antibacterial and antihypertensive, cardiotonic, diuretic, antiinflammatory,
and bronchodilator agents (Leclerc et al., 1986; Milecki et al., 1987; Tikhonova
et al., 2003). The 4-substituted 3-phenyl-2-quinolones show high affinity in binding
to the glycine site of the N-methyl-D-aspartate (NMDA) receptor, and such
antagonists are promising candidates for the treatment of several central nervous
system disorders (Danysz and Parsons, 1998). Amides of 3-hydroxy- and 3-alkyl-4-
carboxylic acids of 2-quinolones also have exhibited a high affinity for the 5-HT3
receptor (Lee, 1997).
In the current study, an attempt was made to understand the ligand–receptor
interactions based on bacterial DNA gyrase as a target enzyme using Molegro Virtual
Docker (MVD) (Thomsen and Christensen, 2006). The structure activity relationships
were established for designed molecules using Sarchitech softwares (http://www.
strandls.com/sarchitect/). Furthermore, the compounds were synthesized and charac-
terized, and their antioxidant and antibacterial activity was determined.
Materials and methods
Chemistry
The chemical structure and three-dimensional (3D) structures were drawn by using
Structure Builder (ACD Chem-Sketch 8.0, ACD Labs, Toronto). The quantitative
structure activity relationship (QSAR) was determined using Sarchitect Designer
2.2–Build 38202 (Strands Life Sciences, Bangalore, India). Docking studies were
done using the facilities of Molecular Modelling (Molegro Virtual Docker
2007.2.2.0, Molegro Bioinformatics, Aarchus C, Denmark). The melting point
was determined using a melting point apparatus (Shital Scientific Industries,
Mumbai, India) and found to be uncorrected. The reactions were monitored by thin-
layer chromatography (TLC), and the Rf values were determined using TLC plates
with the solvent system. Acetone:chloroform (7:3), kmax, and emax for the
synthesized compounds were established by ultraviolet (UV)-visible spectrometer
(Shimadzu UV-Vis Spectrophotometer UV-1650 PC, Shimadzu Corporation,
Kyoto), as explained in the literature (Beckett and Stenlake, 2005). The log p
value was determined as explained in the literature (Selassie, 2003; Taylor, 2005).
Instrumental analysis was carried out in the Quality Assurance Department of
Manipal College of Pharmaceutical Sciences. The IR studies were done with FT-IR
(Shimadzu FTIR 8310, Shimadzu Corporation, Japan). The NMR study was carried
out by the instrument NMR (AMX 400, Bruker AXS Analytical Instruments, New
Delhi, India), and the mass spectral studies were done using GC-MS (Shimadzu
GCMS QP5050, Shimadzu Corporation, Japan).
In Silico approaches
The process of designing new molecules possessing desired physicochemical
properties is a major challenge in the pharmaceutical industry involving laborious

196
Med Chem Res (2010) 19:193–209
and expensive procedures based on trial and error. In most cases, molecular libraries
are screened in a direct search to find lead compounds. We have used molecular
docking to get an insight into molecular interactions and to design potential
inhibitors with better properties. All molecular docking simulations were carried out
using MVD version 2007.2.2.0 installed on an Intel Pentium 4 Machine (Intel
Corporation, Santa Clara, CA).
All the ligand structures were constructed using Chem-Sketch software (ACD
Labs) version 8.0 installed on an Intel Pentium 4 machine. The ligands were saved
in MOL format, then imported in TSAR version 3.3 software (Accelrys
Corporation, San Diego, CA) installed on an Intel Pentium 4 machine and
converted to 3D energy-minimized conformations using CORINA, Molecular
Networks, Erlanger, Germany (converts 2D structure into 3D structure) as
implemented in TSAR. The ligands then were saved in a single MDL SDF file,
followed by selection of the ligands with a lower energy conformation for further
studies. The protein structure of DNA gyrase subunit A Eschericnia coli (PDB
Code: 1AB4) was imported in MVD, and missing bond orders, hybridization states,
and angles then were assigned.
To obtain better potential binding sites in the protein, a maximum of five cavities
were detected using parameters such as molecular surface (expanded van der Waals),
maximum number of cavities (n = 5), minimum cavity volume (10), probe size
(1.20), maximum number of ray checks (n = 16), minimum number of ray hits
(n = 12), and grid resolution (0.80). The chosen cavity was further refined using side
chain minimization by selecting the add-visible option at a maximum of steps per
residue (10,000) and a maximum of global steps (10,000). The setup for side chain
flexibility by selection of the add-visible option, the setting for the selected flexible
side chain during the docking option, and other parameters all were kept in default.
