The antibacterial activity of some sulfonamides and sulfonyl hydrazones, and 2D-QSAR study of a series of sulfonyl hydrazones

Article abstract of DOI:10.1016/j.saa.2012.08.043

Benzenesulfonicacid-1-methylhydrazide (1) and its four aromatic sulfonyl hydrazone derivatives (1a-1d), N-(3-amino-2-hydroxypropyl)benzene sulfonamide (2) and N-(2-hydroxyethyl)benzenesulfonamide (3) were synthesized and their structures were determined b

Full text of DOI:10.1016/j.saa.2012.08.043

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
Contents lists available at SciVerse ScienceDirect
Spectrochimica Acta Part A: Molecular and
Biomolecular Spectroscopy
journal homepage: www.elsevier.com/locate/saa
The antibacterial activity of some sulfonamides and sulfonyl hydrazones, and
2D-QSAR study of a series of sulfonyl hydrazones
H. Güzin Aslan a, Servet Özcan b, Nurcan Karacan c,
⇑
a Department of Chemistry, Science and Art Faculty, Erciyes University, 38039 Melikgazi, Kayseri, Turkey
b Department of Biology, Science and Art Faculty, Erciyes University, 38039 Melikgazi, Kayseri, Turkey
c Department of Chemistry, Science and Art Faculty, Gazi University, 06500 Ankara, Turkey
g r a p h i c a l a b s t r a c t
h i g h l i g h t s
Plot of experimental versus predicted pMIC values of training sets of Escherichia coli and Staphylococcus
aureus.
"
New original sulfonamide and
sulfonyl hydrazones were
synthesized.
"
"
New compounds were screened for
their antibacterial activity.
2D-QSAR analysis was performed on
aromatic sulfonyl hydrazones used
as antimicrobial agents against
Escherichia coli and Staphylococcus
aureus.
a r t i c l e i n f o
a b s t r a c t
Article history:
Benzenesulfonicacid-1-methylhydrazide (1) and its four aromatic sulfonyl hydrazone derivatives (1a–
1d), N-(3-amino-2-hydroxypropyl)benzene sulfonamide (2) and N-(2-hydroxyethyl)benzenesulfonamide
(3) were synthesized and their structures were determined by IR, 1H NMR, 13C NMR, and LCMS tech-
niques. Antibacterial activities of new synthesized compounds were evaluated against various bacteria
strains by microdilution and disk diffusion methods. The experimental results show that presence of
OH group on sulfonamides reduces the antimicrobial activity, and antimicrobial activities of the sulfonyl
hydrazones (1a–1d) are smaller than that of the parent sulfonamide (1), except Candida albicans. In addi-
tion, 2D-QSAR analysis was performed on 28 aromatic sulfonyl hydrazones as antimicrobial agents
against Escherichia coli and Staphylococcus aureus. In the QSAR models, the most important descriptor
is total point-charge component of the molecular dipole for E. coli, and partial negative surface area
(PNSA-1) for S. aureus.
Received 25 February 2012
Received in revised form 4 July 2012
Accepted 8 August 2012
Available online 1 September 2012
Keywords:
Sulfonamides
Sulfonyl hydrazones
Antibacterial activity
QSAR
Ó 2012 Elsevier B.V. All rights reserved.
Introduction
cause of death worldwide and the third leading cause of death in
developed countries [3,4]. Although the search for new lead struc-
Infectious diseases which increase dramatically by resistant and
multiresistant microbes [1,2] are nowadays the second major
tures for the development of antimicrobial agents is an increas-
ingly important problem in medicinal chemistry. Pharmaceutical
companies are leaving this area due to economic reasons [5]. It is
well-known that sulfonamides and sulfonylhydrazones exhibit a
broad spectrum of biological activities such as antimicrobial
[6,7], antitumor [8], antidepressant-like activity [9] e.g., therefore,
⇑
Corresponding author. Tel.: +90 312 2021117; fax: +90 312 2122279.
E-mail address: nkaracan@gazi.edu.tr (N. Karacan).
1386-1425/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.saa.2012.08.043

330
H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
O
S
scientist have directed considerable attention on their synthesis,
bioactivity and computational studies [10–12].
R2
In our previous studies, sulfonic acid hydrazides and their
hydrazones were obtained and screened for their antimicrobial
and cytotoxic activity [13–17]. As part of our ongoing studies,
new aromatic sulfonamides (1–3) and sulfonylhydrazone deriva-
tives (1a–1d) were obtained and their structures were character-
ized by FT-IR, 1H NMR, 13C NMR and LC/MS techniques. Their
antibacterial activities against Gram-positive (Staphylococcus aur-
eus ATCC 25923, Bacillus cereus ATCC 11778, Enterococcus faecalis
ATCC 29212, Bacillus subtilis ATCC 6633, Staphylococcus epidermidis
ATCC 12228, Enterobacter aerogenes ATCC 13048) and Gram-nega-
tive bacteria (Pseudomonas fluorescens ATCC 49838, Klebsiella pneu-
monia ATCC 13883, Escherichia coli ATCC 25922, Pseudomonas
aeruginosa ATCC 27853) and also antifungal activity against Can-
dida albicans ATCC 90028 were screened by both microdilution
and disk diffusion methods. In addition, 2D-QSAR studies were
performed on a series of sulfonyl hydrazones, all of them synthe-
sized previously by us, using the antimicrobial activity values
(pMIC) of E. coli and S. aureus as dependent variables.
N
O
R1
(1) R1= NH2, R2= CH3
(2) R1=H, R2= CH2CH2OH
(3) R1=H, R2=CH2CH(OH)CH2NH2
Fig. 1. Structures of the sulfonamides.
