Isonicotinic acid hydrazide derivatives: Synthesis, antimicrobial activity, and QSAR studies

Article abstract of DOI:10.1007/s00044-011-9662-9

A series of isonicotinic acid hydrazide derivatives (1-19) was synthesized and tested in vitro for antimycobacterial activity against Mycobacterium tuberculosis and antimicrobial activity against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Candida albicans, and Aspergillus niger and the results indicated that the compounds with OH, SCH₃, and OCH ₃ groups were found to be active against the tested strains. None of the test compounds were active against a broad variety of RNA and DNA viruses at subtoxic concentrations, except 8, that showed some selective anti-reovirus-1 activity. The multi-target QSAR models were found to be effective in predicting the antimicrobial activity of the isoniazid derivatives and indicated the importance of nuclear repulsion energy (Nu.E) in explaining the antimicrobial activity of isoniazid derivatives. The developed QSAR models were validated using the external test set of synthesized derivatives. Springer Science+Business Media, LLC 2011.

Full text of DOI:10.1007/s00044-011-9662-9

MEDICINAL
CHEMISTRY
RESEARCH
Med Chem Res (2012) 21:1451–1470
DOI 10.1007/s00044-011-9662-9
ORIGINAL RESEARCH
Isonicotinic acid hydrazide derivatives: synthesis, antimicrobial
activity, and QSAR studies
•
Vikramjeet Judge Balasubramanian Narasimhan Munish Ahuja
•
•
•
Dharmarajan Sriram Perumal Yogeeswari Erik De Clercq
•
•
•
Christophe Pannecouque Jan Balzarini
Received: 10 March 2011 / Accepted: 5 May 2011 / Published online: 21 May 2011
ꢀ Springer Science+Business Media, LLC 2011
Abstract A series of isonicotinic acid hydrazide deriva-
tives (1–19) was synthesized and tested in vitro for antimy-
cobacterial activity against Mycobacterium tuberculosis
and antimicrobial activity against Staphylococcus aureus,
Bacillus subtilis, Escherichia coli, Candida albicans, and
Aspergillus niger and the results indicated that the com-
pounds with OH, SCH3, and OCH3 groups were found to be
active against the tested strains. None of the test compounds
were active against a broad variety of RNA and DNA viruses
at subtoxic concentrations, except 8, that showed some
selective anti-reovirus-1 activity. The multi-target QSAR
models were found to be effective in predicting the antimi-
crobial activity of the isoniazid derivatives and indicated the
importance of nuclear repulsion energy (Nu.E) in explaining
the antimicrobial activity of isoniazid derivatives. The
developed QSAR models were validated using the external
test set of synthesized derivatives.
Keywords Isoniazid derivatives ꢀ Antimycobacterial ꢀ
Antiviral ꢀ Antimicrobial ꢀ QSAR
Introduction
Tuberculosis (TB), caused by the infectious agent Myco-
bacterium tuberculosis, is one of the most important killing
infectious diseases. According to alarming data from the
World Health Organization (WHO), TB has spread to
every corner of the globe. As much as one third of the
world’s population is currently infected, and more than
5,000 people die from TB everyday (Sriram et al., 2009).
The factors responsible for this are: (i) patient non-com-
pliance to existing drug regimens which has resulted in the
emergence of single drug-resistant strains to all major anti-
TB drugs; (ii) emergence of multidrug-resistant TB (MDR-
TB), which is defined as the disease caused by the strains of
M. tuberculosis resistant to two mainstay first-line anti-TB
drugs, isoniazid and rifampicin; and (iii) association of
human immunodeficiency virus (HIV) with TB, in which
TB is the leading cause of death among patients who are
HIV-positive. Consequently, new drugs with divergent and
unique structure and with a mechanism of action possibly
different from that of existing drugs are urgently required
(Nayyar et al., 2007).
V. Judge ꢀ M. Ahuja
Department of Pharmaceutical Sciences, Guru Jambheswar
University of Science and Technology, Hisar 125001, India
B. Narasimhan (&)
Faculty of Pharmaceutical Sciences, Maharshi Dayanand
University, Rohtak 124001, India
e-mail: naru2000us@yahoo.com
AIDS is caused by a retrovirus, the human immunode-
ficiency virus (HIV). Two genetically distinct subtypes
(HIV-1 and HIV-2) have been characterized, but it is
known that the prime etiological agent of AIDS is HIV-1
(Canoa et al., 2006). Combination therapy or highly active
antiretroviral therapy (HAART) with two or more reverse
transcriptase inhibitors and protease inhibitors (PIs) has
dramatically improved the quality of life and survival of
patients infected with human immunodeficiency virus
D. Sriram ꢀ P. Yogeeswari
Medicinal Chemistry Research Laboratory, Pharmacy Group,
Birla Institute of Technology and Science,
Hyderabad 500078, India
E. De Clercq ꢀ C. Pannecouque ꢀ J. Balzarini
Laboratory of Virology & Chemotherapy, Rega Institute
for Medical Research, Minderbroedersstraat 10, 3000 Leuven,
Belgium
123

1452
Med Chem Res (2012) 21:1451–1470
(HIV) type 1 (HIV-1). However, the ability to provide
effective long-term antiretroviral therapy for HIV-1 infec-
tion has become a complex issue, since 40–50% of those
who initially achieved favorable viral suppression to
undetectable levels have experienced treatment failure
(Koh et al., 2003).
et al., in press; Kumar et al., 2010a, b), we hereby report
the synthesis, antitubercular, anti-HIV, antimicrobial, and
QSAR studies of isoniazid derivatives.
Experimental
In the past 25 years, the incidence of microbial infec-
tions has increased an alarming level over the world as
result of antimicrobial resistance. A growing number of
immuno-compromised patients are as a result of cancer
chemotherapy, organ transplantation, and HIV infection
which are the major factors contributing to this increase.
The health problems demand to search and synthesize a
new class of antimicrobial compounds effective against
pathogenic microorganisms that developed resistance to
the antibiotics used in the current regimen (Bayrak et al.,
2009a).
Melting points were determined in open capillary tubes on
a Sonar melting point apparatus and are uncorrected.
Reaction progress was monitored by thin layer chroma-
tography on silica gel sheets (Merck silica gel-G) and the
purity of the compounds was ascertained by single spot on
TLC sheet. 1H nuclear magnetic resonance (1H NMR)
spectra were recorded in Bruker Avance II 400 NMR
spectrometer using appropriate deuterated solvents and are
expressed in parts per million (d, ppm) downfield from
tetramethylsilane (internal standard). Infrared (IR) spectra
were recorded on a Shimadzu FTIR spectrometer.
Quantitative structure–activity relationship (QSAR)
research has been considered a major tool in drug discov-
ery to explore the ligand receptor/enzyme interactions,
especially when the structural details of the target are not
known. QSAR is an effective way for optimizing or cor-
relating the biological activity within a congeneric series
with certain structural features or with functional deter-
minants, such as lipophilicity, polarizability, or electronic
and steric properties (Sivaprakasam et al., 2006). QSAR
models are mathematical equations which construct a
relationship between chemical structures and their biolog-
ical activities as a linear regression model of the form
y = Xb ? e. This equation may be used to describe a set of
predictor variables (X) with a predicted variable (y) by
means of a regression vector (b). In a typical QSAR study
one needs to find a set of molecular descriptors repre-
senting the higher impact on the biological activity of
interest (Sabet et al., 2010).
General procedure for synthesis of ester of isonicotinic
acid
The mixture of isonicotinic acid (0.1 mol) and ethanol (in
excess) was refluxed with sulfuric acid (1–2 ml) till the
completion of reaction monitored by TLC on silica gel G
plates. Then the reaction mixture was added to 200 ml ice
cold water and excess of acid was neutralized by a solution
of sodium bicarbonate. The crude ester was extracted with
ether. The ether layer was separated and ester was obtained
on evaporation of ether layer.
General procedure for the synthesis of isonicotinic acid
hydrazide
The ethanolic solution of ester (0.01 mol) and hydrazine-
hydrate (0.015 mol) was refluxed for appropriate time. The
reaction mixture was then cooled and the precipitated solid
was washed with water, dried, and recrystallized from
ethanol.
Isonicotinic acid hydrazide (Isoniazid; INH) and pyra-
zinamide (PZA) are widely applied as a first line drugs for
the treatment of tuberculosis, usually in combination with
other drugs. Modifying either of these molecules has been a
challenge taken up by several research groups (Imramovsky
et al., 2007). Furthermore, the pharmacokinetic properties
and cellular permeability of a drug can be modulated by
derivatization to bioreversible forms of this drug, namely
hydrazones (Sriram et al., 2006). Isoniazid derivatives have
been reviewed by Scior and Garces-Eisele (2006) and
antitubercular evaluation of novel series of 3-benzofuran-5-
aryl-1-pyrazolyl-pyridylmethanone analogs derived from
isoniazid have been reported (Manna and Agrawal, 2010).
Recently, antimicrobial properties of isoniazid have also
been studied (Bayrak et al., 2009a, b; Rodriguez-Arguelles
et al., 2007). In light of above facts and in continuation of
our research endowed toward the synthesis, antimicrobial,
antimycobacterial, antiviral, and QSAR studies (Judge
General procedure for the synthesis of schiff bases
of isoniazid
The solution of isonicotinic acid hydrazide (0.01 mol) and
appropriate substituted aldehyde (0.01 mol) in ethanol was
refluxed for 4–5 h. The precipitates obtained were filtered
off, washed, and recrystallized from ethanol.
Isonicotinic acid -3-ethoxy-4-hydroxybenzylidene
hydrazide (1)
1
Mp (ꢁC) above 242; Yield—65.3%; H NMR (400 MHz,
CDCl3) d ppm: 3.87 (t, 3H, CH3), 4.17–4.20 (q, 2H, CH2),
123