All docking calculations were carried out using the grid-based MolDock score
˚
(GRID) function with a grid resolution of 0.30 A. The binding site on the receptor
was defined as extending in X, Y, and Z directions around the Dock molecule with a
˚
radius of approximately 10 to 17 A. The MolDock optimization search algorithm
with a maximum of 10 runs was used through the calculations, with all other
parameters kept as defaults. One pose per run was retained based on root mean
˚
square division clustering using a heavy atom threshold set at 2.0 A and an energy
penalty of 100. All the poses were examined manually, and the best poses were
retained.
Optimization of the parameter for suitable docking
To obtain better potential binding sites in the protein (1AB4), a maximum of five
cavities was detected using default parameters. Out of the detected cavities, cavity
˚
number 1 (cavity volume, 118,784 A) was selected for further studies. The chosen
cavity was further refined using side chain minimization by selection of an add-
visible option set at a maximum of 10,000 steps per residue and at a maximum of
10,000 global steps. The initial energy was set at 535,059, whereas the energy after
side chain minimization was set at 373,048. The side chain flexibility was set by
selecting the add-visible option. The same was selected during docking, and the

Med Chem Res (2010) 19:193–209
197
Fig. 2 Interaction between N-1 of 2-quinolone and protein residue ser 296
remaining parameters were kept as fixed variables. Furthermore, the docking
simulation was run first for the parent molecule (JST), and the best pose for the set
derivatives was selected on the basis of the MolDock score and re-rank score. The
performance of the obtained pose showed that the hydrogen bond interaction
between the protein residue at ser 296, and the nitrogen (N-1) of the 2-quinolone
showed maximum affinity, indicating that the docking method was most appropriate
for clarifying the binding mode of 2-quinolones as DNA gyrase inhibitors (Fig. 2).
Design of the newer DNA gyrase inhibitors and their docking
Molecular docking studies offer precise information for studying the interaction
between the ligand and the protein residue and serve as a guide for the drug design.
The key feature of the current study was focused on optimizing the amino group
attached to C-7 of carbostyrils/2-quinolones. Initially, the side chain of the 7-amino
4-methyl quinolin-2(1H)-one analog was extended, and then the amide was selected
as the hydrogen bond acceptor to be attached to the amino group. However, the
substituted phenyl group was chosen for its steric, hydrophobic, and van der Waals
interaction with the protein residues. A total of 15 carboxamides were designed for
the QSAR and molecular docking study. The flexible molecular docking simulation
was run for the designed carboxamides, as shown in the Fig. 3. The best poses then
were retained on the basis of the MolDock and re-rank scores for the QSAR study to
predict the activity of the designed molecules, as shown in Table 1.
QSAR analysis
The QSAR analysis was performed using the Sarchitect designer, version 2.2–build
38202, 2005–2007, installed on an Intel Pentium 4 machine. The most general

198
Med Chem Res (2010) 19:193–209
Fig. 3 One of the best poses of the carboxamide (JST) derivative showing interaction
Table 1 MolDock scores and re-rank scores
Ligand
MolDock score
Affinity
Rerank scores
Interaction
JST-9
JST-13
JST-12
JST-7
JST-5
JST-15
JST-3
JST-4
JST-8
JST-2
JST-11
JST-6
JST-1
JST-10
JST-14
JST
–102.532
–95.4474
–95.0156
–94.8734
–89.0439
–88.2391
–87.6747
–87.1968
–86.803
–24.4034
–26.8291
–27.8455
–32.2542
–32.0621
–26.042
–78.482
–119.007
–112.965
–110.911
–106.27
–76.3078
–76.2609
–72.7632
–68.7345
–63.1849
–68.4932
–69.7239
–67.3391
–67.7446
–69.0841
–67.7203
–66.2215
–65.047
–100.261
–95.3907
–100.957
–101.119
–103.806
–99.1341
–100.204
–100.817
–97.4692
–96.3807
–74.961
–28.7836
–28.7585
–23.6592
–28.5179
–24.6628
–27.3517
–25.123
–86.703
–86.3206
–85.8296
–82.5779
–81.0546
–69.3453
–53.0444
–23.8463
–21.9346
–23.3052
–53.3538
–45.892
–61.7187
mathematical form of QSAR is as follows: activity = f (physiochemical properties
and/or structural properties). The training and test set was developed based on the
data obtained from the reported molecule, then imported in SDF format with their
observed log (1/IC50) values. Furthermore, the hydrogen was adjusted and given a
strip/salt wash. The imported molecules then were optimized to their low-energy
conformer using the Dreiding force field, and the observed value was marked as the
end point.