N-(3-amino-2- hydroxypropyl)benzenesulfonamide (2)
The general synthetic method described above was applied by
using benzenesulfonyl chloride (5.05 mL, 0.04 mol) and 1,3-diami-
no-2-propanol (7.21 g, 0.08 mol). Yield 51%; mp 155 °C; MS (70 eV,
APC1): 231.26 (M+H+, 100%), 231:2ðM ꢀ C6H5SO2Hþꢀ; 13:1%Þ,
2
Anal. Calcd for C9H14N2O3S:C, 47.00; H, .13; N, 12.10; S, 13.91.
Found: C, 46.94; H, 6.12; N, 12.16; S, 13.92.
N-(2-hydroxyethyl)benzenesulfonamide (3)
The general synthetic method described above was applied by
using benzenesulfonyl chloride (5.05 mL, 0.04 mmole) and etha-
nolamine(4.83 mL, 0.08 mol). Yield 65%; mp þ79–80 °C; MS (70 eV,
APC1): 200.3 (MꢀH+–, 100%), 214:1ðM þ NH4 ; 13:2%Þ, Anal. Calcd
for C8H11NO2S: C, 47.70; H, 5.61; N, 7.00; S, 15.83. Found: C,
47.74; H, 5.52; N, 6.96; S, 15.93.
Experimental
The elemental analyses (C, H, N and S) were performed on a
LECO-CHSNO-9320 type elemental analyzer. The IR spectra
(4000–400 cmꢀ1) were recorded on a Mattson-1000 FT-IR spectro-
photometer with samples prepared as KBr pellets. NMR spectra
were recorded on a Bruker-Spectrospin Avance DPX-400 Ultra-
Shield (400 MHz) using DMSO-d6 and CDC13 as a solvent and
TMS as an internal standard. LC/MS-APC1 were recorded on AGI-
LENT 1100. The melting point was recorded on a Opti MELT 3
hot stage apparatus. TLC was conducted on 0.25 mm silica gel
plates (60F254, Merck). Visualization was made with ultraviolet
light. All extracted solvents (all from Merck) were dried over anhy-
drous Na2SO4 and evaporated with a BUCHI rotary evaporator. Re-
agents were obtained commercially from Aldrich (ACS grade) and
used as received.
Salicylaldehydebenzenesulfonylhydrazone (1a)
The general synthetic method described above was applied by
using yellow solid (1) (3.1 mL, 46.0 mmole) and salicylaldehyde
(3 mL, 23.0 mmole). The product was crystallized from ethanol/
hexane mixture (3:1). Yield 82%; mp 112–113 °C; MS (70 eV,
APC1): 301.1 (M+l+, 62.8%), 302.1 (M+2+, 9.0%), 303.1 (M+3+,
7.1%), 134.1 (M-2+ꢀC3H7SO2NH(CH2)2, 21.7%), 164.1 (M+ꢀC4H9-
SO2NH, 37.9%); Anal. Calcd for C10H24N2O4S2: C, 40.0; H, 8.0; N,
9.33.; S, 21.3. Found: C, 40.23; H, 7.94; N, 9.10; 8, 21.51.
2-hydroxy-1-acetophenonbenzenesulfonylhydrazone (1b)
General procedure for the synthesis
The general synthetic method described above was applied by
using yellow solid (1) (3.95 mL, 47.5 mmole) and 1-hydroxyace-
tophenon (3.0 mL, 23.7 mmole). The product was crystallized from
ethanol/hexane mixture (2:1). Yield 88%; mp 116–117 °C; MS
(70 eV, APC1): 315.1 (M+l+–, 100%), 316.1 (M+2+–, 14.5%), 317.1
Compounds (1–3) were synthesized by well-known substitu-
tion reactions between various amines and benzenesulfonyl chlo-
ride. Similarly, compounds (1a–1d) were obtained by
substitution reactions between various aldehydes and compound
(1). Structures of the sulfonamides (1–3) were shown in Fig. 1.
Structural formula of the new sulfonyl hydrazones (1a–1d) were
given in Table 1. Generally, THF solution of amines (or hydrazide)
was added slowly drop by drop to the THF solution of benzenesul-
fonyl chloride (or aldehydes). In this process, temperature was
kept between ꢀ5 and ꢀ10 °C, and the mixture was stirred for
24 h at room temperature. After the completion of the reaction
(monitored by TLC), solvent was filtered in vacuum. The product
was purified by column chromatography. The products were puri-
fied by silica gel 60 (230–400 mesh) column chromatography with
THF as eluent.
+
+
0
(M+3 , 10.4%), 195.1 (M+2 ꢀC4H9SO2–, 31.5%); Anal. Calcd for
CnH26N2O4S2: C, 42.04; H, 8.28; N, 8.92; S, 20.38. Found: C,
42.17; H, 8.45; N, 9.32; S, 19.98.
2-hydroxy-1-naphtaldehydebenzenesulfonylhydrazone (1c)
