Synthesis, antimycobacterial, antiviral, antimicrobial activity and QSAR studies of N2-acyl isonicotinic acid hydrazide derivatives

Article abstract of DOI:10.2174/157340613804488404

A series of N₂-acyl isonicotinic acid hydrazides (1-17) was synthesized and tested for its in vitro antimycobacterial activity against Mycobacterium tuberculosis and the results indicated that the compound, isonicotinic acid N′- tetradecanoyl-hydrazide (12) was more active than the reference compound isoniazid. The results of antimicrobial activity of the synthesized compounds against S. aureus, B. subtilis, E. coli, C. albicans and A. niger indicated that compounds with dichloro, hydroxyl, tri-iodo and N ₂ -tetradecanoyl substituent were the most active ones. The antiviral activity studies depicted that none of the tested compounds were active against DNA or RNA viruses. The multi-target QSAR model was found to be effective in describing the antimicrobial activity of N₂-acyl isonicotinic acid hydrazides.

Full text of DOI:10.2174/157340613804488404

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Medicinal Chemistry, 2013, 9, 53-76
53
Synthesis, Antimycobacterial, Antiviral, Antimicrobial Activity and QSAR
Studies of N2-acyl isonicotinic Acid Hydrazide Derivatives
Vikramjeet Judge1, Balasubramanian Narasimhan2,*, Munish Ahuja1, Dharmarajan Sriram3, Peru-
mal Yogeeswari3, Erik De Clercq4, Christophe Pannecouque4 and Jan Balzarini4
1Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science and Technology, Hisar 125001,
India
2Faculty of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak 124001, India
3Medicinal Chemistry Research Laboratory, Pharmacy Group, Birla Institute of Technology and Science, Hyderabad
500078, India
4Laboratory of Virology & Chemotherapy, Rega Institute for Medical Research, Minderbroedersstraat 10, B-3000
Leuven, Belgium
Abstract: A series of N2-acyl isonicotinic acid hydrazides (1-17) was synthesized and tested for its in vitro antimycobac-
terial activity against Mycobacterium tuberculosis and the results indicated that the compound, isonicotinic acid N'-
tetradecanoyl-hydrazide (12) was more active than the reference compound isoniazid. The results of antimicrobial activity
of the synthesized compounds against S. aureus, B. subtilis, E. coli, C. albicans and A. niger indicated that compounds
with dichloro, hydroxyl, tri-iodo and N2 –tetradecanoyl substituent were the most active ones. The antiviral activity stud-
ies depicted that none of the tested compounds were active against DNA or RNA viruses. The multi-target QSAR model
was found to be effective in describing the antimicrobial activity of N2-acyl isonicotinic acid hydrazides.
Keywords: Antimicrobial, Antitubercular, Antiviral, N2-acyl Isoniazid, QSAR.
INTRODUCTION
or after transplantation, are easily infected by pathogenic
fungi, protozoa and mycobacteria leading rapidly to death
[3]. There are two basic approaches to develop new drugs for
TB: (i) synthesis of analogues, modification or derivatives of
existing compounds for shortening and improving TB treat-
ment and (ii) searching for novel structures, that the TB or-
ganism has never been presented with before, for the treat-
ment of MDR-TB [4].
Tuberculosis (TB) is alarmingly on the rise. Approxi-
mately one third of the world’s population is infected with
TB bacillus, Mycobacterium tuberculosis, with more than 8
million people contracting the disease and 2 million people
dying of it each year. A peculiar aspect of its pathogenicity
comes from the fact that it remains quiescent and becomes
active decades later. One of the most significant risk factor
for developing tuberculosis is human immunodeficiency
virus (HIV) infection. The current treatment of active TB
includes a dosage regime of four drugs (isoniazid, rifam-
picin, pyrazinamide and ethambutol) for at least six months.