Med Chem Res (2010) 19:193–209
199
The descriptors covering the constitutional, topologic (2D), and conformational
(3D) spaces of compounds were computed for the study. The data set was first
divided into training (model) and test sets randomly. The training set then was
checked for descriptors with missing values and pruned to drop descriptors with low
variance and missing values. The data were partitioned by proportionate selection
using the end point column or clustering, with the number of equal bins to be used
set at three, into a set to be used for building the model (training set), and a test set
to validate the percentage (20%) of the data set was assigned to be the test data set.
The training and test data sets were created as child sets of the main data set.
Three training and test sets were generated for further study. The descriptors in the
order of their relevance to the end point value were ranked based on correlation
(Pearson correlation coefficient). Multiple linear regression was used to build the
regression model because it generates linear equations that describe the relation
between the set of independent descriptors and a dependent descriptor. The test set
validation was done using the developed model from the training set, and the best
model was chosen on the basis of q2 for the further study.
Prediction of activity
The data were imported, and prediction was run for the imported data using the best
model obtained. The QSAR analysis represents a part of the rational approach to
synthesis, in which the activity of the designed molecules is predicted in silico
before an actual synthesis. The QSAR model in the current study was developed
using the training set comprising 29 derivatives of 4-hydroxy-2-quinolone and
related compounds. The 29 derivatives of 4-hydroxy-2-quinolones were further
divided into training and test sets (assigned 20% as the test set) as shown by the bar
chart in Fig. 4).
Of the several models developed, the best model was selected based on the
statistical data obtained after the test set validation, as shown in the Table 1. There
was good correlation between the observed (actual) and predicted activity. The
Fig. 4 Histogram showing random selection of training and test set for selected model

200
Med Chem Res (2010) 19:193–209
Table 2 Statistical data of the
quantitative structure activity
relationship (QSAR) model
Total no. of descriptors computed
No. of descriptors removed
1,081
104
Descriptors dropped due to high correlation
Descriptors selected for subset with the highest rank
Descriptor retained
200
23
177
r2 (multiple linear regression)
q2 (test set validation)
0.84867
0.64376
Table 3 Predicted IC50 values
for DNA gyrase
Compounds
Predicted log
(I/IC50
Predicted (IC50
)
)
E - x = 10-x(lM)
JST
–0.06139
7.59711 9 10-13
0.264414455
JST-1
JST-2
JST-3
JST-4
JST-5
JST-6
JST-7
JST-8
JST-9
JST-10
JST-11
JST-12
JST-13
JST-14
JST-15
–0.8754443
–0.8513568
–0.25756377
0.36311024
0.027068108
–0.19548419
–0.70389855
–0.6126759
0.6989249
0.200039653
1.28484 9 10-6
3.9846 9 10-5
2.11144 9 10-16
8.14923 9 10-13
0.02986075
0.007452603
0.027816669
–0.32198408
–0.32198408
–1.6453929
1.1188405
1.19769 9 10-05
1.19769 9 10-05
145.4441271
3.073843743
4.8245 9 10-7
–0.23353136
–1.8305354
422.4558413
model was further validated using the test set (q2 = 0.64376) (Table 2). The
descriptors were correlated with IC50 values, showing that the topologic 2D
descriptors were correlated positively and the conformational 3D descriptors were
correlated negatively. When the model was run for the imported data to predict their
activity compounds, JST 1 to 15 were selected for antimicrobial activity, as shown
in Table 3. The QSAR model predicted good activity for all the test compounds
including the parent molecule, suggesting that these molecules can be used as
probable templates for further synthesis and biologic evaluation.
Synthesis
The chemicals used in the current project were of Analytical Reagent and
Laboratory Reagent grades obtained from Sigma-Aldrich, Sisco Research Labora-
tories, Qualigens, Rankem, SD Fine Chemicals, Hi-Media, Merck, Loba Chemicals,
and Nice Fine Chemical India.