The general synthetic method described above was applied by
using yellow solid (1) (4.7 mL, 47.4 mmole) and 2-hydroxynaftal-
dehyde (3.0 mL, 23.7 mmole). Product was recrystallized from eth-
anol/benzene mixture (2:1). Yield 88%; mp 117–118 °C; MS (70 eV,
APC1): 329.1 (M+1+, 100%), 330.1(M+2+, 16.1%), 331.1 (M+3+,
11.1%), 209.1 (M+2+1ꢀC4H9SO2, 28.9%), 192.1 (M+ꢀC4H9SO2NH,
9.2%); Anal. Calcd for C12H28N2O4S2: C, 43.9; H, 8.5; N, 8.5; S,
19.5. Found: C, 44.33; H, 8.37; N, 8.61; S, 19.52.
Benzenesulfonicacid-1-methylhydrazide (1)
The general synthetic method described above was applied by
using methylhydrazide (4.4 mL, 0.08 mol) and benzenesulfonyl
chloride(5.05 mL, 0.04 mol). Yield 62%; mp 67–68 °C; MS (70 eV,
Thiophene-2-carbaldehyde benzenesulfonylhydrazone (1d)
The general synthetic method described above was applied by
using yellow solid (1) (2.0 mL, 16.0 mmole) and thiophene-2-carb-
aldehyde (1.06 mL, 8.1 mmole). The product was crystallized from
methanol/hexane mixture (2:1). Yield 80%; mp 123–124 °C; MS
(70 eV, APC1): 343.5 (M+1+, 100%), 344.15 (M+2+, 16.1%), 345.1
(M+3+, 10.1%), 223.1 (M+2+ꢀC4H9SO2, 3.9%); Anal. Calcd for C13H30-
APC1):
186.1
(M+,
100%),
185.1,
(MꢀH+,
11.5%),
171:1ðM ꢀ CHþ; 10:5%Þ; 142:1ðM ꢀ C6H5SOþ; 10:5%Þ; Anal. Calcd
3
2
for C7H10N2O2S: C, 45.09; H, 5.43; N, 15.09; S, 17.19. Found: C,
45.14; H, 5.41; N, 15.04; S, 17.21.

H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
331
Table 1
Structural formula and observed pMIC values for the studied data sets of 28 aromatic sulfonyl hydrazones.
O
S
N
R4
R1
N
O
R2
R3
ECa(pMIC)
SAb(pMIC)
.
Compounds
R1
R2
R3
R4
(1a)
(1b)
(1c)
(1d)
SALMSH
SALESH
SALPSH
AFMSH
AFESH
AC6H5
AC6H5
AC6H5
AC6H5
ACH3
ACH3
ACH3
ACH3
AH
AH
AH
AH
AH
AH
AH
AH
AH
ACH3
ACH3
ACH3
ACH3
ACH3
ACH3
ACH3
ACH3
ACH3
AH
AH
ACH3
AH
AH
AH
AH
AH
ACH3
ACH3
ACH3
AH
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC10H6
AC4H3S
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
2.8978
2.8012
3.5550
3.3327
3.1062
3.2016
3.1128
3.1540
3.3008
3.2538
3.1790
3.2343
3.2227
3.2993
3.0427
3.2159
3.5078
3.5584
3.5686
3.0466
3.1526
3.1162
3.0018
3.1040
3.0278
3.6226
3.7633
3.6659
2.9722
2.9824
2.9708
2.9812
3.0673
3.0685
3.0784
3.0532
3.0571
3.0693
3.0734
3.0373
3.0357
3.0460
3.0548
3.0597
3.0019
3.0095
3.0090
3.0429
3.0603
3.0389
3.0649
3.0778
3.0791
3.0044
3.0179
3.0175
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
ACH3
ACH2CH3
ACH2CH2CH3
AFPSH
A2-OHAC6H4
NAFMSH
NAFESH
NAFPSH
SALMSMH
SALESMH
SALPSMH
AFMSMH
AFESMH
AFPSMH
NAFMSMH
NAFESMH
NAFPSMH
5MSALMSH
5MSALESH
5MSALPSH
5MAFMSH
5MAFESH
5MAFPSH
A2-OHAC10H6
A2-OHAC10H6
A2-OHAC10H6
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC6H4
A2-OHAC10H6
A2-OHAC10H6
A2-OHAC10H6
A2-OHA5-MeAC6H3
A2-OHA5-MeAC6H3
A2-OHA5-MeAC6H3
A2-OHA5-MeAC6H3
A2-OHA5-MeAC6H3
A2-OHA5-MeAC6H3
AH
AH
AH
AH
AH
ACH3
ACH3
ACH3
AH
AH
AH
AH
AH
AH
AH
AH
AH
AH
ACH3
ACH3
ACH3
AH
a
E. coli ATCC 25922.
S. aureus ATCC 25923.
b
N2O4S2: C, 45.6; H, 8.77; N, 8.18; S, 18.71. Found: C, 45.87; H, 8.20;
N, 8.16; S, 18.94.
2.4 mL 96 well Masterblock dish containing either MHB for bacte-
rial strains and or YPDB for the yeast. For the test, the 96-well
plates were prepared by dispensing into each well 195 lL of serial
dilutions of synthesized compounds was transferred into seven
Biological activity: in vitro evaluation
consecutive wells in each column. The last well, containing only
195
control. For each columns of the plate, 5
tested inoculated to each well individually. The final volume in
each well was brought to 200 L by adding MHB or YPDB solution.
For the bacterial cells; ampicilin, trymethoprim, tetracycline in
MHB and for yeast miconazole and nystatin in YPDB at the concen-
l
L of MHB or YPDB without compound was used as negative
Biological activity of the synthesized compounds were individ-
ually screened against a panel of microorganisms, including Gram-
positive (S. aureus ATCC 25923, B. cereus ATCC 11778, E. faecalis
ATCC 29212, Bacillus subtilis ATCC 6633, S. epidermidis ATCC
12228, E. aerogenes ATCC 13048), Gram-negative bacteria (P. fluo-
rescens ATCC 49838, K. pneumonia ATCC 13883, E. coli ATCC
25922, P. aeruginosa ATCC 27853) and yeast ( C. albicans ATCC
90028). Cultures were obtained from Erciyes University, Depart-
ment of Biology. Bacterial strains were cultured overnight at
35 °C in Triptic Soy Broth (TSB) and the yeast was cultured over-
night at 30 °C in Yeast-extract Peptone Dextrose Broth (YPDB) in
a rotary shaker at 200 rpm. Overnight cultures were then trans-
ferred to fresh medium and adjusted the turbidity of all broth cul-
tures to 0.1 absorbance at 640 nm on a spectrophotometer. These
stock cultures were stored in the dark at 4 °C during the survey.
lL of the strains to be
l
tration range of 1000–7.8 lg/mL was used as standard drug for po-
sitive control. Contents of each well were mixed on a plate shaker
at 300 rpm for 20 s and then incubated at 35 °C for 18–24 h. Micro-
bial growth was determined by absorbance at 600 nm using the
Tecan Sunrise microplate reader and with the presence of a white
‘‘pellet’’ on the well bottom by visual examination. The concentra-
tion resulted with no growth confirmed by plating 5 lL samples
from clear wells on MHA or YPDA. Every experiment in the anti-
bacterial assay was replicated twice against each organism. MIC’s
were defined as the lowest concentrations of the antimicrobial
agents that inhibited visible growth of the microorganism.