As a consequence of the prolonged duration, irregular treat-
ment, and highly adaptive nature of the organisms to the
surroundings, multidrug resistant (MDR) strains of M. tuber-
culosis have developed [1]. The emergence of AIDS, decline
in socioeconomic standards and a reduced emphasis on TB
control programs contribute to disease’s resurgence in indus-
trialized countries [2]. The search for novel antibacterial
agents active against Mycobacterium tuberculosis and other
atypical mycobacteria is urgent due to lack of effectiveness
of known antitubercular agents against opportunistic patho-
gens as a consequence of rapidly emerging resistance. Fur
thermore, immunocompromised patients observe with AIDS,
The emergence of resistance in most of the pathogenic
bacteria to the currently available antibacterial agents is the
major problem in the treatment of serious bacterial infections
caused by these organisms. These resistant strains curtail the
life span of the drug [5]. During the past years an increasing
interest has been devoted to the study of new and more se-
lective antimicrobial agents. Due to this, not only have new
synthetic methods been developed, but a greater amount of
interest has been devoted to comprehension of their mecha-
nism of action and structure activity relationships [6].
Acquired immunodeficiency syndrome (AIDS) is one of
the most frightening syndromes worldwide. AIDS was first
identified in 1983 in U.S.A. and the studies revealed that the
virus entered the U.S. population sometime in the late 1980,
Center for Disease Control and Prevention (CDCP) has de-
fined AIDS as, all HIV infected people with fewer than 200
CD4+ T cells per cubic millimeter of blood (normal is 1000-
1200). There are now more than 40 million people living
with AIDS worldwide and globally 24.8 million people have
died of AIDS since the beginning of epidemic and it is esti-
*Address correspondence to this author at the Faculty of Pharmaceutical
Sciences, Maharshi Dayanand University, Rohtak 124001, India; Tel: +91-
1262-272535; Fax: +91-1262-274133; E-mail: naru2000us@yahoo.com
1875-6638/13 $58.00+.00
© 2013 Bentham Science Publishers

54 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
mated that 68 million will die of AIDS by 2020 [7]. AIDS
remains an enormous health threat, although chemo-
therapeutic agents have increased in number and effective-
ness. Both nucleoside (AZT, DDI, DDC, D4T, 3TC) and
non-nucleoside (nevirapine, delavirdine) HIV reverse tran-
scriptase (RT) inhibitors and HIV protease (saquinavir, indi-
navir, ritonavir, nelfinavir) inhibitors have been licensed by
the US FDA. Also, combination therapy of inhibitors of both
groups results in undetectable levels of HIV in the blood of
infected patients [8]. The US Food and Drug Administration
(FDA) approved medications have limitations such as high
cost, decreased sensitivity due to the rapid emergence of
drug-resistant mutants, and adverse effects like peripheral
neuropathy, bone marrow suppression, and anemia. Thus,
more effective and less toxic anti-HIV agents are still
needed. In addition, alternative approaches, including herbal
therapies after long-term screening of plant extracts, particu-
larly anti-infective or immunomodulating medicinal herbs
and the structural modification of lead compounds, have
been attempted [9].
activity [13-15]. In order to bring into sharper focus the fun-
damental issue of the activities of acylated derivatives of
INH and in pursuit of achieving this goal, our research ef-
forts focused on the synthesis, antimicrobial, antimycobacte-
rial, antiviral and QSAR studies [16-18], herewith we report
the synthesis, antimycobacterial, anti-HIV, antimicrobial and
QSAR studies of N2-acyl isonicotinic acid hydrazide deriva-
tives.
MATERIAL AND METHODS
Melting points were determined in open capillary tubes
on a Sonar melting point apparatus and are uncorrected. Re-
action progress was monitored by thin layer chromatography
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 re-
corded in Bruker Avance II 400 NMR spectrometer using
appropriate deuterated solvents and are expressed in parts
per million (ꢀ, ppm) downfield from tetramethylsilane (in-
ternal standard). Infrared (IR) spectra were recorded on a
Shimadzu FTIR spectrophotometer.