Med Chem Res (2012) 21:1451–1470
1453
General procedure for the synthesis of N1-benzoylated
schiff bases of isoniazid
6.89–6.91 (s, 1H, OH), 7.06–7.08 (s, 1H, CH of C2 of
phenyl ring), 7.97 (d, 2H, CH of C5 and C6 of phenyl ring),
8.37 (d, 2H, CH of C2 and C6 of pyridine ring), 8.79 (d, 2H,
CH of C3 and C5 of pyridine ring), 11.71 (s, 1H, NH). IR
(KBr pellets) m cm-1: 3254.34 (NH str., amide), 3093.31
(CH str., aromatic), 2973.58 (CH str., aliphatic), 1644.86
(C=O str., amide), 1593.74 (C=C str., skeletal phenyl
nucleus), 1276.12 (C–O–C str., aralkyl ether), 1255.95 (OH
bending), 845.53 (CH out of plane bending, 4-substituted
pyridine).
The Schiff base (0.01 mol) obtained above was dissolved
in dichloromethane to which an equimolar amount of
benzoyl chloride, obtained by refluxing benzoic acid with
thionyl chloride, was added with stirring for 2 h. The crude
products were separated out by evaporating dichloro-
methane and recrystallized from ethanol to yield the pure
compounds.
Benzoic acid N0-(4-hydroxy-3-methoxy-benzylidene)-N-
(pyridine-4-carbonyl)-hydrazide (10)
Isonicotinic acid-3,4,5-trimethoxybenzylidene
hydrazide (4)
Mp (ꢁC) 230–233; Yield—57.8%; 1H NMR (400 MHz,
DMSO) d ppm: 3.70 (s, 3H, OCH3), 3.84 (s, 3H, OH),
7.28–7.38 (m, 5H, CH of phenyl ring), 7.46–7.50 (m, 3H, CH
of benzylidene ring), 7.70 (s, 1H, CH of N=CH), 7.91–7.94
(d, 2H, CH of C3 and C5 of pyridine ring), 8.77 (d, 2H, CH of
C2 and C6 of pyridine ring). IR (KBr pellets) m cm-1: 3414.15
(OH str.), 3036.09 (CH str., aromatic), 2904.92 (CH str.,
aliphatic), 1680.07 (C=O str., acyl group), 1597.13 (C=O
str., amide), 1513.22 (C=C str., skeletal phenyl nucleus),
1285.61 (C–O–C str., aralkyl ether), 814.96 (CH out of plane
bending, 4-substituted pyridine).
Mp (ꢁC) 205–208; Yield—80.7%; 1H NMR (400 MHz,
DMSO) d ppm: 3.36 (s, 9H, OCH3), 7.21–7.23 (s, 2H, CH
of C2 and C6 of trimethoxy phenyl ring), 7.83–7.84 (d, 2H,
CH of C3 and C5 of pyridine ring), 8.44 (s, 1H, CH of
N=CH), 8.73–8.76 (d, 2H, CH of C2 and C6 of pyridine
ring), 11.91 (s, 1H, NH). IR (KBr pellets) m cm-1: 3168.22
(NH str., amide), 2983.04 (CH str., aliphatic), 1682.00
(C=O str., amide), 1583.63 (C=C str., skeletal phenyl
nucleus), 1248.96 (C-O-C str., aralkyl ether), 858.36 (CH
out of plane bending, 4-substituted pyridine).
Isonicotinic acid-4-methylbenzylidene hydrazide (5)
Benzoic acid N0-(4-methylsulfanyl-benzylidene)-N-
(pyridine-4-carbonyl)-hydrazide (12)
Mp (ꢁC) 198–201; Yield—84.6%; 1H NMR (400 MHz,
DMSO) d ppm: 3.28 (s, 3H, CH3), 6.72–6.95 (m, 4H, CH
of phenyl ring), 7.76–7.77 (d, 2H, CH of C3 and C5 of
pyridine ring), 8.32 (s, 1H, CH of N=CH), 8.68–8.69 (d,
2H, CH of C2 and C6 of pyridine ring), 11.90 (s, 1H, NH).
IR (KBr pellets) m cm-1: 3177.86 (NH str., amide), 2935.78
(CH str., aliphatic), 1682.96 (C=O str., amide), 1583.63
(C=C str., skeletal phenyl nucleus), 1240.0 (C–O–C str.,
aralkyl ether), 835.21 (CH out of plane bending, 4-substi-
tuted pyridine).
Mp (ꢁC) 226–229; Yield—45.8%; 1H NMR (400 MHz,
DMSO) d ppm: 2.48 (s, 3H, SCH3), 7.11–7.20 (m, 3H, CH
of C3, C4 and C5 phenyl ring), 7.34–7.37 (d, 2H, CH of C2,
and C6 phenyl ring), 7.62–7.64 (d, 2H, CH of C3 and C5
of benzylidene ring), 7.91–7.93 (d, 2H, CH of C2 and C6 of
benzylidene ring), 8.21–8.23 (d, 2H, CH of C3 and C5 of
pyridine ring), 8.52 (s, 1H, CH of N=CH), 8.86–8.87 (d,
2H, CH of C2 and C6 of pyridine ring). IR (KBr pellets) m
cm-1: 3014.87 (CH str., aromatic), 1667.53 (C=O str., acyl
group), 1596.16 (C=O str., amide), 1497.79 (C=C str.,
skeletal phenyl nucleus), 609.53 (C–S str.), 732.98 (CH out
of plane bending, 4-substituted pyridine).
Isonicotinic acid-1-H-indol-3lmethylene hydrazide (8)
Mp (ꢁC) 225–228; Yield—61.9%; 1H NMR (400 MHz,
DMSO) d ppm: 7.07–7.16 (m, 2H, CH of C5 and C6 of
indole ring), 7.36–7.38 (m, 2H, CH of C4 and C7 of indole
ring), 7.53–7.54 (m, 2H, CH of C2 of indole ring),
7.80–7.81 (d, 2H, CH of C3 and C5 of pyridine ring), 8.60
(s, 1H, CH of N=CH), 8.68–8.71 (d, 2H, CH of C2 and C6
of pyridine ring), 11.24 (s, 1H, NH of indole), 11.57 (s, 1H,
NH of hydrazide). IR (KBr pellets) m cm-1: 3173.04 (NH
str., amide), 3052.48 (CH str., aromatic), 2940.61 (CH str.,
aliphatic), 1634.74 (C=O str., amide), 1428.35 (NH str.,
indole ring), 739.73 (CH out of plane bending, indole ring),
847.75 (CH out of plane bending, 4-substituted pyridine).
Benzoic acid N0-(4-methyl-benzylidene)-N-(pyridine-4-
carbonyl)-hydrazide (14)
Mp (ꢁC) 220–223; Yield—62.7%; 1H NMR (400 MHz,
DMSO) d ppm: 2.31 (s, 3H, CH3), 7.07–7.49 (m, 5H, CH
of phenyl ring), 7.59–7.61 (d, 2H, CH of C3 and C5
of benzylidene ring), 7.91–7.93 (d, 2H, CH of C2 and C6 of
benzylidene ring), 8.56–8.57 (d, 2H, CH of C3 and C5 of
pyridine ring), 8.68 (s, 1H, CH of N=CH), 8.93–8.94 (d,
2H, CH of C2 and C6 of pyridine ring). IR (KBr pellets)
123

1454
Med Chem Res (2012) 21:1451–1470
m cm-1: 3004.26 (CH str., aromatic), 1653.07 (C=O str.,
acyl group), 1593.27 (C=O str., amide), 1486.22 (C=C str.,
skeletal phenyl nucleus), 841.00 (CH out of plane bending,
4-substituted pyridine).
subtilis, Gram-negative bacterium: Escherichia coli and
fungal strains: Candida albicans and Aspergillus niger by
tube dilution method (Cappucino and Sherman, 1999).
Dilutions of test and standard compounds [norfloxacin
(antibacterial) and fluconazole (antifungal)] were prepared
in double strength nutrient broth I.P. (bacteria) and Sab-
ouraud dextrose broth I.P. (Pharmacopoeia of India, 2007)
(fungi). The samples were incubated at 37ꢁC for 24 h
(bacteria), at 25ꢁC for 7 days (A. niger), and at 37ꢁC for
48 h (C. albicans), and the results were recorded in terms
of MIC (the lowest concentration of test substance which
inhibited the growth of microorganisms).
General procedure for the synthesis of N2-acyl
isonicotinic acid hydrazides (17–19)
The corresponding carboxylic acids (0.01 mol) were
refluxed with thionyl chloride (0.015 mol) for 3 h. After
refluxing was complete, the excess thionyl chloride was
distilled off to get the acyl chloride. The isonicotinic acid
hydrazide (0.01 mol) was suspended in dichloromethane
and respective acyl chloride (0.01 mol) was added drop-
wise to this solution with constant stirring on a magnetic
stirrer for 3–4 h. The product obtained after evaporation of
dichloromethane was recrystallized from ethanol.
QSAR studies
The structures of isonicotinyl hydrazide derivatives were
first pre-optimized with the Molecular Mechanics Force
Field (MM?) procedure included in Hyperchem 6.03
(1993) and the resulting geometries are further refined by
means of the semiempirical method PM3 (Parametric
2-Chloro-5-nitro-benzoic acid N0-(pyridine-4-carbonyl)-
hydrazide (17)
˚
Method-3). We chose a gradient norm limit of 0.01 kcal/A
1
Mp (ꢁC) 200–203; Yield—56.30%; H NMR (400 MHz,
for the geometry optimization. The lowest energy structure
was used for each molecule to calculate physicochemical
properties using TSAR 3.3 software for Windows (TSAR
3D Version 3.3, 2000). Further, the regression analysis was
performed using the SPSS software package (1999). The
predictive powers of the equation were validated by
determination of cross-validated r2 (q2) using leave one out
(LOO) cross-validation method (Schaper, 1999).
DMSO) d ppm: 7.79–7.81 (d, 2H, CH of C3 and C4 of
phenyl ring), 8.32 (s, 1H, CH of C5 of phenyl ring),
8.51–8.53 (d, 2H, CH of C3 and C5 of pyridine ring),
9.14–9.17 (d, 2H, CH of C2 and C6 of pyridine ring), 10.44
(s, 1H, NH proton of N2), 11.20 (s, 1H, NH proton of N1).
IR (KBr pellets) m cm-1: 3132.53 (NH str., amide), 3083.34
(CH str., aromatic), 1708.04 (C=O str., Nicotinoyl),
1677.18 (C=O str., Acyl), 1528.65 (NO2 asymmetric str.,
aromatic nitro group), 1339.62 (NO2 symmetric str., aro-
matic nitro group), 1273.07 (C–N str., coupled vibrations
amide), 841.00 (CH out of plane bending, 4-substituted
pyridine), 739.73 (OCN deformations, amide IV band),
667.40 (OCN deformations, amide VI band).
Calculation of statistical parameters
The developed QSAR models were validated by the cal-
culation of following statistical parameters : probable error
of the coefficient of correlation (PE), least square error
(LSE), Friedman’s lack of fit measure (LOF), standard
error of prediction (SEP), quality value (Q), and sum of
squares of response values (SSY) (Mandloi et al., 2005;
Pinheiro et al., 2004].
Evaluation of antimycobacterial activity
All compounds were screened for their in vitro antimyco-
bacterial activity against MTB, in Middlebrook 7H11agar
medium supplemented with OADC by agar dilution
method similar to that recommended by the National
Committee for Clinical Laboratory Standards for the
determination of MIC in triplicate (1995). The minimum
inhibitory concentration (MIC) is defined as the minimum
concentration of compound required to give complete
inhibition of bacterial growth.
These parameters were calculated from the following
equations:
ꢀ
ꢁ
p
PE ¼ 2 1 ꢁ r2 =3 n
where r is the correlation coefficient and n is the number of
compounds used.
2
LSE ¼ RðYobs ꢁ Ycalc
Þ
where Yobs and Ycalc are the observed and calculated values,
respectively.
Evaluation of antimicrobial activity (determination
of minimum inhibitory concentration)
2
LOF ¼ LSE=f1 ꢁ ðC þ d ꢀ p=nÞg
where LSE is the least square error, C is the number of
descriptors ?1, p is the number of independent parameters,
The antimicrobial activity was performed against Gram-
positive bacteria: Staphylococcus aureus and Bacillus
123