Microdilution method
Minimal inhibitory concentrations (MIC) were determined by
microdilution broth method following the procedures recom-
mended by the National Committee for Clinical Laboratory Stan-
dards (NCCLSs, 2000) [18]. Shortly, synthesized compounds
dissolved in dimethylsulfoxide (DMSO) were first diluted to the
highest concentration, and then serial twofold dilutions were made
Disk diffusion method
Antibacterial screening of synthesized compounds dissolved in
DMSO were performed using Miller Hinton Agar (MHA) for the
bacterial strains and Yeast-extract Peptone Dextrose Agar (YPDA)
for yeast cells. 100
lL of the culture suspensions adjusted to the
in a concentration range from 31.25 to 2000 lg/mL in sterile
OD640 0.1 (equivalent to 0.5 Mc Farland Turbidity Tubes) were

332
H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
Table 2
Four-parameter QSAR models by BMLR method.
X
D
X
t-Test
Descriptors
For E. coli
Training set
R
2 = 0.9887
F = 327.0753
s
2 = 0.0010
R2c ¼ 0:9745
v
0
1
2
3
4
1.1619eꢀ03
8.4052eꢀ01
7.5577eꢀ01
6.2884eꢀ01
8.4501eꢀ03
5.9281eꢀ05
2.1365eꢀ01
6.4655eꢀ01
1.4002eꢀ01
3.8829eꢀ03
3.5999
Intercept
ꢀ25.2993
11.6893
5.9193
ꢀ2.1762
Tot point-charge comp. of the mol. dipole
HOMO energy
Relative number of aromatic bonds
Relative negative charged SA (RNCS)
Test set
R
2 = 0.9644, RMSE = 0.0348
For S. aureus
Training set
R
2 = 0.9873
F = 290.3714
s
2 = 0.0001
R2c ¼ 0:9741
v
0
1
2
3
4
3.2572eꢀ05
2.1309e+01
1.1269e+01
2.0901eꢀ03
2.0286eꢀ02
1.3049eꢀ07
4.3953eꢀ03
2.4389eꢀ01
5.7156eꢀ05
8.9030eꢀ04
2.6141
Intercept
ꢀ25.7306
ꢀ8.7205
3.6568
ꢀ2.2786
Partial negative surface area (PNSA-1)
Max nucleoph. react. index for a N atom
H-acceptors surface area (HASA)
Relative number of double bonds
Test set
R
2 = 0.9856, RMSE = 0.0048
swabbed over the entire surface of the medium [19,20]. Sterile 6-
mm-diameter disks (1.2 mm thickness whatman filter paper) were
among the descriptors applied in the same equation; in fact, BMLR
method in CODESSA softwere rejects descriptors with intercorrela-
tion coefficients larger than a default (0.8) threshold value.
impregnated with 50
extract per disk) placed onto MHA or YPDA. Negative controls were
prepared just by using DMSO. For bacterial cells; ampicilin (50 g/
disk), trymethoprim (30 g/disk), tetracycline (30 g/disk) on
MHA and for yeast miconazole (40 g/disk) and nystatin (30 g/
lL dissolved extracts (including 1.2 mg total
l
Regression analysis
l
l
Best Multiple Linear Regression (BMLR) method embedded in
CODESSA software was used to obtain the QSAR models [35]. The
BMLR regression algorithm generates the best n-parameter regres-
sion equation (n P 2), based on the highest R2 and F values ob-
tained in the process. During the calculation the decriptor scales
are normalized and centered automatically. If the variables are
mutually intercorrelated, the BMLR rejects descriptors with inter-
correlation coefficients larger than a certain threshold value [36].
To validate the predictive capability of the models, the squared
correlation coefficient (R2), leave-one-out cross-validated squared
l
l
disk) on YPDB were used as reference standards to determine the
sensitivity of each strain. The inoculated plates were incubated at
35 °C for 18–24 h. The antibacterial activity was measured as the
diameter (mm) of clear zone of growth inhibition. Four disks per
plate and each test were run in duplicates.
QSAR analysis
Data sets
correlation coefficient (R2c ), the Fisher criteria (F), and standard er-
v
Antimicrobial activity values of a series of sulfonyl hydrazones,
all of which synthesized in our laboratory previously [13–17,21–
31], were screened against S. aureus ATCC 25923 and E. coli. Exper-
imental MIC values were first transformed to pMIC (–logMIC) on a
molar basis (listed in Table 1) and used as dependent variables to
obtain the linear relationship. Twenty-eight data set was randomly
separated into a training set of 20 compounds and a test set (pre-
diction set) of eight compounds.
ror (s2) were used [37] for internal validation. High R2 values (>0.9),
small standard deviations (<0.07), high F values and high cross-val-
idated squared correlation coefficient (>0.9) indicate the robust-
ness of generated models. In order to check the performance of
the obtained models (shown in Table 2), we apply the obtained
linear model to the test set. R2 was used to evaluate the fitness
ability, and RMSE (root mean square error) was used to evaluate
the predictive capability of the model. The statistical parameters
for the test sets were R2 = 0.9644 and RMSE = 0.0348 for E. coli,
R2 = 0.9856 and RMSE = 0.0048 for S. aureus, confirming the capa-
bility of the model derived from the training set.
Descriptor calculation
Energy minimization of all of the compounds was performed by
using Gaussian 03 software and semi-empirical AM1 method [32].