Biological activities of the molecules are a function of
their chemical and physical properties. A structure–activity
relationship is a qualitative association between a chemical
substructure and the potential of a chemical to exhibit a cer-
tain biological effect. A quantitative structure–activity rela-
tionship (QSAR) is a mathematical model that relates a
quantitative measure of chemical structure to a biological
effect. Thus, the structure–activity relationship of the mole-
cules could be explained quantitatively [10]. Quantitative
structure–activity relationships (QSARs) represent an at-
tempt to correlate structural properties of the compounds
with biological activities and chemical reactivity. These
chemical descriptors, which include parameters to account
for hydrophobicity, electronic, inductive, or polar properties,
and steric effects, are determined empirically or by calcula-
tions [11].
General Procedure for Synthesis of Ester
The mixture of isonicotinic acid (0.1 mol) and ethanol (in
excess) was refluxed with sulphuric 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 etha-
nol.
Isoniazid (INH) is the most frequently prescribed primary
prophylactic and chemotherapeutic drug against M. tubercu-
losis. Enzymatic acylation of the antitubercular isoniazid
(INH) by arylamine N-acetyl transferases (NATs) reduces
the therapeutic effectiveness of the drug. Because it repre-
sents a major metabolic pathway for INH in human beings,
such acetylation has serious consequences for tuberculosis
treatment regimens. Among patients in whom this process is
efficient, the “rapid acetylators,” the resultant chronic under-
dosing of INH may give rise to the development of resis-
tance, as well as inadequate therapy. NATs occur in myco-
bacteria and in their mammalian hosts. It is thought that the
resultant chemical change prevents the activation of INH that
is required for proper drug action. A recombinant NAT from
M. tuberculosis acetylates INH in vitro. When the corre-
sponding nat gene is over expressed in a suitable INH-
susceptible host, Mycobacterium smegmatis, the resultant
organism becomes more resistant to INH. Resistance to INH
in mycobacteria can thus be related to increased expression
of NAT. Not much work has been done previously to charac-
terize the antitubercular properties of other N2- acyl isoniazid
derivatives. The appreciable in vitro and in vivo antimyco-
bacterial activity of acylated derivatives of isoniazid has
been reported by Hearn and Cynamon [12]. The isoniazid
derivatives have also been reported to possess antimicrobial
General Procedure for the Synthesis of N2-acyl Isonico-
tinic Acid Hydrazides (1-15)
The different carboxylic acids (0.01 mol) were refluxed
with thionyl chloride (0.015 mol) for three hours. After re-
fluxing was complete, the excess thionyl chloride was dis-
tilled off to get the respective acyl chlorides. The isonicotinic
acid hydrazide (0.01 mol) was suspended in dichloromethane
and acyl chloride (0.01 mol) was added dropwise to this so-
lution with constant stirring on a magnetic stirrer for 3-4
hours. The product obtained after evaporation of dichloro-
methane was recrystallized from ethanol.
Benzoic acid N'-(pyridine-4-carbonyl)-hydrazide (1):
Mp (°C) 180-183; Yield– 89.4%; 1H NMR (400 MHz,
DMSO) ꢀ ppm: 7.42-7.58 (m, 3H, CH of C3, C4 and C5 of
phenyl ring), 7.97-8.01 (d, 2H, CH of C2 and C6 of phenyl
ring), 8.33-8.35 (d, 2H, CH of C3 and C5 of pyridine ring),
8.91-8.93 (d, 2H, CH of C2 and C6 of pyridine ring), 10.55
(s, 1H, NH proton of N2), 11.24 (s, 1H, NH proton of N1). IR
(KBr pellets) ꢁ cm-1: 3217.78 (NH str., amide), 3005.15 (CH

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 55
str., aromatic), 1611.24 (C=O str., Nicotinoyl), 1570.86
(C=O str., Acyl), 1466.363 (C=C str., skeletal phenyl nu-
cleus), 1248.06 (C-N str., coupled vibrations amide), 839.47
(CH out of plane bending, 4-substituted pyridine), 720.11
(OCN deformations, amide IV band), 634.84 (OCN defor-
mations, amide VI band).