Med Chem Res (2012) 21:1451–1470
1455
n is the number of compounds used, d is the smoothing
parameter which controls the bias in the scoring factor
between equations with different number of terms and was
kept 1.0.
soon as it reached completion in the control virus-infected
cell cultures that were not treated with the test compounds.
p
Results and discussion
SEP ¼ LSE=n
The quality value, Q, is given by
Chemistry
Q ¼ r=SE
The synthesis of target compounds was carried out as
depicted in Scheme 1. The isonicotinic acid was refluxed
with ethanol in the presence of sulfuric acid to get the ethyl
ester of isonicotinic acid. The ester thus obtained was
refluxed with hydrazine hydrate to obtain the isonicotinic
acid hydrazide. The isonicotinic acid hydrazide was
refluxed with various substituted aldehydes to yield the
target hydrazones (1–9, 15). Furthermore, the reaction of
compounds 1–3, 5, 6, and 15 with benzoyl chloride, which
was prepared by refluxing benzoic acid with thionyl chlo-
ride, resulted in the formation of benzoylated derivatives
10–14, 16. All the compounds were obtained in appreciable
yield and their physicochemical characteristics are pre-
sented in Table 1.
where Q is the quality value, r is the correlation coefficient,
and SE is the standard error.
The predictive ability of QSAR models was also quan-
tified in terms of q2, which is defined as
n
.
o
2
2
q2¼ 1 ꢁ RðYobs ꢁ Ycalc
Þ
RðYobs ꢁ YmeanÞ
The low value of PE, LSE, LOF, and SEP and high value
of Q and q2 are the essential criteria for qualifying the
model as the best one.
Evaluation of anti-HIV activity
The anti-HIV activity and cytotoxicity were evaluated
against HIV-1 strain IIIB and HIV-2 ROD in MT-4 cell
cultures using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphe-
nyltetrazolium bromide (MTT) method (Pauwels et al.,
1988). Briefly, virus stocks were titrated in MT-4 cells and
expressed as the 50% cell culture infective dose (CCID50).
MT-4 cells were suspended in culture medium at 1 9 105
cells/ml and infected with HIV at a multiplicity of infection
of 0.02. Immediately after viral infection, 100 ll of the cell
suspension was placed in each well of a flat-bottomed
microtiter tray containing various concentrations of the test
compounds. After a 4-day incubation period at 37ꢁC, the
number of viable cells was determined using the MTT
method. Compounds were tested in parallel for cytotoxic
effects in uninfected MT-4 cells.
The structures of synthesized compounds were ascer-
tained on the basis of their consistent IR an NMR spectral
characteristics. The presence of singlet signal above d
11.50 ppm in compounds 1, 2, 3, 4, 5, 6, 7, 8, and 9 reveals
the presence of the proton NH and it disappears in the
compounds 10, 11, 12, 13, 14, and 16.
The presence of singlet signal around d 8.0 ppm con-
firms the presence of N=CH linkage in the synthesized
compounds. In all the synthesized compounds two doublet
signals were observed at two different d values, with the
one at higher d value corresponds to C2 and C6 CH protons
as they are in close proximity of the electronegative
nitrogen atom in the ring and the doublet signal at lower d
represents the remaining two protons of the isonicotinyl
nucleus. The singlet signal due to NH at d 11.24 ppm in
compound 8 confirms the presence of the indole nucleus in
the synthesized compounds. The appearance of multiplet
signals in the aromatic region in compounds 10, 12, and 14
confirmed the existence of an acyl group in these com-
pounds. The singlet signal at d 3.28 ppm confirms the
presence of a methyl group in compound 5. The singlet
signal at d 3.36 ppm confirms the presence of a 3,4,5-tri-
methoxy group in compound 4. The presence of CH3 group
in compound 5 was depicted by the singlet signal at d
3.28 ppm. The singlet signal at d 2.48 ppm corresponding
to the SCH3 group confirms the presence of thiomethyl
group in compound 12.
Antiviral assays
The antiviral assays [except anti-human immunodeficiency
virus (HIV) assays] were based on inhibition of virus-
induced cytopathicity in HEL [herpes simplex virus type 1
(HSV-1), HSV-2 (G), vaccinia virus, and vesicular stoma-
titis virus], Vero (parainfluenza-3, reovirus-1, Sindbis,
Coxsackie B4, and Punta Toro virus), HeLa (vesicular
stomatitis virus, Coxsackie virus B4, and respiratory syn-
cytial virus) cell cultures. Confluent cell cultures in
microtiter 96-well plates were inoculated with 100 cell
culture inhibitory dose-50 (CCID50) of virus (1 CCID50
being the virus dose to infect 50% of the cell cultures) in the
presence of varying concentrations (100, 20, 4, … lg/ml) of
the test compounds. Viral cytopathicity was recorded as
The presence of the C=O functional group was
marked by the appearance of stretching band around
1680–1640 cm-1, in compounds 1, 4, 5, and 8 which is
123

1456
Med Chem Res (2012) 21:1451–1470
O
O
SOCl2
R'COCl
R'COOH
17-19
N
NH2
OH
OC2H5
H
C
R1
O
R2
R3
R4
NH
N
O
O
O
R1
OHC
R5
C
H OH
5
2
NH NH
R5
2
2
R2
R4
Reflux
R3
N
1-6, 15
N
N
N
OH
O
RCHO
O
SOCl
2
Cl
O
NH
N
O
CH
R
N
N
CH
R1
R2
R5
O
R4
N
R3
N
7-9
10-14, 16
Comp.
1
R1
R2
R3
R4
R5
R
R’
H
OC2H5
OH
OH
H
H
H
H
-
-
H
OCH3
H
H
-
-
-
-
-
-
-
-
-
-
-
2
3
4
5
6
7
OCH3
H
OCH3
H
H
H
-
OCH3
OCH3
CH3
SCH3
-
OCH3
H
H
H
-
H
H
-
H
H
-
HO
8
9
-
-
-
-
-
-
-
-
-
-
-
-
N
H
CH3
H
H
OCH3
OH
OH
SCH3
H
H
H
H
H
H
H
H
-
H
H
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
10
11
12
13
14
15
16
17
OC2H5
H
H
H
H
H
H
-
H
OCH3
H
OCH3
H
CH3
H
OH
OH
-
H
H
H
-
-
Cl
O2N
18
19
-
-
-
-
-
-
-
-
-
-
-
-
Cl
Cl
H3C
Scheme 1 Synthetic route followed for the synthesis of isoniazid derivatives
123

Med Chem Res (2012) 21:1451–1470
1457
Table 1 Physicochemical properties and antimycobacterial activity of synthesized isoniazid derivatives
Compound
Mol. formula
Mol. wt.
Melting pt. (ꢁC)
Rfa
% yield
MIC MTB-
H37Rv (lM 9 10-3
)
Training set
1
2
C15H15N3O3
285
271
285
315
239
271
291
264
189
375
389
375
389
343
Above 242
238–241
193–196
205–208
198–201
175–178
239–242
225–228
187–190
230–233
234–237
226–229
215–218
220–223
0.78
0.74
0.69
0.71
0.68
0.57
0.59
0.64
0.52
0.45
0.43
0.40
0.51
0.44
65.3
71.2
68.5
80.7
84.6
71.5
56.8
61.9
74.5
57.8
60.4
45.8
63.9
62.7
11
12
C14H13N3O3
C15H15N3O3
C16H17N3O4
C14H13N3O
C14H13N3OS
C17H13N3O2
C15H12N4O
C10H11N3O
C21H17N3O4
C22H19N3O4
C21H17N3O2S
C22H19N3O4
C21H17N3O2
3
11
4
20
5
52
6
12
7
21
8
24
9
17
10
11
12
13
14
Test set
15
16
17
18
19
INH
ETBb
CFL
RIFb
a
[67
[64
[67
[64
[73
C13H11N3O2
C20H15N3O3
C13H9N4O4Cl
C13H10N3O2Cl
241
345
320
275
227
230–233
214–217
200–203
216–219
235–238
0.65
0.48
0.71
0.63
0.69
50.60
52.4
52
[72
56.30
71.40
51.80
4.9
22.7
55.1
C9H10N3O2Cl
2.04
15.31
9.4
0.24
Mobile phase: ethanol
b
Sriram et al. (2007)
Antimycobacterial activity
characteristic of the amide linkage. The vibrational fre-
quency C=O functional group shifts to a lower frequency
around 1597–1593 cm-1, in compounds 10, 12, and 14,
which may be due to substitution of NH proton with acyl
group. The NH stretching of secondary amide was
observed around 3200–3100 cm-1 in compounds 1, 4, 5,
and 8 and this characteristic peak disappeared in the
spectra of compounds 10, 12, and 14. The presence of
peaks slightly above and below 3000 cm-1 indicates the
presence of an aromatic and aliphatic portion in the
synthesized compounds, respectively. The skeletal C=C-
stretching bands were observed around 1500 cm-1 in the
spectra of the synthesized compounds which represents
the presence of aromatic groups. In compounds 1, 4, and 5
the C-O–C stretching was observed at 1276.12, 1248.96,
and 1240.0 cm-1, which reveals the presence of a meth-
oxy group in their structure. The CH out of plane bending
observed around vibrational frequency of 860–814 cm-1
indicated the presence of the 4-substituted pyridine ring in
the structure of the synthesized compounds.
The in vitro antitubercular activity of synthesized com-
pounds against M. tuberculosis (MTB) was carried out in
Middlebrook 7H11agar medium supplemented with OADC
by agar dilution method and the results are presented in
Table 1. The results of antitubercular activity indicated that
the synthesized derivatives were active against M. tubercu-
losis (MTB) with an MIC of 11 9 10-3 lM which approa-
ches the antitubercular potential of ciprofloxacin. The
antimycobacterial potential of compounds 1, 2, 3, and 6 was
found to be better than standard drug ethambutol (ETB). It
was observed from the results of antimycobacterial activity
that compounds with free OH group at para position (com-
pounds 1 and 2) in their molecular structure were more active
as compared to other derivatives which may be due the fact
that free OH group may be involved in the binding of the
drug with the receptor site of the Mycobacterium. It can also
be seen from the antimycobacterial activity data that
when we replaced the OH group with electron donating CH3
123