Gaussian outputs were loaded into the CODESSA (version 2.7.10)
software to calculate more than 500 molecular descriptors (consti-
tutional, topological, geometrical, electrostatic, quantum-chemical
and thermodynamical descriptors). Online AlogPS 2.1 applet was
used to calculate the logP values of our compounds [33]. Hydration
energy values were calculated using HyperChem 7.5 software [34].
The ‘‘breaking point’’ rule was applied to determine the optimal
number of descriptors in the model equations. This rule is based
Results and discussion
Structure of the compounds
Experimental 1H and 13C NMR chemical shift values of our com-
pounds were listed in Table 4. Proton chemical shift values of (1)
and (2) were reported previously, but we have found no reference
about their carbon atom chemical shift values in the literature
[38,39]. Carbon atom peaks of the compounds were assigned using
theoretical chemical shift values calculated with GIAO/DFT/B3LYP/
++6-311G(2d,2p) methods in DMSO solution. In the NMR spectra of
the compounds, proton signals of aromatic moiety appear at 6.90–
8.12 ppm, and aromatic carbon peaks appear at 164.01 and
on the significant improvement of R2 R2 < 0.02–0.04) with re-
(D
spect to the number of descriptors in the model. Consequently,
four descriptors were used as independent variables in our models
(Table 2). The absence of colinearity among the used descriptors is
confirmed by intercorrelation matrix for the independent variables
in our models (Table 3). No significant correlation was found

H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
333
Table 3
Correlation matrix of the descriptors involving in the QSAR models.
For E. coli
For S. aureus
HOMO
RNAOa
RNCSb
TPCc
RNDBd
MNRIe
PNSA-1f
HASAg
HOMO
RNAO
RNCS
TPC
1.0000
0.6112
0.3162
ꢀ0.1244
RNDB
MNRI
PNSA-1
HASA
1.0000
1.0000
0.2377
0.1154
ꢀ0.0570
ꢀ0.4512
0.2532
1.0000
0.2644
ꢀ0.6185
1.0000
ꢀ0.2046
1.0000
ꢀ0.0410
1.0000
1.0000
a
b
c
d
e
f
RNAO: Relative number of aromatic bonds.
RNCS: Relative negative charged SA.
TPC: Tot point-charge comp. of the molecular dipole.
RNDB : Relative number of double bonds.
MNRI: Max nucleoph. react. index for a N atom.
PNSA-1: Partial negative surface area.
g
HASA: H-acceptors surface area.
Table 4
The 1H and 13C NMR chemical shifts values in d6-DMSO (ppm) of the new compounds.
Assignments
(1a)
(1b)
(1c)
(1d)
(1)
(2)
(3)
1H NMR data
CACH3
NACH3
NH2
–
2.30(s,3H)
2.61(s,3H)
–
–
–
–
–
–
–
–
2.60(s,3H)
–
–
–
–
–
8.60(s,1H)
10.31(s,1H)
6.90–7.58
2.60(s,3H)
–
–
–
–
–
9.98(s,1H)
12.85(s,1H)
8.05–7.31
2.97(s,3H)
–
–
–
–
–
8.73(s,1H)
–
7.19–8.43
3.31(s,3H)
3.81(s,2H)
–
–
–
–
–
–
–
–
–
–
–
n.o.
7.15(br)
NH
8.44(br)
CH2(a)
CH2(b)
CH(c)
N@CH
OH
2.83(t,2H)
3.59(t,2H)
–
2.88(d,2H)
2.66(d,2H)
3.87(s,1H)
–
7.15 (br)
6.51–7.30
–
12.93(s,1H)
7.43–6.97
5.18(s,1H)
8.44(br)
ArH
8.12–7.63
13C NMR data
CACH3
NACH3
CH2(a)
CH2(b)
CH(c)
–
15.55
36.97
–
–
–
–
–
–
–
–
–
35.22
–
–
–
37.01
–
–
–
37.02
–
–
–
40.46
–
–
–
45.42
60.08
–
42.47
40.59
64.87
–
N@CH
141.61
133.60
161.10
156.02
–
–
–
ArC
158.22 –117.13
130.45 –119.81
164.01 –112.25
144.09 –122.11
148.13 –125.95
134.10 –125.77
129.07 –128.04
117.13 ppm. In the 1H NMR spectra of (2) and (3), a very broad
band at ꢁ8.4 ppm and ꢁ7.4 ppm are assigned to overlapped NH,
OH and aromatic proton peaks, respectively.
methyl group stretching vibrations of (1) were found at
ꢁ2974 cmꢀ1
.
IR spectra Characteristic vibration of the compounds were sum-
marized in Table 5. Asymmetric and symmetric NH2 stretching
Antimicrobial activity
vibrations of (1) were observed between 3140 and 3100 cmꢀ1
.
The synthesized compounds and reference drugs (tetracycline,
trymethoprim, miconazole and nystatin) were screened in vitro
against various pathogens. Their minimum inhibitory concentra-
tions (MICs) were given in Table 6, and diameter of the inhibition
zones (mm) were tabulated in Table 7. As seen in Table 3, the
compound (1) is the most potent sulfonamide among this series.
(1) is a very hydroscopic compound, existence of hydrogen bond-
ing shifted its stretching vibrations towards lower wave numbers
than we expected. The vibration observed at ꢁ1608 cmꢀ1 of (3)
is assigned to
D(NH2) in-plane bending vibration. Secondary alco-
hol stretching vibration of (3) was shown at 1113 cmꢀ1. Terminal
Table 5
Wave numbers (cmꢀ1) of selected vibration bands of the new compounds.
Compounds
m
as(NH2)a
m
s(NH2)b
m
(NH)c
D
(NH2)d
m
as(SO2)
m
s(SO2)
D
(SO2)
m
(CN)
m
(CO)
(1)
(2)
(3)
(1a)
(1b)
(1c)
(1d)
3141
–
3360
–
–
–
–
3100
–
3331
–
–
–
–
–
1600
–
n.o
–
–
1249
1361
1334
1295
1329
1344
1316
1157
1151
1156
1180
1150
1162
1166
3290
501
525
561
517
531
520
n.oe
–
–
–
1659
1606
1636
1617
1258
1271
1265
–
–
–
–
–
–
a
b
c
t
t
t
as: asymmetric stretching.
s: symmetric stretching.