Med Chem Res (2010) 19:193–209
201
Synthesis of 7-amino 4-methylquinolin-2(1H)-one (JST, Fig. 5) included 10.8 g
(0.1 moles) of m-phenylene diamine and 12.64 mL (0.1 mol) of ethylacetoacetate
taken together in a 250-mL round-bottom flask. The reaction mixture then was
refluxed at 150ꢁC for 18 h in an oil bath. At the end of the reaction period, 200 mL
of water was added to the flask, and the contents were heated on a hot plate to the
boiling temperature of water. Next, the mixture was filtered, and the filtrate was
CH3
∆
O
O
H2O
+
O
+
NH2
-C2H5OH
EtO
CH3
H2N
H2N
N
H
JST
Conrad-Limpach Synthesis
COCl
Pyridine
Toluene
CH3
R
O
NH
N
H
O
JST - 1 to 13
R
Compound code
-R
JST-1
JST-2
JST-3
JST-4
JST-5
JST-6
JST-7
JST-8
JST-9
JST-10
JST-11
JST-12
JST-13
H
o-Cl
m-Cl
p-Cl
o, p-Cl
p-F
o, o-Br
p-NO2
o, o-NO2
o-CH3
p-CH3
m, p-OCH3
-benzene (fusion)
o: ortho; m: meta; p: para
Fig. 5 Preparation of carboxamides of 7-amino 4-methylquinolin-2(1H)-one

202
Med Chem Res (2010) 19:193–209
COCl
COCl
Dry toluene, N
SOCl 2,
110 0C 2
COOH
SO2
HCl
+
+
R
PCl5
R
HCl
POCl 3
+
+
R
Fig. 6 Preparation of carboxylic chloride from the parent carboxylic acid (methods 1 and 2)
chilled in the refrigerator until the appearance of precipitate. The precipitate then
was retrieved, dried in air, purified by recrystallization from methanol, and
characterized.
Preparation of carboxylic acid chloride from the parent carboxylic acid
Method 1 (Fig. 6) (Raitio et al., 2006)
To a solution of carboxylic acid (1.0 mmol) in anhydrous toluene AR grade (10–
20 ml), thionyl chloride (3.5 mmol) was added and the reaction mixture refluxed
under a nitrogen atmosphere for 3 h. The mixture was cooled to room temperature,
and the solvent was evaporated under reduced pressure. Anhydrous toluene (10 mL)
was further added; evaporation was repeated; and the residue was dried under high
vacuum.
Method 2 (Fig. 6) (Furniss et al., 2004)
Equimolar quantities of carboxylic acid and phosphorus pentachloride were taken in
a round-bottom flask fitted with a calcium chloride guard tube connected to a gas
absorption device. The flask was heated in a water bath with stirring until the
reaction began and then kept 30 min longer or until vigorous evolution of hydrogen
chloride had almost ceased. The mixture was cooled to room temperature, and the
phosphorus oxychloride (boiling point, 107ꢁC) was evaporated under reduced
pressure. The product was poured into a small wide-mouth bottle, allowed to
solidify, and protected from moisture.
Synthesis of derivatives
Preparation of carboxamides of 7-amino 4-methylquinolin-2(1H)-one (Fig. 6)
To a solution of 7-amino 4-methyl 2-quinolone (parent compound) in pyridine (5–
10 mL), acid chloride (2-equivalent) was added dropwise at 0.5ꢁC under continuous

Med Chem Res (2010) 19:193–209
203
(CH3CO)2
HCl
O
NH
JST - 14
N
H
O
H2N
N
H
O
JST
Cinnamoyl Chloride
O
NH
N
H
O
JST - 15
Fig. 7 Acetylation and cinnamoylation of 7-amino 4-methylquinoline-2(1H)-one
stirring. The reaction mixture was stirred in a cold condition, and the reaction was
monitored by TLC using the solvent acetone:chloroform (7:3). Finally, the reaction
mixture was poured into ice cold water. The product obtained was filtered, washed
with distilled water until it was free from pyridine, and purified by column
chromatography.
Acetylation of 7-amino 4-methylquinolin-2(1H)-one (Fig. 7) (Furniss et al., 2004)
To 0.5 g of 7-amino 4-methyl 2-quinolone dissolved in 2 mol/L of HCl was added
a small amount of crushed ice. Next, a 20% solution of hydrated sodium acetate
(25 mL) was introduced, to which was added 5 mL of acetic anhydride. The
reaction mixture was stirred in a cold condition until the smell of acetic anhydride
disappeared. The pure product obtained was collected by filtration under a
vacuum.
Spectral studies
Compound JST (7-amino-4-methyl quinolin-2(1H)-one)
The yield was 65%, the m.p 271ꢁC, and the Rf value 0.44. Spectroscopic analysis
showed IR (KBr) tmax/cm-1: NH2 (str) 3423, NH (str) 28 amide 3307, NH (b) amide
1637, C=O (str) 1658, C=C (str) aromatic 1421, 1475, 1552, CH (str) aromatic
methyl 1369. 1H NMR (300 MHz, dimethyl sulfoxide [DMSO]): 11.143 (s, 1H, NH
(a)), 2.275 (d, 3H, CH3(c)), 7.338 (d, 1H, Ar-H (e)), 6.353 (d, 1H, Ar-H (d)), 5.948
(s, 1H, Ar-H, (b)), 5.75 (s, 2H, NH2 (f)). MASS: 174 [M]?, 145 [M-CO]?, 117 [M-
CO,NH,CH2]?, 118 [M-CO,NH,CH2,CH3]?, 104 [M-CO, NH, CH2,CH2]?, 91 [M-
CO, NH, CH2, CH2, NH2]?, 66 [M-CO, NH, CH2, CH2, NH2, C2H2]?, 52 [M-CO,
NH, CH2, CH2, NH2, C2H2, CH2]?, 78 [M-CO, NH, CH2, CH2, CH2, NH2]?, 54 [M-
CO, NH, CH2, CH2, CH2, NH2, C2H2]?, 131 [M-CO, NH]?, 102 [M-CO, NH, CH3,
NH2]?.