1458
Med Chem Res (2012) 21:1451–1470
6. The presence of electron withdrawing NO2 and Cl
groups in the molecular structure (compound 17) leads
to a steep increase in antimycobacterial activity.
group (compound 5), a fall in activity was observed
(52 9 10-3 lM) but if we substituted the CH3 group with
SCH3 group (compound 6), an abrupt rise in activity was
observed (12 9 10-3 lM). This may be attributed to the fact
that, similar to the binding of the OH group with the target
site, SCH3 group containing free lone pair of electrons was
involved in the binding of structure with the target site. The
substitution of phenyl ring of the aldehydes with naphthalene
nucleus (compound 7) showed antimycobacterial potential
but the replacement of the naphthalene with the heterocyclic
indole nucleus (compound 8) leads to a fall in antitubercular
activity of the synthesized isoniazid derivatives. The sub-
stitution of NH proton of hydrazide with acyl group,
C6H5CO, leads to decrease in antimycobacterial activity of
synthesized derivatives (compounds 10, 11, 12, 13, and 14)
which shows that the NH proton is necessary for antimyco-
bacterial activity.
Cytostatic, cytotoxic, and antiviral activities
The compounds were in general poorly cytotoxic against
HEL, HeLa, and Vero cell cultures (except 7 that showed
an MCC of C20 lg/ml for HEL, but 0.2 to C0.8 lg/ml for
HeLa and Vero cell cultures). Instead, their cytostatic
activities ranged between 0.10 lg/ml (compound 7) and
C100 lg/ml depending the nature of the compounds
(Table 2). Generally, none of the compounds were inhibi-
tory to HIV (Table 2) or any of the other RNA or DNA
viruses tested at subtoxic concentrations. Compound 7
showed anti-HSV-1, -HSV-2, and -VV activity at EC50
values of 0.06–0.4 lg/ml (Table 3), but given the potent
cytostatic activity of this compound, it is unclear whether
this represents a direct antiviral effect or, more likely, an
The test set compounds 15–19 were also evaluated for
their antimycobacterial activity and compound 17 was
highly active antimycobacterial agent with MIC value
4.9 9 10-3 lM and was twice active than ciprofloxacin
and thrice active than ethambutol.
Table 2 Anti-HIV potential of synthesized isoniazid derivatives in
MT-4 cells
From the results of antimycobacterial activity the fol-
lowing conclusions regarding structure activity relationship
(SAR) can be drawn:
Compound
EC50 (lg/ml)
CCa50 (lg/ml)
HIV-1 (IIIb)
HIV-2 (ROD)
1. From the appreciable antimycobacterial activity of
compounds 1 and 2 it may be concluded that the
presence of a free hydroxyl group at para position,
OH, is necessary for antimycobacterial activity.
2. The substitution of the OH group with an electron
donating CH3 (compound 5) decreases the antimyco-
bacterial activity. These results are similar to the
reports of Sriram et al. (2007) who observed that the
addition of a methyl group decreases the antimyco-
bacterial activity of N-hydroxythiosemicarbazones.
3. The replacement of the benzylidene ring with a
naphthalene ring (compound 7) or a heterocyclic
indole ring (compound 8) did not improve the
antimycobacterial activity. This is similar to one of
our previous reports (Kumar et al., 2009).
1
[102
[89
[102
[89
102 20
2
C89
3
[9
[9
9
4.5
4
[110
[25
[110
[25
110 12
5
25
59
9
8
6
[59
[59
7
[0.10
[95
[0.10
[95
0.10 0.01
95 16
11 10
105 18
C92
8
9
[11
[11
10
[105
[92
[105
[92
11
12
[69
[69
69
8
13
[12
[12
12 0.9
42 11
2.52 0.10
–
14
[42
[42
15
[2.52
NT
[2.52
NT
4. The presence of the OH group at ortho position
(compound 7) increases the activity of the compounds.
This is in concordance with Tripathi et al. (2006) who
stated that the OH group at ortho position leads to a
measurable change in activity of the compounds.
5. The substitution of the methyl group (compound 5)
with the more bulky thiomethyl group (compound 6)
increased the antimycobacterial activity. This is in
accordance with the results of Desai et al. (2001) who
reported that addition of a bulkier group at the
4-position positively contributes to the antimycobac-
terial activity.
16
17
[115.67
[120.00
[77.47
0.050 0.011
0.002 0.001
[115.67
[120.00
[77.47
[4.0
115.67 6.03
[120.00
77.47 58.50
[4.0
18
19
Nevirapine
Zidovudine
0.002 0.001
[25
50% Effective concentration or compound concentration required to
inhibit virus-induced cytopathicity by 50%
NT not tested
a
50% Cytotoxic concentration or compound concentration required
to reduce MT-4 cell viability by 50%
123

Med Chem Res (2012) 21:1451–1470
1459
Table 3 Cytotoxicity and anti-
DNA virus activity of
synthesized isoniazid
Compound Minimum cytotoxic
concentrationa (lg/ml)
ECb50 (lg/ml)
Herpes simplex Herpes simplex Vaccinia virus Herpes simplex
virus-1 TK-
KOS ACVr
derivatives in HEL cell cultures
virus-1 (KOS) virus-2 (G)
1
[100
[100
[100
[100
[100
[100
C20
[100
[100
[100
[100
[100
[100
0.06
[100
[100
[100
[100
[100
[100
0.4
[100
[100
[100
[100
[100
[100
0.14
[100
[100
[100
[100
[100
[100
0.4
2
3
4
5
6
7
8
[100
100
[100
[20
[100
[20
[100
[20
[100
[20
9
a
10
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
[100
Required to cause a
microscopically detectable
alteration of normal cell
morphology
11
12
13
14
b
Required to reduce virus-
induced cytopathicity by 50%
Table 4 Cytotoxicity and anti-
RNA virus activity of
synthesized isoniazid
Compound
Minimum cytotoxic
concentrationa (lg/ml)
ECb50 (lg/ml)
Vesicular
stomatitis virus
Coxsackie
virus B4
Respiratory
syncytial virus
derivatives in HeLa cell cultures
1
[100
100
[100
[20
[100
[20
[20
[100
9
[100
[20
2
3
100
[20
[20
4
C100
100
[100
[20
[100
[20
5
6
100
[20
[20
[0.04
[100
[20
[20
[100
[100
[4
[20
7
0.2
[0.04
[100
[20
[0.04
[100
[20
8
C100
100
9
10
11
12
13
14
100
[20
[20
a
Required to cause a
[100
[100
20
[100
[100
[4
[100
[100
[4
microscopically detectable
alteration of normal cell
morphology
b
Required to reduce virus-
induced cytopathicity by 50%
100
[20
[20
[20
indirect cytostatic effect of the compound. Compounds 5,
6, 7, and 12 were found to be inhibitory to Coxsackie B4
virus in one cell line but not in another (Tables 4, 5).
Instead, compound 8 showed an EC50 of 2.4 lg/ml against
reovirus-1 in Vero cell cultures that is at a concentration
well below its toxicity threshold. This observed activity is
further under investigation.
positive S. aureus, B. subtilis, Gram negative E. coli and
antifungal activity against C. albicans and A. niger by the
serial dilution method (Cappucino and Sherman, 1999)
using norfloxacin and fluconazole as reference standards
for antibacterial and antifungal activities, respectively, and
the results are presented in Table 6.
For antibacterial activity against B. subtilis all the syn-
thesized derivatives were more active than the isoniazid. In
particular, the compounds 4 and 13 were found to be the most
effective antibacterial agents having pMICbs values 2.40 and
2.49 lM, respectively. The antibacterial activity value of
these compounds approaches the antibacterial potential of
Antibacterial and antifungal activities
The synthesized isoniazid derivatives (1–19) were evalu-
ated in vitro for their antibacterial activity against Gram-
123

1460
Med Chem Res (2012) 21:1451–1470
Table 5 Cytotoxicity and anti-RNA virus activity of synthesized isoniazid derivatives in Vero cell cultures
Compound
Minimum cytotoxic
concentrationa (lg/ml)
ECb50 (lg/ml)
Para
influenza-3 virus
Reovirus-1
Sindbis virus
Coxsackie
virus B4
Punta
Toro virus
1
[100
[100
100
[100
[100
[20
[100
[100
[20
[100
[100
[20
[100
[100
[20
[100
[20
9
[100
[100
[20
2
3
4
[100
C20
[100
[20
[100
[20
[100
[20
[100
[20
5
6
C100
C0.8
[100
100
[100
[0.8
[100
[20
[100
[0.8
2.4
[100
[0.8
[100
[20
[100
[0.8
[100
[20
7
[0.8
45
8
9
[20
[20
[100
[100
9
10
11
12
13
14
a
C100
[100
C100
100
[100
[100
[100
[20
[100
[100
[100
[20
[100
[100
[100
[20
[100
[100
[100
[20
[20
[20
C20
[20
[20
[20
[20
Required to cause a microscopically detectable alteration of normal cell morphology
b
Required to reduce virus-induced cytopathicity by 50%
Table 6 Antibacterial and antifungal potentials (lM/ml) of synthesized isoniazid derivatives
Compound
pMICbs
pMICsa
pMICec
pMICca
pMICan
pMICb
pMICf
pMICam
Training set
1
2
2.06
2.04
2.06
2.40
1.98
2.04
2.07
2.02
1.88
2.18
2.19
2.18
2.49
2.14
1.74
0.18
2.06
2.04
2.06
2.10
1.98
2.04
2.07
2.02
1.88
2.48
2.19
2.18
2.49
2.44
2.04
0.19
2.36
2.34
2.06
2.10
1.98
2.34
2.07
2.02
1.88
2.48
2.49
2.48
2.49
2.44
1.74
0.25
2.36
2.34
2.36
2.40
2.28
2.34
2.37
2.63
2.48
3.08
2.79
2.78
3.10
2.74
2.34
0.28
2.36
2.34
2.36
2.40
2.28
2.34
2.37
2.32
2.18
2.48
2.19
2.48
2.49
2.44
2.04
0.13
2.16
2.14
2.06
2.20
1.98
2.14
2.07
2.02
1.88
2.38
2.29
2.28
2.49
2.34
1.84
0.18
2.36
2.34
2.36
2.40
2.28
2.34
2.37
2.48
2.33
2.78
2.49
2.63
2.80
2.59
2.19
0.18
2.24
2.22
2.18
2.28
2.1
3
4
5
6
2.22
2.19
2.2
7
8
9
2.06
2.54
2.37
2.42
2.61
2.44
1.98
0.18
10
11
12
13
14
INH
SD
Test set
15
16
17
18
19
Std.
1.98
2.44
2.11
2.34
1.96
2.61a
1.98
1.84
2.11
2.34
2.26
2.61a
2.29
2.44
2.11
1.74
2.26
2.61a
2.29
3.04
2.41
2.64
2.26
2.64b
2.29
2.44
2.41
1.74
2.26
2.64b
2.08
2.24
2.11
2.14
2.16
2.61
2.29
2.74
2.41
2.19
2.26
2.64
2.17
2.44
2.23
2.16
2.20
2.62
SD standard deviation
a
b
Norfloxacin, Fluconazole
123