: stretching.
d
e
D
: bending.
n.o: not observed.

334
H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
Table 6
Antimicrobial activity of the new compounds with microdilution method (
l
g/mL).
Eae
125
Pfa
Pab
Ecc
Kpd
Saf
Bcg
Bsh
Sei
Ef
Cak
j
(1)
(2)
(3)
(1a)
(1b)
(1c)
(1d)
62.5
1000
1000
500
1000
250
62.5
1000
1000
1000
1000
250
125
125
125
125
125
125
250
>2000
1000
1000
500
1000
1000
500
1000
500
>2000
1000
1000
1000
250
1000
1000
1000
1000
500
>2000
>2000
250
>2000
>2000
500
>2000
1000
500
>2000
>2000
250
>2000
>2000
500
500
500
250
500
250
250
500
250
125
500
500
125
1000
1000
500
500
500
1000
125
125
125
125
250
a
b
c
d
e
f
P. fluorescens ATCC 49838.
P. aeruginosa ATCC 27853.
E. coli ATCC 25922.
K. pneumonia ATCC 13883.
E. aerogenes ATCC 13048.
S. aureus ATCC 25923.
B. cereus ATCC 11778.
B. subtilis ATCC 6633.
g
h
i
S. epidermidis ATCC 2228.
E. faecalis ATCC 29212.
C. albicans ATCC 90028.
j
k
It showed good antibacterial activity against both Gram-negative
bacteria (P. fluorescens at 62.5 g/mL, K. pneumonia at 125 g/mL,
E. coli at 125 g/mL, P. aeruginosa at 62.5 g/mL) and Gram-posi-
tive bacteria (S. aureus 125 g/mL, B. Cereus 125 g/mL, E. faecalis
250 g/mL, B. subtilis 125 g/mL, S. epidermidis 125 g/mL, E. aerog-
enes 125 g/mL), and also antifungal activity against C. albicans at
>2000 g/mL. In sulfonyl hydrazone series, compound (1d)
showed observable activity against Gram-negative bacteria
(P. fluorescens at 125 g/mL, K. pneumonia at 125 g/mL, E. coli at
125 g/mL, P. aeruginosa at 125 g/mL) and Gram-positive bacteria
(B. subtilis 125 g/mL, S. epidermidis 125 g/mL).
of them synthesized earlier by us, were taken to perform the 2D-
QSAR analysis.
l
l
l
l
l
l
l
QSAR analysis
l
l
l
Structures of 28 sulfonyl hydrazones and their antimicrobial
activity against E. coli ATCC 25922 and S. aureus ATCC 25923 were
listed in Table 1. In Table 2, four-parameter models obtained by
using BMLR method are given in decreasing relevance order
according to their statistical significance (ordered by t-test value).
l
l
l
l
l
l
l
In these tables, X and
DX are regression coefficients of the QSAR
equation and their standard errors, respectively. A graphical pre-
sentation of the relationship between the experimental and the
predicted pMIC values for training sets are given in Fig. 2.
Structure–activity relationships
In the QSAR model for E. coli, the most important descriptor is
total point-charge component of the molecular dipole. This is an
electrostatic descriptor and related with charge and polarizability.
It presumably contributes general electrostatic interactions. Its po-
sitive coefficient indicates that activity of the compounds increases
when the charge is distributed throughout the molecule. The sec-
ond important descriptor is HOMO energy. HOMO energy level de-
scribes global and local nucleohilicity in cases of non-covalent
molecular interactions. In general, a high-lying HOMO molecular
orbital assumes a charge or electron transfer from the compound
to the receptor. The third descriptor, relative number of aromatic
bonds, is defined as the ratio of the number of aromatic bonds to
the total number of bonds. The fourth descriptor is relative nega-
tive charged surface area (RNCS). It is an electrostatic descriptor
and it deals with the features responsible for polar interactions be-
tween molecules. This descriptor is sensitive to both the size and
the charge of the molecule.
In the QSAR model for S. aureus, the most important descriptor
is partial negative surface area (PNSA-1). It is responsible for polar
interactions between molecules. The larger value of the descriptor
indicates the higher polarity of the molecule. The positive regres-
sion coefficient for this descriptor reflects the fact that the larger
value of this descriptor leads to higher binding ability. The second
important descriptor is maximum nucleophilic reactivity index for
a N atom, which describes the tendency of a molecule to act as an
nucleophile in a chemical reaction, in other words, it is related to
electron transfer between the donor and the acceptor. Due to the
positive sign of the regression coefficient, the higher the descriptor
value is, (the molecule will act as a stronger nucleophile) the
higher its antimicrobial effect will be. The third descriptor is
H-acceptors surface area (HASA). It is related with hydrogen bond
Sulfonamide (1) showed good activity against Gram-negative
bacteria, however, its sulfonyl hydrazones (1a–1d) showed moder-
ate activity against both Gram-positive bacteria except C. albicans.
According to disk diffusion data, reference drugs showed better
activity than our compounds in all tested strains. Antimicrobial
activities of the sulfonamides bearing hydroxyl group (2–3) were
remarkably lower than that of (1). It may be attributed that an in-
crease in hydrophilicity of the sulfonamides would cause their
antimicrobial activity to decrease. As seen in Table 8, logP values
(0.34, ꢀ0.44, ꢀ1.03) and hydration energy values (ꢀ7.92, ꢀ12.81,
ꢀ13.89 kcal/mol) of three sulfonamides (1–3) decrease as their
activity decreases.