204
Med Chem Res (2010) 19:193–209
Compound JST-1 (N(1H)-7-(benzoylamino) 4-methyl quinolin-2(1H)-one)
The yield was 80%, the m.p. more than 310ꢁC, and the Rf value 0.66. Spectroscopic
analysis showed IR (KBr) tmax/cm-1: NH (str) 3330, NH (b) 1500, NH (b) overtone
3120, C=O (str) 1660, CH (str) Ar-CH3 1300, Ar-C=C (str) aromatic 1420, 1460,
1560. 1H NMR (300 MHz, DMSO): 11.595 (s, 1H, NH (a)), 2.395 (s, 3H, CH3(c)),
6.272 (s, 1H, Ar-H, (b)), 10.495 (s, 1H, NH (f)), 7.524–7.677 (m, 5H, Ar-H (h, I, j,
k, l)), 7.524 (d, 1H, Ar-H, (d)), 8.054 (d, 1H, Ar-H, (e). MASS: 278 [M]?, 105 [M-
C10H9N2O]?, 77 [M-C11H9N2O2]?, 52 [M-C13H11N2O2]?.
Compound JST-4 (N(1H)-7-(40-chloro benzoylamino) 4-methyl Quinolin-2(1H)-one)
The yield was 85%, the m.p. more than 310ꢁC, and the Rf value 0.72. Spectroscopic
analysis showed IR (KBr) tmax/cm-1: NH (str) 3330, NH (b) 1500, NH (b) overtone
3130, C=O (str) 1660, CH (str) Ar-CH3 1300, Ar-C=C (str) 1420, 1460, 1560. H
1
NMR (300 MHz, DMSO): 11.606 (s, 1H, NH (a)), 2.392 (s, 3H, CH3(c)), 6.273 (s,
1H, Ar-H, (b)); 10.547 (s, 1H, NH (f)); 7.905–8.0 (m, 4H, Ar-H (h, I, j, k)); 7.584 (d,
1H, Ar-H, (d)); 7.971 (d, 1H, Ar-H, (e)) MASS: 312 [M]?, 139 [M-C10H9N2O]?,
111 [M-C11H9N2O2]?, 75 [M-C11H9N2O2Cl]?.
Compound JST-13 (N(1H)-7-(10-napthoyl Benzoylamino) 4-methyl Quinolin-2(1H)-
one)
The yield was 70%, the m.p 308ꢁC, and the Rf value 0.75. Spectroscopic analysis
showed IR (KBr) tmax/cm-1: NH (str) 3330, NH (b) 1500, NH(b) overtone 3120,
C=O (str) 1660, Ar-CH3 (str) 1300, Ar-C=C (str) 1460, 1500, 1560. H NMR
1
(300 MHz, DMSO): 11.606 (s, 1H, NH (a)), 2.403 (s, 3H, CH3(c)), 6.285 (s, 1H, Ar-
H, (b)); 10.841 (s, 1H, NH (f)); 7.344 -8.161 (10H, Ar-H (d, e, g, h, i, j, k, l, m)).
MASS: 328 [M]?, 155 [M-C10H9N2O]?, 127 [M-C11H9N2O2]?, 117 [M-
C13H9NO2]?, 91 [M-C15H11NO2]?.
Compound JST-14 (N(1H)-7-(acetamido) 4-methyl Quinolin-2(1H)-one)
The yield was 60%, the m.p. 300ꢁC, and the Rf value 0.45. The spectroscopic
analysis showed IR (KBr) tmax/cm-1: NH (str) 3300, NH (b) 1560, NH (b) overtone
3120, C=O (str) 1680, Ar-C=C (str) 1480, 1500, 1560. 1H NMR (300 MHz,
DMSO): 11.557 (s, 1H, NH (a)), 2.072 (d, 3H, CH3(c)), 7.266 (d, 1H, Ar-H (d));
7.583 (d, 1H, Ar-H (e)); 6.242 (s, 1H, Ar-H, (b)); 10.227 (s, 2H, NH2, (f)); 2.366 (s,
3H, CH3 (h)). MASS: 216 [M]?, 174 [M-C2H2O]?, 145 [M-C3H3O2]?.