Med Chem Res (2012) 21:1451–1470
1461
4. The synthesized derivatives were more active toward
the Gram-negative bacterium E. coli than Gram-
positive B. subtilis and S. aureus. This finding is in
agreement with Sbardella et al. (2004).
the standard drug norfloxacin. In case of S. aureus, com-
pounds 10 and 13 have shown marked antibacterial potential
at pMICsa values 2.48 and 2.49 lM, respectively. For anti-
bacterial activity against E. coli compounds 10–13 had
shown better antibacterial activity with pMICec values of
2.48, 2.49, 2.48, and 2.49 lM, respectively.
The antifungal activity against C. albicans revealed that
compounds 10 and 13 were the potential candidates having
pMICca values 3.08 and 3.10 lM, respectively. The com-
pounds 10 and 13 have better antifungal activity than the
standard drug fluconazole. In case of A. niger compounds
10, 12, and 13 were found to be active with pMICan values
2.48, 2.48, and 2.49 lM, respectively.
5. The substitution of NH proton with acyl group
(compounds 10–14) leads to increase in activity of
the compounds. This may be due to the increase in
lipophilicity of the molecules which may allow them
to easily penetrate the microbial membrane. These
results are in agreement with the observations of
Imramovsky et al. (2007). These results are in contrast
with the results of antimycobacterial activity where the
activity decreases due to the N1-benzoylation.
6. The presence of substituent at ortho position increases
the antibacterial and antifungal potentials of the
compounds which can be seen from the antimicrobial
activity of compounds 3, 7, and 13. This fact is
supported by the observations of Guven et al. (2007).
7. Compound 17 was found to be highly active which
may be due to the presence of electron withdrawing
groups NO2 and Cl in its structure.
The test set compounds (15–19) were also active against
the tested microorganisms and compounds 16 and 18 were
the most active among them, with their antifungal activity
against C. albicans better than the standard drug
fluconazole.
It can be observed from the results presented in Table 6
that the synthesized isoniazid derivatives have higher
antifungal potential particularly against C. albicans. The
compounds were also found to be more active against
Gram-negative E. coli as compared to Gram-positive
B. subtilis and S. aureus.
8. Compound 16 having OH group at ortho position and
NH proton being replaced by benzoyl group was also
found to be highly active that may be attributed to the
free OH group and its increased lipophilicity.
Structure activity relationship
The SAR findings of the antimycobacterial and antimi-
crobial activities are summarized in Fig. 1.
From the results of antimicrobial activity, the following
structure activity the relationship can be drawn:
QSAR studies
1. The compounds have shown marked antifungal
potential as compared to antibacterial activity, which
shows that there are different structural requirements
are essential for antibacterial and antifungal activities.
These results are similar to those of Sortino et al.
(2007).
Development of one-target QSAR model
In order to identify the substituent effect on the antimi-
crobial activity, quantitative structure activity relationship
(QSAR) studies between the in vitro activity and descrip-
tors coding for lipophilic, electronic, steric, and topological
properties of the 14 synthesized isoniazid derivatives
(training set) were undertaken, using the linear free energy
relationship model (LFER) described by Hansch and Fujita
(1964). Biological activity data determined as MIC values
were first transformed into pMIC values (i.e., -log MIC)
and used as dependent variable in QSAR study. The dif-
ferent molecular descriptors (independent variables) like
log of octanol–water partition coefficient (log P), molar
2. It can also be seen from the results of antibacterial and
antifungal activities that the activity increases with the
addition of a bulkier substituent on the phenyl nucleus
of the synthesized compounds which can be easily
seen from the higher activity of compound 1 in
comparison to compounds 2 and 6 in comparison to
compound 5, respectively.
3. The results of antimicrobial activity depicted that the
presence of electron donating group, OCH3, enhanced
the antimicrobial activity of the synthesized deriva-
tives. It can be observed from the results of antimi-
crobial activity that compound 2 was active and the
addition of OCH3 group made it more active (com-
pound 3) and further addition of OCH3 (compound 4)
made the structure of the molecule highly active
against the tested strains. This is supported by results
of Emami et al. (2008).
refractivity (MR), Kier’s molecular connectivity (0v, vv,
0
1v, 1vv, 2v, 2vv) and shape (j1, j2, j3, ja1, ja2, ja3)
topological indices, Randic topological index (R), Balaban
topological index (J), Wiener topological index (W), total
energy (Te), energies of highest occupied molecular orbital
(HOMO) and lowest unoccupied molecular orbital
(LUMO), dipole moment (l), nuclear repulsion energy
(Nu.E) and electronic energy (Ele.E), calculated for
123

1462
Med Chem Res (2012) 21:1451–1470
Fig. 1 Structural requirements
for the antimycobacterial and
antimicrobial activities of
synthesized isoniazid
the antimicrobial activity
ses
Replacement with
acyl group
ses the antimycobacterial activity
derivatives
H
ses
the antimycobacterial and
antimicrobial activity
N
N
CH3
O
p-SC
H3
the antimycobacterial and
antimicrobial activity
ses
R
N
the antimycobacterial and
antimicrobial activity
o-OCH3
o/p- OH
ses
the antimycobacterial and
antimicrobial activity
ses
Essential for antimycobacterial
activity
obtained by LOO method, s is the standard error of the
estimate, and F is the Fischer statistics.
isoniazid derivatives are presented in Table 7 (Hansch
et al., 1973; Kier and Hall, 1976; Randic, 1975, 1993;
Balaban, 1982; Wiener, 1947). Units of the energies and
dipole were electron volts (eV) and atomic units (a.u.),
respectively (Dai et al., 1999).
For antibacterial activity against E. coli, the developed
QSAR model (Eq. 1) describes the importance of valence
first-order molecular connectivity topological index (1vv).
Topological indices are numerical quantifiers of molecular
topology and are sensitive to bonding pattern, symmetry,
content of heteroatom as well as degree of complexity of
atomic neighborhoods (Lather and Madan, 2005). The
valence first-order molecular connectivity topological
index (1vv) represents the molecules with branched struc-
ture. In this case, the positive correlation was observed
In this study, a data set of 15 compounds (14 isoniazid
derivatives along with isoniazid itself) was subjected to
linear free energy regression analysis for model generation.
Preliminary analysis was carried out in terms of correlation
analysis. A correlation matrix constructed for antibacterial
activity against E. coli is presented in Table 8. The correla-
tions of different molecular descriptors with antibacterial
and antifungal activities are presented in Table 9. In general,
high colinearity (r [ 0.8) was observed between different
parameters. The high interrelationship was observed
between 0v and 1v (r = 0.998) and low interrelationship was
observed between Te and l (r = 0.072). The correlation
matrix indicated the predominance of topological parame-
ters and electronic parameters in describing the antimicro-
bial activity of the synthesized compounds.
1
between vv and antibacterial activity against E. coli and
the results presented in Table 9 are in concordance with the
model expressed by Eq. 1 and values of 1vv shown in
Table 10 which depict that compounds 10, 11, 12, and 13
having high 1vv values (8.35, 8.93, 9.53, and 8.74) have got
the highest antibacterial potential (2.48, 2.49, 2.48, and
2.49).
The QSAR model expressed by Eq. 1 was cross-validated
by its high q2 values (q2 = 0.756) obtained with LOO
method. The value of q2 greater than 0.5 is the basic
requirement for qualifying a QSAR model to be valid one
(Golbraikh and Tropsha, 2002). The comparison of observed
and predicted antibacterial activities is presented in
Table 10. It can be seen from theresults that the observed and
predicted antibacterial activities lie close to each other as
evidenced by their low residual values (Table 10). The plots
of observed, predicted, and residual pMIC activity values
were also developed to check the statistical validity of QSAR
models. The plot of predicted pMICec against observed
pMICec (Fig. 2) also favors the model expressed by Eq. 1.
Further, the plot of observed pMICec versus residual pMICec
The antibacterial activity of synthesized isoniazid
derivatives against E. coli is governed by the valence first-
order molecular connectivity topological index (1vv)
(Eq. 1).
ot-QSAR model for antibacterial activity against E. coli
pMICec ¼ 0:1231vv þ 1:389
ð1Þ
n ¼ 15; r ¼ 0:893; q2 ¼ 0:756; s ¼ 0:118;
F ¼ 50:93:
Here and thereafter, n is the number of data points, r is the
correlation coefficient, q2 is the cross-validated, r2 is
123

Med Chem Res (2012) 21:1451–1470
1463
123

1464
Med Chem Res (2012) 21:1451–1470
Table 8 Correlation matrix for antibacterial activity of synthesized isoniazid derivatives against E. coli
log P
0v
0vv
1v
1vv
2v
2vv
3v
j1
W
Te
Ele.E
l
Nu.E pMICec
log P
0v
0vv
1v
1vv
2v
2vv
3v
1.000
0.851 1.000
0.863 0.992 1.000
0.865 0.998 0.992 1.000
0.902 0.958 0.980 0.966 1.000
0.884 0.992 0.982 0.997 0.963 1.000
0.921 0.949 0.969 0.960 0.995 0.963 1.000
0.853 0.970 0.949 0.970 0.920 0.981 0.928 1.000
0.835 0.997 0.991 0.991 0.951 0.980 0.935 0.957 1.000
0.839 0.985 0.972 0.981 0.943 0.976 0.932 0.958 0.982 1.000
-0.778 -0.991 -0.976 -0.985 -0.923 -0.974 -0.906 -0.959 -0.992 -0.975 1.000
-0.820 -0.992 -0.978 -0.987 -0.937 -0.978 -0.924 -0.959 -0.991 -0.995 0.988 1.000
-0.306 -0.137 -0.189 -0.132 -0.256 -0.125 -0.271 -0.125 -0.141 -0.229 0.072 0.189 1.000
0.824 0.991 0.977 0.986 0.937 0.977 0.925 0.958 0.989 0.996 -0.986 -1.000 -0.202 1.000
j1
W
Te
Ele.E
l
Nu.E
pMICec 0.794 0.869 0.878 0.864 0.893 0.864 0.878 0.863 0.873 0.857 -0.851 -0.848 -0.224 0.846 1.000
Table 9 Correlation of molecular descriptors with antimicrobial activity of synthesized derivatives
Mol. descriptor
pMICbs
pMICsa
pMICec
pMICca
pMICan
pMICb
pMICf
pMICam
log P
MR
0v
0vv
1v
1vv
2v
2vv
3v
0.573
0.813
0.847
0.854
0.837
0.775
0.808
0.755
0.780
0.698
0.857
0.851
0.867
0.854
0.837
-0.418
0.814
-0.868
-0.846
0.201
0.465
-0.126
0.843
0.682
0.743
0.773
0.744
0.767
0.700
0.771
0.715
0.798
0.704
0.764
0.710
0.739
0.658
0.767
-0.226
0.810
-0.759
-0.812
0.598
0.049
-0.444
0.817
0.794
0.877
0.869
0.878
0.864
0.893
0.864
0.878
0.863
0.851
0.873
0.869
0.876
0.860
0.864
-0.489
0.857
-0.851
-0.848
0.290
0.521
-0.224
0.846
0.676
0.739
0.750
0.725
0.752
0.706
0.747
0.702
0.706
0.615
0.743
0.717
0.718
0.668
0.752
-0.188
0.818
-0.728
-0.798
0.606
0.171
-0.376
0.805
0.655
0.759
0.737
0.763
0.746
0.748
0.739
0.761
0.708
0.753
0.729
0.712
0.734
0.709
0.746
-0.605
0.649
-0.717
-0.688
0.111
0.647
-0.062
0.683
0.784
0.923
0.941
0.937
0.933
0.903
0.925
0.894
0.924
0.859
0.942
0.921
0.939
0.900
0.933
-0.439
0.937
-0.935
-0.944
0.402
0.409
-0.295
0.944
0.754
0.841
0.842
0.831
0.846
0.811
0.840
0.812
0.796
0.741
0.833
0.806
0.815
0.767
0.846
-0.361
0.864
-0.817
-0.862
0.514
0.361
-0.313
0.866
0.798
0.919
0.931
0.924
0.928
0.895
0.920
0.890
0.903
0.840
0.929
0.905
0.920
0.876
0.928
-0.420
0.937
-0.917
-0.941
0.456
0.402
-0.312
0.942
3vv
j1
j2
ja1
ja2
R
J
W
Te
Ele.E
LUMO
HOMO
l
Nu.E
(Fig. 3) indicated that there was no systemic error in model
development as the propagation of error was observed on
both sides of zero (Kumar et al., 2007).
Equations 2–5 were developed to predict the antibacte-
rial and antifungal activities of isoniazid derivatives against
B. subtilis, S. aureus, C. albicans, and A. niger.
123