Thiophene ring-containing sulfonyl hydrazone (1d) showed the
best antimicrobial activity against microorganism, however, the
compound (1d) was found to be inactive against C. albicans. This
result is perhaps not surprising as thiophene ring skeleton is
widely found in many biologically active compounds [40], for
example, Biotin (Vitamin H) is a tetrahydrothiophene. Naphtha-
lene-containing sulfonyl hydrazones (1c) showed the second best
antimicrobial activity. It is known that naphthalene groups can
form cation–pi interaction and aromatic pi-stacking. When elec-
tron rich naphthalene encounters a cation or a positively charged
group on protein, receptor site bonds the aromatic ring to make
charge-transfer complex. This feature corresponds to some param-
eter such as RNABs (Relative number of aromatic bonds), RNBRs
(Relative number of benzene rings), MPPBO (Max pi–pi bond or-
der) (Table 8). As seen in Table 5, these parameters correlate with
antibacterial activities of our compounds. However, to find a quan-
titative structure activity relationship, we need to perform statisti-
cal analysis. For this reason, a set of analog sulfonyl hydrazones, all

H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
335
Table 7
Antimicrobial activity of the new compounds (150
lg/disk) with disk diffusion method.
Pfa
Pab
Ecc
Kpd
Eae
Saf
Bcg
Bsh
Sei
Efj
Cak
(1)
(2)
22
0
19
0
18
0
17
0
16
0
19
0
15
0
16
0
14
0
15
0
0
0
(3)
0
0
0
0
0
0
0
0
0
0
0
(1a)
(1b)
(1c)
(1d)
12
11
26
25
19
0
6
5
13
11
17
17
23
0
6
6
23
21
12
0
6
5
13
10
19
12
0
37
0
0
11
10
26
25
19
0
9
9
14
12
16
15
19
29
0
11
9
17
0
0
27
0
14
12
16
0
0
0
25
24
23
31
0
18
17
0
28
0
28
24
26
20
0
Tetracycline (30
l
g)
l
Trymethoprim (30
Miconazole (30 g)
Nystatin (40 g)
g)
l
0
0
0
0
0
0
0
0
26
18
l
0
0
0
0
0
a
b
c
d
e
f
P. fluorescens ATCC 49838.
P. aeruginosa ATCC 27853.
E. coli ATCC 25922.
K. pneumonia ATCC 13883.
E. aerogenes ATCC 13048.
S. aureus ATCC 25923.
B. cereus ATCC 11778.
B. subtilis ATCC 6633.
g
h
i
S. epidermidis ATCC 12228.
E. faecalis ATCC 29212.
C. albicans ATCC 90028.
j
k
Table 8
Some physicochemical properties of the new compounds.
(1)
(2)
(3)
(1a)
2.19
(1b)
2.33
(1c)
3.31
(1d)
ALOGPsa 0.34
ꢀ0.44
ꢀ1.03
2.23
ꢀ6.60
0.35
b
D
Hh
ꢀ7.92
ꢀ12.81
ꢀ13.89
ꢀ11.07
ꢀ8.83
ꢀ9.42
RNABc
RNBRd
0.27
0.25
0.0417
0.4741
0.21
0.0345
0.4803
0.34
0.31
0.41
0.0455
0.0588 0.0541 0.0750 0.0333
0.8716 0.8781 0.8926 0.8614
MPPBOe 0.4789
a
b
c
ALOGPs: Lipophilicity.
Hh: Hidration energy.
RNAB: Relative number of aromatic bonds.
RNBR: Relative number of benzene rings.
MPPBO: Max pi–pi bond order.
D
d
e
Fig. 3. Plot of experimental versus predicted pMIC values of test sets of E. coli and S.
aureus.
formation and intermolecular interactions. It is known that polar
interaction between molecules is directly related to the hydrogen
bond or Lewis basicity of the molecule. The fourth descriptor is rel-
ative number of double bonds.
In order to confirm our QSAR equations, we have predicted the
antimicrobial activity of the sulfonyl hydrazone in the test set. A
graphical presentation of the relationship between the experimen-
tal and the predicted pMIC values for test sets are given in Fig. 3.
Observed and predicted values are very close to each other. The
test set has an acceptable external correlation coefficient (R2 > 0.9).
Fig. 2. Plot of experimental versus predicted pMIC values of training sets of E. coli
and S. aureus.

336
H.G. Aslan et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 98 (2012) 329–336
[11] M. Karabacak, E. Postalcilar, M. Cinar, Spectrochim. Acta Part A 85 (2012) 261–
From the model equation, we can predict that (i) point-charge
270.
on molecule affect the antimicrobial activity of the sulfonyl hydra-
zone (ii) presence of aromatic groups increase the antimicrobial
activity (iii) sulfonyl hydrazones act as Lewis base (or nucleophile)
in intermolecular interaction.
[12] H. Alyar, A. Ünal, N. Özbek, S. Alyar, N. Karacan, Spectrochim. Acta Part A
<http://dx.doi.org/10.1016/j.saa.2012.01.065>.
[13] H.A. Aslan, S. Ozcan, N. Karacan, Inorg. Chem. Commun. 14 (2011) 1550–1553.
[14] N. Özbek, S. Alyar, N. Karacan, J. Mol. Struct. 938 (2009) 48–53.
[15] N. Özbek, G. Kavak, Y. Özcan, S. Ide, N. Karacan, J. Mol. Struct. 919 (2009) 154–
159.
[16] N. Özbek, H. Katircioglu, N. Karacan, T. Baykal, Bioorg. Med. Chem. 15 (2007)
7494.
Conclusion
[17] N.I. Dodoff, U. Ozdemir, N. Karacan, M. Georgieva, S.M. Konstantinov, M.E.
Stefanova, Z Nat. 54B (1999) 1553–1562.