Biologic activity
Antioxidant activity
The antioxidant activity of the test compounds was determined by the 1,1-diphenyl-
2-picrylhydrazyl (DPPH) radical scavenging method described earlier (Rajakumar

Med Chem Res (2010) 19:193–209
205
and Rao, 1995). Different aliquots of the test compound (10–1,000 lg/mL) in
methanol were mixed with 1 mmol/L of methanolic DPPH solution to a final
volume of 2.0 mL and incubated for 20 min at room temperature. Absorbance was
measured at 517 nm. A blank was performed in the same manner without the drug,
and ascorbic acid was taken as the standard. The experiment was performed in
triplicate, and the percentage of radical scavenging was determined as ([blank –
test]/blank) 9 100. Microsoft excel was used to calculate IC50.
Antibacterial activity
Antimicrobial activity was determined by the agar diffusion method explained
earlier (Cruikshank et al., 1975). All 12 synthesized test compounds were tested
against four species of bacteria, namely, Bacillus subtilis (gram-positive), Staph-
ylococcus aureus (gram-positive), Escherichia coli (gram-negative), and Pseudo-
monas aeruginosa (gram-negative). Stock solutions of synthesized test compounds
and standard drugs were prepared in DMSO. The test compounds were used at a
concentration of 500 lg/0.1 mL. Amoxycillin and ciprofloxacin were used as
standards at concentrations of 10 lg/0.1 mL and 5 lg/0.1 mL, respectively.
Mueller-Hinton agar medium (beef extract 300, casein hydrolasate 17.5, starch
1.5, and agar 17.0 in distilled water at a pH 7.4 0.2 and 25ꢁC, sterilized by
autoclave at 15 lb pressure at 121ꢁC for 15 min) was used for the agar diffusion
method. The petri dishes were thoroughly washed and sterilized in a hot air oven at
160ꢁC for 1 h. The inoculum was added to the medium, which was poured into
sterile petri dishes for solidifying. Wells (bores) were made in the medium using a
sterile borer after solidification. To the respective bores, 0.1 mL of the test and
standard solutions was added. A control bore containing only DMSO was
maintained in each plate. The petri dishes were kept at room temperature 30 min
for diffusion to take place, then incubated at 37ꢁC for 24 h. The zone of inhibition
was observed and measured using a scale.
Results and discussion
Of the 16 test compounds synthesized, including the parent, only the parent
compound (JST) and JST-14 showed a log p value well within 1, whereas, all the
other test compounds showed values above 1, as shown in the Table 4. However, no
single compound showed values above 2, indicating that these compounds, with log
p values less than 2, would show activity well within the safety range.
In the current study, it was thought worthwhile to have test compounds with log p
values such that they partitioned optimally in the lipophilic and hydrophilic regions.
The log p values of all the test compounds were found to be in the range of 0.793 to
1.828. The kmax values of all the test compounds were found to be in the range of
325 to 344 nm. The kmax and emax of the synthesized compounds were found,
respectively, to be in the range of 325 to 344 nm and 1.3 9 104 to 2.9 9
104 mol-1 cm-1. As the substitution on the parent molecule was made, there was a
decrease in kmax
.

206
Med Chem Res (2010) 19:193–209
Table 4
kmax, emax, Rf, p and log p values of the synthesized compounds
Compounds Molecular
formula
Molecular Melting
weight
Yield Rf kmax emax
(%)
p
Value
Log
p
point (8C)
JST
C
C
C
C
C
C
C
C
C
C
C
C
10H10N2O
174.19
278.30
271
[310
[310
[310
[320
318
65
80
76
70
85
88
68
83
85
85
65
70
74
70
60
66
0.44 344 17232.96 6.21 0.793
0.66 325 17192.91 45.62 1.659
0.70 330 16989.06 35.66 1.55
0.72 333 12609.38 48.73 1.688
0.72 335 18443.75 48.67 1.687
JST-1
JST-2
JST-3
JST-4
JST-5
JST-6
JST-7
JST-8
JST-9
JST-10
JST-11
JST-12
JST-13
JST-14
JST-15
17H14N2O2
17H13ClN2O2 312.75
17H13ClN2O2 312.75
17H13ClN2O2 312.75
17H12Cl2N2O2 347.19
0.79 332 17542.59 67.3
1.828
17H13FN2O2
296.29
315
0.70 333 17993.84 40.46 1.61
0.77 336 21023.92 55.64 1.745
0.72 338 17102.85 42.56 1.63
0.77 337 16484.56 65.32 1.82
0.74 331 18179.92 51.40 1.71
0.73 333 19886.66 46.71 1.67
0.62 332 24930.88 29.04 1.46
17H12Br2N2O2 436.09
[310
[320
[320
317
17H13N3O4
17H12N4O6
18H16N2O2
18H16N2O2
323.30
368.30
292.33
292.33
338.35
330.37
216.23
304.34
320
C19H18N2O4
318
C21H16N2O2
C12H12N2O2
C19H16N2O2
308
0.75 331 18041.64 52.2
1.718
300
0.45 329 14286.24 9.89 0.995
0.71 341 29234.16 49.00 1.69
[320
Table 5 1,1-Diphenyl-2-
picrylhydrazyl DPPH radical
scavenging activity
Compound
IC50
Ascorbic acid
JST
17.67
1,886.00
2,192.98
975.66
JST-1
JST-4
JST-9
990.09
JST-14
170.01
Antioxidant activity is a prerequisite for performing many related biologic
treatments such as anticancer, antiinflammatory, antiallergic, and antidiabetic
procedures. The antioxidant procedure for all the synthesized test compounds (JST
and JST 1–15) was performed using the DPPH• scavenging method. Ascorbic acid
was used as the standard. The test compounds JST, JST-1, JST-4, JST-9, and JST-14
showed antioxidant activity, as shown in Table 5.