Med Chem Res (2012) 21:1451–1470
1465
Table 10 Comparison of observed and predicted antibacterial and antifungal activities obtained by ot-QSAR model
Compound
pMICec (Eq. 1)
pMICbs (Eq. 2)
pMICsa (Eq. 3)
pMICca (Eq. 4)
pMICan (Eq. 5)
Obs
Pre
Res
0.18
Obs
Pre
Res
Obs
Pre
Res
Obs
Pre
Res
Obs
Pre
Res
1
2.36
2.34
2.06
2.10
1.98
2.34
2.07
2.02
1.88
2.48
2.49
2.48
2.49
2.44
1.74
2.18
2.10
2.15
2.22
2.07
2.25
2.21
2.14
1.90
2.42
2.49
2.56
2.46
2.38
1.73
2.06
2.04
2.06
2.40
1.98
2.04
2.07
2.02
1.88
2.18
2.19
2.18
2.49
2.14
1.74
2.10
2.07
2.10
2.18
1.96
2.00
2.08
2.02
1.87
2.29
2.32
2.21
2.32
2.18
1.77
-0.04
-0.03
-0.04
0.22
2.06
2.04
2.06
2.10
1.98
2.04
2.07
2.02
1.88
2.48
2.19
2.18
2.49
2.44
2.04
2.10
2.07
2.12
2.18
2.01
2.04
2.11
2.06
1.93
2.32
2.36
2.28
2.37
2.25
1.87
-0.04
-0.03
-0.06
-0.08
-0.03
0.00
2.36
2.34
2.36
2.40
2.28
2.34
2.37
2.63
2.48
3.08
2.79
2.78
3.10
2.74
2.34
2.51
2.46
2.48
2.59
2.38
2.42
2.52
2.45
2.26
2.84
2.92
2.79
2.89
2.71
2.18
-0.15
-0.12
-0.12
-0.19
-0.10
-0.08
-0.15
0.18
2.36
2.34
2.36
2.40
2.28
2.34
2.37
2.32
2.18
2.48
2.19
2.48
2.49
2.44
2.04
2.32
2.30
2.33
2.37
2.27
2.32
2.33
2.29
2.21
2.43
2.45
2.45
2.46
2.41
2.13
0.04
0.04
2
0.24
-0.09
-0.12
-0.09
0.09
3
0.03
4
0.03
5
0.02
0.01
6
0.04
0.02
7
-0.14
-0.12
-0.02
0.06
-0.01
0.00
-0.04
-0.04
-0.05
0.16
0.04
8
0.03
9
0.01
0.22
-0.03
0.05
10
11
12
13
14
INH
Test set
15
16
17
18
19
-0.11
-0.13
-0.03
0.17
0.24
0.00
-0.17
-0.10
0.12
-0.13
-0.01
0.21
-0.26
0.03
-0.08
0.03
0.03
0.06
-0.04
-0.03
0.19
0.03
0.03
0.01
0.17
0.16
-0.09
2.29
2.44
2.11
1.74
2.26
2.04
2.35
2.17
2.11
1.97
0.25
0.09
1.98
2.44
2.11
2.34
1.96
1.98
2.20
2.18
2.04
1.96
0.00
0.24
1.98
1.84
2.11
2.34
2.26
2.02
2.27
2.16
2.06
1.98
-0.04
-0.43
-0.05
0.28
2.29
3.04
2.41
2.64
2.26
2.37
2.72
2.53
2.41
2.28
-0.08
0.32
2.29
2.44
2.41
1.74
2.26
2.26
2.39
2.33
2.29
2.24
0.03
0.05
-0.06
-0.37
0.29
-0.07
0.30
-0.12
0.23
0.08
-0.55
0.02
0.00
0.28
-0.02
.3
2.6
2.5
2.4
2.3
2.2
2.1
2.0
1.9
.2
.1
0.0
-.1
-.2
1.8
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
Observed pMICec
Observed pMICec
Fig. 3 Plot of residual pMICec against the experimental pMICec for
the linear regression model developed by Eq. 1
Fig. 2 Plot of observed pMICec against the predicted pMICec for the
linear regression model developed by Eq. 1
ot-QSAR model for antibacterial activity against B. sub-
tilis
ot-QSAR model for antibacterial activity against S. aur-
eus
pMICbs ¼ ꢁ0:00017Te þ 1:459
ð2Þ
pMICsa ¼ 0:000019Nu:E þ 1:750
ð3Þ
n ¼ 15; r ¼ 0:868; q2 ¼ 0:660; s ¼ 0:095;
n ¼ 15; r ¼ 0:817; q2 ¼ 0:500; s ¼ 0:112;
F ¼ 39:79:
F ¼ 26:05:
123

1466
Med Chem Res (2012) 21:1451–1470
The model described by Eq. 4 depicted the importance
of Wiener topological index (W) in describing the anti-
fungal activity against C. albicans. The Wiener index
(W) was introduced by Wiener (1947) to demonstrate the
correlations between the physicochemical properties of
organic compounds and the topological structure of their
molecular graphs in terms of sum of distances between any
two carbon atoms in the molecule.
ot-QSAR model for antifungal activity against C. albi-
cans
pMICca ¼ 0:00034W þ 2:134:
ð4Þ
n ¼ 15; r ¼ 0:818; q2 ¼ 0:532; s ¼ 0:165;
F ¼ 26:28:
ot-QSAR model for antifungal activity against A. niger
The model described by Eq. 5 demonstrated the
importance of valence first-order molecular connectivity
topological index (1vv) in describing the antifungal activity
against A. niger. The positive correlation of the molecular
descriptor with antifungal activity reveals that increase in
pMICan ¼ 0:03150vv þ 1:960
ð5Þ
n ¼ 15; r ¼ 0:763; q2 ¼ 0:351; s ¼ 0:084;
F ¼ 18:16:
1
the value of vv (Table 7) will lead to an increase in anti-
The model expressed by Eq. 2 demonstrated that
antibacterial activity against B. subtilis is governed by
the total energy of the molecule (Te). The total energy (Te)
calculated by semiempirical methods can be used as a
measure of non-specific interactions of the drug with its
target site, i.e., the total energies of protonated and neutral
molecule, can be considered as a good measure of
hydrogen bonds (the higher the energy, the stronger the
bond) and can be used to determine the correct localization
of the most favorable hydrogen bond acceptor site
(Karelson et al., 1996).
fungal activity against A. niger. The low residual values
presented in Table 10 are in agreement with the fact that
models expressed by Eqs. 2–5 are also valid ones.
As in case of Eq. 1, the high q2 values (q2 [ 0.5) sup-
ported the validity of developed QSAR models described
by Eqs. 2–4. The cross-validated correlation coefficient
(q2 [ 0.5) values obtained for best QSAR model indicated
their reliability in predicting the antimicrobial activity of
synthesized compounds. In case of A. niger the q2 (Eq. 5)
value is less than 0.5, which shows that the developed
model is an invalid one. But according to the recommen-
dations of Kim et al. (2007), the regression models are
acceptable if the value of standard deviation (SD, Table 6)
is not much larger than 0.3. As the value of standard
deviation in case of Eq. 5 is less than 0.3, i.e., 0.28, so the
developed model is a valid one. It is important to note that
Eqs. 1–5 were derived using the entire data set as there
were no outliers in the data set.
As the coefficient of total energy (Te) in Eq. 2 is nega-
tive, therefore, the antibacterial activity against B. subtilis
will increase with decreasing the Te values. This is clearly
evident from Table 6 that compounds 4, 11, and 13 having
low Te values -4181.98, -4977.37, and -4976.67
(Table 7) have highest antibacterial activity values of 2.40,
2.19, and 2.49 respectively. Similarly, compounds 5 and 9
having maximum Te values -2910.53 and -2370.69
(Table 7) have minimum antibacterial activity against B.
subtilis (Table 6).
Generally for QSAR studies, the biological activities of
compounds should span 2–3 orders of magnitude. But in
this study, the range of antibacterial and antifungal activ-
ities of the synthesized compounds is within one order of
magnitude. It is important to note that the predictability of
the QSAR models developed in this study is high evi-
denced by their low residual values. This is in accordance
with results suggested by the Bajaj et al. (2005), who stated
that the reliability of the QSAR model lies in its predictive
ability even though the activity data are in the narrow
range. Further, recent literature reveals that the QSAR have
been applied to describe the relationship between narrow
range of biological activity and physicochemical properties
of the molecules (Narasimhan et al., 2007; Sharma et al.,
2006; Hatya et al., 2006; Kumar et al., 2006). When bio-
logical activity data lie in the narrow range, the presence of
minimum standard deviation of the biological activity
justifies its use in QSAR studies (Kumar et al., 2007;
Narasimhan et al., 2007). The minimum standard deviation
(Table 6) observed in the antimicrobial activity data jus-
tifies its use in QSAR studies. The low value of PE, LSE,
In case of S. aureus, the developed QSAR model (Eq. 3)
indicated the predominance of nuclear repulsion energy in
describing the antibacterial activity. The nuclear repulsion
energy between two atoms (A and B) is given by
ENu:EðABÞ ¼ ZAZB=RAB
where A is the given atomic species, B is the another
atomic species, ZA is the charge of atomic nucleus A, ZB is
the charge of atomic nucleus B, and RAB is the distance
between the atomic nuclei A and B (Clementi, 1980).
The coefficient of nuclear repulsion energy (Nu.E) is
positive, which shows that the antibacterial activity will
increase with the increase in nuclear repulsion energy of
the synthesized compounds, which can be clearly seen
from the results of antibacterial activity against S. aureus
(Table 6) and values of nuclear repulsion energy presented
in Table 7 that compounds 10, 13, and 14 had the highest
antibacterial potential and compounds 5 and 9 had minimal
antibacterial activity.
123