Obtained results demonstrate that antimicrobial activities of
the sulfonamide is higher than that of corresponding sulfonyl
hydrazones, and presence of OH group on sulfonamide reduces
the antimicrobial activity. 2D-QSAR analysis was carried out on a
series of aromatic sulfonyl hydrazones as antimicrobial agents
against E. coli and S. aureus. According to the four-descriptor QSAR
model, total point-charge component of the molecular dipole,
HOMO energy, relative number of aromatic bonds and relative
negative charged surface area play a key role in the antimicrobial
activity of E. coli, however, partial negative surface area, maximum
nucleophilic reactivity index for a N atom, H-acceptors surface area
and relative number of double bonds are containing descriptors in
the QSAR model for S. aureus. Briefly, aromatic sulfonyl hydrazones
act as nucleophile in intermolecular interactions, and more aro-
matic bonds increase the antimicrobial activity.
[18] National Committee for Clinical Laboratory Standards (NCCLS), Methods for
Dilution Antimicrobial Susceptibility Tests for Bacteria that Grow Aerobically,
fifth ed. Approved Standards, M7-A5. NCCLS, Wayne, PA, 2000.
[19] National Committee for Clinical Laboratory Standards (NCCLS), Performance
Standards for Antimicrobial Disk Susceptibility Tests, seventh ed. Approved
Standards, M2-A7. NCCLS, Wayne, PA, 2000.
[20] A.W. Bauer, W.M.M. Kirby, J.V. Sheris, M. Truck, Am. J. Clin. Pathol. 45 (1966)
493–496.
[21] S. Alyar, U.O. Ozmen, N. Karacan, J. Mol. Struct. 889 (2008) 144–149.
[22] A. Ienco, C. Mealli, P. Paoli, N.I. Dodoff, Z. Kantarci, N. Karacan, New J. Chem. 23
(1999) 1253–1260.
[23] O.S. Senturk, U. Ozdemir, S. Sert, N. Karacan, F. Ugur, J. Coord. Chem. 60 (2007)
229–235.
[24] U. Ozdemir, O.S. Senturk, S. Sert, N. Karacan, F. Ugur, J. Coord. Chem. 59 (2006)
1905–1911.
[25] U. Ozdemir, N. Karacan, O.S. Senturk, S. Sert, F. Ugur, Syn. React. Inorg. Metal.
34 (2004) 1057–1067.
[26] S. Sert, O.S. Senturk, U. Ozdemir, N. Karacan, F. Ugur, J. Coord. Chem 57 (2004)
183–188.
[27] O.S. Senturk, U. Ozdemir, S. Sert, N. Karacan, Inorg. Chem Commun. 6 (2003)
926–929.
Acknowledgements
[28] U. Ozdemir, N. Karacan, O.S. Senturk, S. Sert, F. Ugur, J. Trans. Metal. Chem. 28
(2003) 443–446.
[29] U.O. Ozmen, G. Olgun, Spectrochim. Acta A 70 (2008) 641–645.
[30] U.O. Ozdemir, P. Guvenc, E. Sahin, F. Hamurcu, Inorg. Chim. Acta 362 (2009)
2613–2618.
[31] U.O. Ozdemir, F. Arslan, F. Hamurcu, Spectrochim. Acta A 75 (2010) 121–126.
[32] M.J. Frisch et al. Gaussian, Inc., Pittsburgh PA., Gaussian 03 (Revision B.04),
2003.
The authors thank the TUBITAK (No. 104 T 390) and Gazi Uni-
versity BAP (No. 05/2007-01) for the financial support of this
project.
References
[33] <http://www.vcclab.org/lab/alogps/>.
[1] S. Rachakonda, L. Cartee, Curr. Med. Chem. 11 (2004) 775–793.
[2] C. Walsh, Antibiotics Actions Origins Resistance, ASM, Washington, DC, 2003.
[3] World Health Organisation (WHO) Geneva, World Health Report-2002, 2002.
[4] C. Nathan, Nature 431 (2004) 899.
[5] F. von Nussbaum, M. Brands, B. Hinzen, S. Weigand, D. Häbch, Angew. Chem.
Int. Ed. 45 (2006) 5072.
[6] C.M. Sharaby, Spectrochim. Acta Part A 66 (2007) 1271–1278.
[7] C.M. Sharaby, G.G. Mohamed, M.M. Omar, Spectrochim. Acta Part A 66 (2007)
935–948.
[34] HyperChem 7.5 program (2002) Hypercube Inc., Toronto, Canada.
[35] M. Karelson, Molecular Descriptors in QSAR/QSPR, John Wiley & Sons., New
York, 2000. pp. 143–187 221–237.
[36] A.R. Katritzky, L.M. Pacureanu, S.H. Slavov, D.A. Dobchev, D.O. Shah, M.
Karelson, Comput. Chem. Eng. 33 (2009) 321–332.
[37] A. Katritsky, M. Karelson, V.S. Lobanov, R. Dennington, T. Keith, CODESSA
2.7.10., Semichem, Inc., Shawnee, KS, 2004.
[38] R.T. Hrubiec, K. Shyam, L.A. Cosby, A.C. Sartorelli, J. Med. Chem. 29 (1986)
1777–1779.
[8] N.S. El-Sayed, E.R. El-Bendary, S.M. El-Ashry, M.M. El-Kerdawy Eur, J. Med.
Chem. 46 (2011) 3714–3720.
[39] A.E. Kretov, G.V. Tikhonova, Chem. Technol. Inst., Dnepropetrovsk, Zhurnal
Obshchei Khimii 29 (1959) 412–415.
[9] K.N. de Oliveira, P. Costa, J.R. Santin, L. Mazzambani, C. Burger, C. Mora, R.J.
Nunes, M.M. de Souza, Bioorg. Med. Chem. 19 (2011) 4295–4306.
[10] A. Chandran, Y.S. Mary, H.T. Varghese, C.Y. Panicker, P. Pazdera, G. Rajendran,
Spectrochim. Acta Part A 79 (2011) 1584–1592.
[40] Salo Gronowitz, The Thiophene and Its Derivatives: Pt.4, John Wiley & Sons
Inc., 1991.