None of the test compounds except JST-14 showed antioxidant potential, clearly
suggesting the need for a balance in hydrophilicity/hydrophobicity. This was
supported by its partition coefficient data, as shown in Table 4. However, the parent
molecule did show a similar partition coefficient value without much antioxidant
property, suggesting that no direct correlation existed between the log p value and
the antioxidant activity. Furthermore, all the test compounds screened for their
antioxidant activity had a log p value greater than 1 and possessed virtually no

Med Chem Res (2010) 19:193–209
207
activity. Thus, there is a need to change the peripheral groups in 2-quinolones to get
optimum biologic activity.
Of the 16 test compounds, including the parent molecule, synthesized and tested
for their antibacterial activity (Table 6), compound JST-12 showed activity better
than the other test compounds against E. coli and S. aureus. However, the activity of
JST-12 was not comparable with that of the standards, amoxycillin and ciproflox-
acillin. Compound JST-12 showed a log p value of 1.46, whereas the other test
compounds had values below or above this range and were not significant in
expressing their antibacterial property. From the docking simulation studies, it was
found that compound JST-9 showed very high re-rank scores against the target
enzyme DNA gyrase. However, in reality, when tested against the organisms, it did
not generate any useful data.
The rational approach to lead discovery has prompted a better insight into the
development of a more specific 2-quinolone as a potential antibacterial agent. The
data showing docking and the QSAR analysis definitely have generated useful
parameters needed for an ideal bacterial DNA gyrase inhibitor. The rational
approach to lead discovery presents a direct correlation between an ideal
therapeutically built-up molecule and the synthesized test compound. However,
the current study showed that this method was not solely responsible for generating
Table 6 Antibacterial activity of synthesized test compounds
Compound
Zone of inhibition (mm)
Escherichia
coli
Pseudomonus
aerugenosa
Staphylococcus
aureus
Bacillus
subtilis
Amoxacillin
Ciprofloxacin
JST
23
30
10
–
26
32
11
11
–
30
38
11
–
34
34
10
12
10.5
–
JST-1
JST-2
–
–
JST-3
–
–
–
JST-4
9
–
–
–
JST-5
9
–
–
–
JST-6
–
–
11
12
–
12
12
–
JST-7
–
–
JST-8
11
13
–
9
JST-9
10
–
–
12.5
12
–
JST-10
JST-11
JST-12
JST-13
JST-14
JST-15
10
–
13
15
11
–
10
–
16
–
13
13
13
11
–
–
11
–
12
–

208
Med Chem Res (2010) 19:193–209
functional activities of test compounds in reality. This approach also has paved the
way for generating more useful 2-quinolone analogs in future studies as bacterial
DNA gyrase inhibitors.