Med Chem Res (2012) 21:1451–1470
1467
Table 11 PE, LSE, LOF, SEP, Q, SDEP, Spress, e-, and RMSE values calculated for the derived models for modeling antimicrobial activity of
synthesized isonicotinic acid-1-(substituted phenyl)-ethylidene/cycloheptylidene hydrazide derivatives
Equations
Descriptor
PE
LSE
LOF
SEP
Q
e-
RMSE
SDEP
Spress
1
2
3
4
5
6
7
8
1vv
0.035
0.042
0.057
0.057
0.073
0.019
0.043
0.019
0.178
0.116
0.163
0.352
0.090
0.052
0.110
0.047
0.045
0.029
0.041
0.088
0.023
0.004
0.007
0.012
0.028
0.023
0.027
0.040
0.020
0.015
0.022
0.015
7.57
0.088
0.061
0.085
0.139
0.051
0.050
0.072
0.043
0.109
0.088
0.104
0.153
0.078
0.059
0.086
0.056
0.18
0.09
0.11
0.16
0.08
0.06
0.09
0.06
0.19
0.16
0.15
0.27
0.09
0.17
0.16
0.17
Te
9.14
7.30
Nu.E
W
0vv
4.96
9.08
Ele.E
Nu.E
Nu.E
14.98
9.30
15.44
LOF, standard deviation of prediction (Spress), and standard
deviation error of predictions (SDEP) and SEP and high
value of r2 and Q (Table 11) revealed the statistical sig-
nificance of the developed QSAR models.
The mt-QSAR model for antibacterial activity displayed
the importance of electronic energy (Ele.E) in describing
the antibacterial activity of synthesized isoniazid deriva-
tives, represented as the model expressed by Eq. 6.
Development of multi-target QSAR model
mt-QSAR model for antibacterial activity
pMICb ¼ ꢁ0:0000192 Ele:E þ 1:684
ð6Þ
According to the above ot-QSAR models one should use
five different equations with different errors to predict the
activity of a new compound against the five microbial
species. The ot-QSAR models, which are almost in the
whole literature, become unpractical or at less complicated
to use when we have to predict to each compound results
for more than one target. In these cases, we have to develop
one ot-QSAR for each target. However, very recently the
interest has been increased in development of multi-target
QSAR (mt-QSAR) models. In opposition to ot-QSAR, the
mt-QSAR model is a single equation that considers the
nature of molecular descriptors which are common and
essential for describing the antibacterial and antifungal
activities (Prado-Prado et al., 2008; Gonzalez-Diaz et al.,
2007, 2008; Cruz-Monteagudo et al., 2007; Gonzalez-Diaz
and Prado-Prado, 2008).
n ¼ 15; r ¼ 0:944; q2 ¼ 0:852; s ¼ 0:063;
F ¼ 106:40:
The mt-QSAR model for antifungal and antimicrobial
activities revealed the importance of nuclear repulsion
energy (Nu.E) in describing antifungal activity and the
overall antimicrobial activity represented by Eqs. 7 and 8,
respectively.
mt-QSAR model for antifungal activity
pMICf ¼ 0:0000191Nu:E þ 2:057
ð7Þ
ð8Þ
n ¼ 15; r ¼ 0:865; q2 ¼ 0:636; s ¼ 0:093;
F ¼ 38:88:
mt-QSAR model for antimicrobial activity
In this study, we have attempted to develop three dif-
ferent types of mt-QSAR models viz. mt-QSAR model for
describing antibacterial activity of synthesized compounds
against S. aureus, B. subtilis, and E. coli, mt-QSAR model
for describing antifungal activity of synthesized com-
pounds against C. albicans and A. niger as well a common
mt-QSAR model for describing the antimicrobial (over-
all antibacterial and antifungal) activity of synthesized
isoniazid derivatives against all the above-mentioned
microorganisms.
pMICam ¼ 0:0000204Nu:E þ 1:849
n ¼ 15; r ¼ 0:942; q2 ¼ 0:835; s ¼ 0:061;
F ¼ 03:09:
It was observed from mt-QSAR models (Eqs. 6–8) that the
antibacterial, antifungal, and overall antimicrobial activities
of synthesized isoniazid derivatives is governed by energy
parameters, viz., nuclear repulsion energy (Nu.E) describing
the antifungal and overall antimicrobial potential and
electronic energy describing the antibacterial potential of
the isoniazid derivatives. The developed mt-QSAR models
were statistically valid as they had the high r and q2 values
and low residual values (Table 12). As in the case of ot-
QSAR models, the plot of predicted pMICam against
observed pMICam (Fig. 4) also favors the developed model
In order to develop mt-QSAR models, initially we have
calculated the average antibacterial, antifungal, and anti-
microbial activity values of isoniazid derivatives which are
presented in Table 6. These average activity values were
also correlated with the molecular descriptors of synthe-
sized compounds (Table 9).
123

1468
Med Chem Res (2012) 21:1451–1470
.1
0.0
-.1
-.2
Table 12 Comparison of observed and predicted antibacterial, anti-
fungal, and antimicrobial activities obtained by mt-QSAR model
Compound pMICb (Eq. 6)
Obs Pre Res
pMICf (Eq. 7)
Obs Pre Res
pMICam (Eq. 8)
Obs Pre Res
Training set
1
2
2.16 2.11 0.05 2.36 2.41 -0.05 2.24 2.23 0.01
2.14 2.08 0.06 2.34 2.38 -0.04 2.22 2.20 0.02
2.06 2.13 -0.07 2.36 2.43 -0.07 2.18 2.25 -0.07
2.20 2.20 0.00 2.40 2.49 -0.09 2.28 2.31 -0.03
1.98 2.01 -0.03 2.28 2.32 -0.04 2.10 2.13 -0.03
2.14 2.04 0.10 2.34 2.35 -0.01 2.22 2.16 0.06
2.07 2.13 -0.06 2.37 2.43 -0.06 2.19 2.24 -0.05
2.02 2.06 -0.04 2.48 2.37 0.11 2.20 2.18 0.02
1.88 1.92 -0.04 2.33 2.24 0.09 2.06 2.05 0.01
2.38 2.36 0.02 2.78 2.64 0.14 2.54 2.47 0.07
2.29 2.40 -0.11 2.49 2.67 -0.18 2.37 2.51 -0.14
2.28 2.31 -0.03 2.63 2.59 0.04 2.42 2.42 0.00
2.49 2.42 0.07 2.80 2.69 0.11 2.61 2.53 0.08
2.34 2.27 0.07 2.59 2.56 0.03 2.44 2.39 0.05
1.84 1.84 0.00 2.19 2.17 0.02 1.98 1.98 0.00
3
4
5
6
7
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
8
Observed pMICam
9
10
11
12
13
14
INH
Test set
15
16
17
18
19
Fig. 5 Plot of residual pMICam against the experimental pMICam
for the linear regression model developed by Eq. 8
PE, LSE, LOF, standard deviation of prediction (Spress) and
standard deviation error of predictions (SDEP) and SEP and
high value of r2 and Q (Table 11) revealed the statistical
significance of the developed QSAR models.
2.08 2.02 0.06 2.29 2.33 -0.04 2.17 2.14 0.03
2.24 2.29 -0.05 2.74 2.58 0.16 2.44 2.4
0.04
2.11 2.19 -0.08 2.41 2.48 -0.07 2.23 2.3 -0.07
2.14 2.07 0.07 2.19 2.37 -0.18 2.16 2.18 -0.02
2.16 1.84 0.32 2.26 2.17 0.09 2.20 1.97 0.23
Validation of predictability of developed QSAR models
using test set
In order to validate the predictability of the developed
QSAR models, we have synthesized a test set of five
compounds (15–19) and their antimicrobial activity values
were determined experimentally as well as predicted using
the developed QSAR models and the results are presented
in Tables 10 and 12. The results of the predicted antimi-
crobial activity indicated that the developed models were
efficiently predicting the antimicrobial activity of the
synthesized compounds with similar structure (compounds
15 and 16) as well as compound with slightly different
structures (compounds 17–19). The low residual values for
these compounds indicated that the developed QSAR
models were valid as they were predicting the antimicro-
bial activity quite effectively. The mt-QSAR models were
more precise in prediction as their residual values were
very low.
2.6
2.5
2.4
2.3
2.2
2.1
2.0
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
Observed pMICam
Fig. 4 Plot of observed pMICam against the predicted pMICam for
the linear regression model developed by Eq. 8
Conclusion
expressed by Eq. 8. Further, the plot of observed pMICam
versus residual pMICam (Fig. 5) indicated that there was no
systemic error in model development as the propagation of
error was observed on both sides of zero, i.e., both positive
and negativeresidual values were observed. The low valueof
A series of isoniazid derivatives (1–19) was synthesized
and tested for their in vitro antimycobacterial activity
against M. tuberculosis and the compounds with OH,
SCH3, and OCH3 groups were found to be active ones and
123

Med Chem Res (2012) 21:1451–1470
1469
different environmental or biological systems. J Comput Chem
28(11):1909–1923
Dai J, Sun C, Han S, Wang L (1999) QSAR for polychlorinated
compounds (PCOCs). I. Prediction of partition properties for
PCOCs using quantum chemical parameters. Bull Environ
Contam Toxicol 62:530–538
Desai B, Sureja D, Naliapara Y, Shah A, Saxena AK (2001) Synthesis
and QSAR studies of 4-substituted phenyl-2,6-dimethyl-3,5-
bis-N-(substituted phenyl)carbamoyl-1,4-dihydro- pyridines as
potential antitubercular agents. Bioorg Med Chem 9:1993–1998
Emami S, Foroumadi A, Falahati M, Lotfali E, Rajabalian S,
Ebrahimi FS, Shafiee A (2008) 2-Hydroxyphenacyl azoles and
related azolium derivatives as antifungal agents. Bioorg Med
Chem Lett 18:141–146
Golbraikh A, Tropsha A (2002) Beware of q2!. J Mol Graphics Model
20:269–276
Gonzalez-Diaz H, Prado-Prado FJ (2008) Unified QSAR and
network-based computational chemistry approach to antimicro-
bials, part 1: multispecies activity models for antifungals.
J Comput Chem 29(4):656–667
Gonzalez-Diaz H, Vilar S, Santana L, Uriarte E (2007) Medicinal
chemistry and bioinformatics—current trends in drugs discovery
with networks topological indices. Curr Top Med Chem 7(10):
1015–1029
Gonzalez-Diaz H, Gonzalez-Diaz Y, Santana L, Ubeira FM, Uriarte E
(2008) Networks and connectivity indices. Proteomics 8(4):
750–778
compound 17 synthesized in the test set was twice active
than ciprofloxacin and thrice active than ethambutol. The
results of antiviral activity testing showed that none of the
tested compounds was active against a broad variety of
RNA and DNA viruses at subtoxic concentrations, except
compound 8 that showed a selective anti-reovirus-1 activ-
ity. The synthesized compounds were also screened for
their antimicrobial potential against S. aureus, B. subtilis,
E. coli, C. albicans, and A. niger and the results of anti-
microbial activity were similar to the antimycobacterial
activity except that N1-acyl substituted derivatives (10–14)
were the most active antimicrobial agents. To understand
the relationship between physicochemical parameters and
antibacterial and antifungal activities of isoniazid deriva-
tives, QSAR investigation was performed by development
of one target and multi target models. The multi-target
model was found to be effective in describing the antimi-
crobial activity of isoniazid derivatives in comparison to
the one target models and indicated the importance of
nuclear repulsion energy (Nu.E). The external validation of
QSAR models was done by the prediction of antimicrobial
activity of test set compounds.
Guven OO, Erdogan T, Goker H, Yildiz S (2007) Synthesis and
antimicrobial activity of some novel phenyl and benzimidazole
substituted benzyl ethers. Bioorg Med Chem 17:2233–2236
Hansch C, Fujita T (1964) p-r-p analysis. A method for the
correlation of biological activity and chemical structure. J Am
Chem Soc 86:1616–1626
Hansch C, Leo A, Unger SH, Kim KH, Nikaitani D, Lien EJ (1973)
Aromatic substituent constants for structure-activity correlations.
J Med Chem 16:1207–1216
Acknowledgments The author (VJ) is thankful to Department of
Technical Education, Government of Haryana (India) for providing
fellowship to carry out the research project. We would like to thank
Mrs. Leentje Persoons, Mrs. Frieda De Meyer and Mrs. Leen Ingels,
Rega Institute for Medical Research, Belgium for excellent technical
assistance in the evaluation of antiviral activity.
Hatya SA, Aki-sener E, Tekiner-Gulbas B, Yildiz I, Temiz-Arpaci O,
Yalcin I, Altanlar N (2006) Synthesis, antimicrobial activity and
QSARs of new benzoxazine-3-ones. Eur J Med Chem 41:
1398–1404
References
Hyperchem 6.0 (1993), Hypercube, Inc., Gainesville
Imramovsky A, Polanc S, Vinsova J, Kocevar M, Jampilek J,
Reckova Z, Kaustova J (2007) A new modification of anti-
tubercular active molecules. Bioorg Med Chem 15:2511–2559
Judge V, Narang R, Sharma D, Narasimhan B, Kumar P Hansch
analysis for the prediction of antimycobacterial activity of
ofloxacin derivatives. Med Chem Res. doi: 10.1007/s00044-
010-9400-8 (in press)
Karelson M, Lobanov VS, Katritzky AR (1996) Quantum-chemical
descriptors in QSAR/QSPR studies. Chem Rev 96(3):1027–1044
Kier LB, Hall LH (1976) Molecular connectivity in chemistry and
drug research. Academic Press, New York
Kim YM, Farrah S, Baney RH (2007) Structure-antimicrobial activity
relationship for silanols, a new class of disinfectants, compared
with alcohols and phenols. Int J Antimicrob Agents 29:217–222
Koh Y, Nakata H, Maeda K, Ogata H, Bilcer G, Devasamudram T,
Kincaid JF, Boross P, Wang Y, Tie Y, Volarath P, Gaddis L,
Harrison RW, Weber IT, Ghosh AK, Mitsuya H (2003) Novel
bis-tetrahydrofuranylurethane containing nonpeptidic protease
inhibitor (PI) UIC-94017 (TMC114) with potent activity against
multi-PI-resistant Human Immunodeficiency Virus in vitro.
Antimicrob Agents Chemother 47(10):3123–3129
Bajaj S, Sambi SS, Madan AK (2005) Prediction of anti-inflammatory
activity of N-arylanthranilic acids: computational approach using
refined Zagreb Indices. Croat Chem Acta 78(2):165–174
Balaban AT (1982) Highly discriminating distance-based topological
index. Chem Phys Lett 89:399–404
Bayrak H, Demirbas A, Demirbas N, Karaoglu SA (2009a) Synthesis
of some new 1,2,4-triazoles starting from isonicotinic acid
hydrazide and evaluation of their antimicrobial activities. Eur J
Med Chem 44:4362–4366
Bayrak H, Demirbas A, Karaoglu SA, Demirbas N (2009b) Synthesis
of some new 1,2,4-triazoles, their mannich and schiff bases and
evaluation of their antimicrobial activities. Eur J Med Chem
44:1057–1066
Canoa P, Gonzalez-moa MJ, Teijeira M, Teran C, Uriarte E,
Pannecouque C, De Clercq E (2006) Synthesis and anti-HIV
activity of novel cyclopentenyl nucleoside analogues of 8-azap-
urine. Chem Pharm Bull 54(10):1418–1420
Cappucino JG, Sherman N (1999) Microbiology—a laboratory
manual. Addison Wesley Longman Inc, Redwood City, p 263
Clementi E (1980) Computational aspects of large chemical systems.
Springer, New York
Cruz-Monteagudo M, Gonzalez-Diaz H, Aguero-Chapin G, Santana
L, Borges F, Dominguez ER, Podda G, Uriarte E (2007)
Computational chemistry development of a unified free energy
Markov model for the distribution of 1300 chemicals to 38
Kumar A, Sharma P, Gurram VK, Rane N (2006) Studies on synthesis
and evaluation of quantitative structure–activity relationship of
10-methyl-6-oxo-5-arylazo-6,7-dihydro-5H-[1,3]azaphospholo
123

1470
Med Chem Res (2012) 21:1451–1470
[1,5-d][1,4]benzodiazepin-2-phospha-3-ethoxycarbonyl-1-phos-
phorus dichlorides. Bioorg Med Chem Lett 16:2484–2491
Kumar A, Narasimhan B, Kumar D (2007) Synthesis, antimicrobial,
and QSAR studies of substituted benzamides. Biorg Med Chem
15:4113–4124
Kumar P, Narasimhan B, Sharma D, Judge V, Narang R (2009)
Hansch analysis of substituted benzoic acid benzylidene/furan-2-
yl-methylene hydrazides as antimicrobial agents. Eur J Med
Chem 44:1853–1863
Randic M (1993) Comparative regression analysis. Regressions based
on a single descriptor. Croat Chem Acta 66:289–312
Rodriguez-Arguelles MC, Lopez-Silva EC, Sanmartin J, Pelagatti P,
Zani F (2007) Copper complexes of imidazole-2-, pyrrole-2- and
indol-3-carbaldehyde thiosemicarbazones: inhibitory activity
against fungi and bacteria. J Inorg Biochem 101:138–147
Sabet R, Mohammadpour M, Sadeghi A, Fassihi A (2010) QSAR
study of isatin analogues as in vitro anti-cancer agents. Eur J
Med Chem 45:1113–1118
Kumar D, Judge V, Narang R, Sangwan S, De Clercq E, Balzarini J,
Narasimhan B (2010a) Benzylidene/2-chlorobenzylidene hydra-
zides: synthesis, antimicrobial activity, QSAR studies and
antiviral evaluation. Eur J Med Chem 45:2806–2816
Kumar P, Narasimhan B, Yogeeswari P, Sriram D (2010b) Synthesis
and antitubercular activities of substituted benzoic acid
N0-(substituted benzylidene/furan-2-ylmethylene)-N-(pyridine-
3-carbonyl)-hydrazides. Eur J Med Chem 45:6085–6089
Lather V, Madan AK (2005) Topological models for the prediction of
anti-HIV activity of dihydro (alkylthio) (napthylmethyl) oxo-
pyrimidines. Bioorg Med Chem 13:1599–1604
Mandloi D, Joshi S, Khadikar PV, Khosla N (2005) QSAR study on
the antibacterial activity of some sulfa drugs: building blockers
of Mannich bases. Bioorg Med Chem Lett 15:405–411
Manna K, Agrawal YK (2010) Design, synthesis, and antitubercular
evaluation of novel series of 3-benzofuran-5-aryl-1-pyrazolyl-
pyridylmethanone and 3-benzofuran-5-aryl-1-pyrazolylcarbonyl-
4-oxo-naphthyridin analogs. Eur J Med Chem 45:3831–3839
Narasimhan B, Judge V, Narang R, Ohlan S, Ohlan R (2007)
Quantitative structure–activity relationship studies for prediction
of antimicrobial activity of synthesized 2,4-hexadienoic acid
derivatives. Bioorg Med Chem Lett 17:5836–5845
Sbardella G, Mai A, Artico M, Setzu MG, Poni G, Colla PL (2004)
New 6-nitroquinolones: synthesis and antimicrobial activities. IL
Farmaco 59:463–471
Schaper KJ (1999) Free-Wilson-type analysis of non-additive
substituent effects on THPB dopamine receptor affinity using
artificial neural networks. Free-Wilson-type analysis of non-
additive substituent effects on THPB dopamine receptor affinity
using artificial neural networks. Quant Struct Act Relat 18:
354–360
Scior T, Garces-Eisele SJ (2006) Isoniazid is not a lead compound for
its pyridyl ring derivatives, isonicotinoyl amides, hydrazides,
and hydrazones: a critical review. Curr Med Chem 13(18):
2205–2219
Sharma P, Kumar A, Sharma M (2006) Synthesis and QSAR studies
on 5-[2-(2-methylprop-1-enyl)-1Hbenzimidazol-1yl]-4,6-diphe-
nyl-pyrimidin-2-(5H)- thione derivatives as antibacterial. Eur J
Med Chem 41:833–840
Sivaprakasam P, Xiea A, Doerksen RJ (2006) Probing the physico-
chemical and structural requirements for glycogen synthase
kinase-3a inhibition: 2D-QSAR for 3-anilino-4-phenylmalei-
mides. Bioorg Med Chem 14:8210–8218
Sortino M, Delgado P, Jaurez S, Quiroga J, Abonia R, Insuasey B,
Rodero MN, Garibotto FM, Enriz RD, Zacchino SA (2007)
Synnthesis and antifungal activity of (Z)-5-arylidenerhodanines.
Bioorg Med Chem 15:484–494
SPSS for Windows (1999) version 10.05, SPSS Inc., Bangalore
Sriram D, Yogeeswari P, Madhu K (2006) Synthesis and in vitro
antitubercular activity of some 1-[(4-sub)phenyl]-3-(4-{1-[(pyr-
idine-4-carbonyl)hydrazono]ethyl} phenyl thiourea. Bioorg Med
Chem Lett 16:876–878
National Committee for Clinical Laboratory Standards (1995) Anti-
mycobacterial susceptibility testing for Mycobacterium tubercu-
losis. Proposed standard M24-T. National Committee for
Clinical Laboratory Standards, Villanova
Nayyar A, Monga V, Malde A, Coutinho E, Jain R (2007) Synthesis
and anti-tuberculosis activity, and 3D-QSAR study of 4-(ad-
mantan-1-yl)-2-substituted quinolines. Bioorg Med Chem
15:626–640
Pauwels R, Balzarini J, Baba M, Snoeck R, Schols D, Herdewijn P,
Desmyter J, De Clercq E (1988) Rapid and automated tetrazo-
lium based colorimetric assay for detection of anti-HIV
compounds. J Virol Methods 20:309–322
Pharmacopoeia of India (2007) Controller of Publications, vol I.
Ministry of Health Department, Govt. of India, New Delhi, p 37
Pinheiro AAC, Borges RS, Santos SL, Alves CN (2004) A QSAR
study of 8.O.40-neolignans with antifungal activity. J Struct Mol
(Theochem) 672:215–219
Prado-Prado FJ, Gonzalez-Diaz H, Vega OMDL, Ubeira FM, Chou
KC (2008) First multi-tasking QSAR model for Input-Coded
prediction, structural back-projection, and complex networks
clustering of antiprotozoal compounds. Bioorg Med Chem
16(11):5871–5880
Sriram D, Yogeeswari P, Dhakla P, Senthilkumar P, Banerjee D
(2007) N-Hydroxythiosemicarbazones: synthesis and antituber-
cular activity. Bioorg Med Chem Lett 17:1888–1891
Sriram D, Yogeeswari P, Priya DY (2009) Antimycobacterial activity
of novel N-(substituted)-2-isonicotinoylhydrazinocarbothioa-
mide endowed with high activity towards isoniazid resistant
tuberculosis. Biomed Pharmcother 63:36–39
Tripathi RP, Saxena N, Tiwari VK, Verma SS, Chaturvedi V, Manju
YK, Srivastva AK, Gaikwad A, Sinha S (2006) Synthesis and
antitubercular activity of substituted phenylmethyl- and pyridyl-
methyl amines. Bioorg Med Chem 4:8186–8196
TSAR 3D Version 3.3 (2000), Oxford Molecular Limited
Wiener H (1947) Structural determination of paraffin boiling points.
J Am Chem Soc 69:17–20
Randic M (1975) Characterization of molecular branching. J Am
Chem Soc 97:6609–6615
123