References
Beckett AH, Stenlake JB (2005) Practical pharmaceutical chemistry, Part II, 4th edn. CBS Publishers and
Distributors, New Delhi, India, pp 275–278
Boehm HJ, Boehringer M, Bur D, Gmuender H, Huber W, Klaus W, Kostrewa D, Kuehne H, Luebbers T,
Meunier-Keller N, Mueller F (2000) Novel inhibitors of DNA gyrase: 3D structure based biased
needle screening, hit validation by biophysical methods, and 3D guided optimization: promising
alternative to random screening. J Med Chem 43:2664–2674. doi:10.1021/jm000017s
Chatterji M, Unniraman S, Mahadevan S, Nagaraja V (2001) Effect of different classes of inhibitors
on DNA gyrase from Mycobacterium smegmatis. J Antimicrob Chemother 48:479–485. doi:
10.1093/jac/48.4.479
Cooper CS, Klock PL, Chu DT, Hardy DJ, Swanson RN, Plattner JJ (1992) Preparation and in vitro and in
vivo evaluation of quinolines with selective activity against gram positive organisms. J Med Chem 35:
1392–1398. doi:10.1021/jm00086a007
Cruikshank R, Duguid JP, Marmion BP, Swain RH (1975) Medical microbiology, 2nd edn. Churchill
Livingstone, NY, USA, p 190
Danysz W, Parsons CG (1998) Glycine and N-methyl-D-aspartate receptors: physiological significance
and possible therapeutic applications. Pharmacol Rev 50:597–664
Dodia N, Shah A (2001) Synthesis and anti-HIV studies of some substituted pyrimidinediones,
ethoxypyranon [3,2-C] quinolines and hydrazinopyrano [3,2-C] quinolines. Indian J Pharm Sci 63:
211–215
Furniss BS, Hannaford AJ, Smith PWG, Tatchell AR (2004) Vogel’s textbook of practical organic
chemistry, 5th edn. Pearson Education, Delhi, India, p 1074
Heddle J, Maxwell A (2002) Quinolone-binding pocket of DNA gyrase: role of GyrB. Antimicrob Agents
Chemother 46:1805–1815. doi:10.1128/AAC.46.6.1805-1815.2002
Jain SC, Pandey MK, Upadhyay RK, Kumar R, Hundal G, Hundal MS (2006) Alkaloids from Toddalia
aculeata. Phytochemistry 67:1005–1010. doi:10.1016/j.phytochem.2006.03.012
Joseph B, Darro F, Behard A, Frydman A, Lesur B, Collignon F (2002) 3-Aryl-2-quinolone derivatives:
synthesis and characterization of in vitro and in vivo antitumor effects with emphasis on a new
therapeutical target connected with cell migration. J Med Chem 45:2543–2555. doi:10.1021/jm010
978m
Leclerc G, Marciniak G, Decker N, Schwartz J (1986) Cardiotonic agents. 1. Synthesis and structure-
activity relationships in a new class of 3-, 4-, and 5-pyridyl-2(1H)-quinolone derivatives. J Med
Chem 29:2427–2432. doi:10.1021/jm00162a002
Lee HZ (1997) Inhibitory effect of 2-phenyl-4-quinolone on serotonin-mediated changes in the morphology
and permeability of endothelial monolayers. Eur J Pharmacol 335:245–254. doi:10.1016/S0014-
2999(97)01203-X
Milecki J, Baker SP, Standifer KM, Ishizu T, Chida Y, Kusiak JW (1987) Carbostyril derivatives having
potent b-adrenergic agonist properties. J Med Chem 30:1563–1566. doi:10.1021/jm00392a006
Pan XS, Fisher LM (1998) DNA gyrase and topoisomerase IV are dual targets of clinafloxacin action in
streptococcus pneumonia. Antimicrob Agents Chemother 42:2810–2816
Raitio KH, Savinainen JR, Vepsalainen J, Laitinen JT, Poso A, Jarvinen T, Nevalainen T (2006)
Synthesis and SAR studies of 2-oxoquinoline derivatives as CB2 receptor inverse agonists. J Med
Chem 49:2022–2027. doi:10.1021/jm050879z
Rajakumar DV, Rao MN (1995) Antioxidant properties of phenyl styryl ketones. Free Radic Res 22:309–
317. doi:10.3109/10715769509145643
Schechner M, Scirockin F, Stote RH, Dejaegere AP (2004) Functionality maps of the ATP-binding site of
DNA gyrase-B: generation of a consensus model of ligand binding. J Med Chem 47:4373–4390. doi:
10.1021/jm0311184

Med Chem Res (2010) 19:193–209
209
Selassie CD (2003) History of quantitative structure-activity relationship: Burger’s medicinal chemistry
and drug discovery, vol I, 6th edn. Wiley InterScience, Hoboken, NJ, pp 15–23
Taylor PJ (2005) Hydrophobic properties of drug in comprehensive medicinal chemistry, vol IV, 1st edn.
Elsevier, Pergamon Press, Oxford, UK, pp 270–273
Thomsen R, Christensen MH (2006) MolDock: a new technique for high-accuracy molecular docking.
J Med Chem 49:3315–3321. doi:10.1021/jm051197e
Tikhonova IG, Baskin II, Palyulin VA, Zefirov NS (2003) CoMFA and homology-based models of the
glycine binding site of N-methyl-D-aspartate receptor. J Med Chem 46:1609–1616. doi:10.1021/
jm0210156