aromatic), 1680.07 (C=O str., Nicotinoyl), 1643.42 (C=O
str., Acyl), 1501.65 (C=C str., skeletal phenyl nucleus),
1216.17 (C-N str., coupled vibrations amide), 842.93 (CH
out of plane bending, 4-substituted pyridine), 643.29 (OCN
deformations, amide VI band).
Isonicotinic acid N'-tetradecanoyl-hydrazide (12): Mp
(°C) 194-197; Yield– 65.48%; 1H NMR (400 MHz, DMSO)
ꢀ ppm: 0.82-0.85 (t, 3H, CH3), 1.21-1.27 (m, 20H, CH of
CH2 of C4-C13 of Myristoyl chain), 1.54-1.56 (m, 2H, CH of
CH2 of C3 of Myristoyl chain), 2.50-2.51 (m, 2H, CH of CH2
of C2 of Myristoyl chain), 8.13-8.14 (d, 2H, CH of C3 and C5
of pyridine ring), 8.92-8.94 (d, 2H, CH of C2 and C6 of pyri-
dine ring), 10.09 (s, 1H, NH proton of N2), 10.93 (s, 1H, NH
proton of N1). IR (KBr pellets) ꢁ cm-1: 3192.08 (NH str.,
amide), 2955.28 (CH str., aliphatic), 1700.23 (C=O str.,
Nicotinoyl), 1647.28 (C=O str., Acyl), 1495.93 (C=C str.,
skeletal phenyl nucleus), 1470.13 (CH bending, CH3),
1281.55 (C-N str., coupled vibrations amide), 847.90 (CH
out of plane bending, 4-substituted pyridine), 758.04 (OCN
deformations, amide IV band), 652.47 (OCN deformations,
amide VI band).
3-Methyl-benzoic
acid
N'-(pyridine-4-carbonyl)-
1
hydrazide (2): Mp (°C) 194-197; Yield– 85.68%; H NMR
(400 MHz, DMSO) ꢀ ppm: 2.38 (s, 3H, CH3), 7.32-7.37 (m,
2H, CH of C4 and C5 of phenyl ring), 7.75-7.79 (d, 2H, CH
of C2 and C6 of phenyl ring), 8.51-8.52 (d, 2H, CH of C3 and
C5 of pyridine ring), 9.11-9.12 (d, 2H, CH of C2 and C6 of
pyridine ring), 10.76 (s, 1H, NH proton of N2), 11.43 (s, 1H,
NH proton of N1). IR (KBr pellets) ꢁ cm-1: 3209.44 (NH str.,
amide), 3074.98 (CH str., aromatic), 2967.28 (CH str., ali-
phatic), 1692.50 (C=O str., Nicotinoyl), 1654.68 (C=O str.,
Acyl), 1513.01 (C=C str., skeletal phenyl nucleus), 1279.97
(C-N str., coupled vibrations amide), 825.38 (CH out of
plane bending, 4-substituted pyridine), 746.05 (OCN defor-
mations, amide IV band), 632.01 (OCN deformations, amide
VI band).
Isonicotinic acid N'-[2-(2,4-dichloro-phenyl)-acetyl]-
1
3-Hydroxy-benzoic acid N'-(pyridine-4-carbonyl)-
hydrazide (5): Mp (°C) 222-225; Yield– 59.35%; H NMR
1
hydrazide (13): Mp (°C) 182-185; Yield– 67.8%; H NMR
(400 MHz, DMSO) ꢀ ppm: 3.70 (s, 2H, CH2), 7.26 (s, 1H,
CH of C6 of 2,4-dichlorophenyl ring), 7.33 (s, 1H, CH of C5
of 2,4-dichlorophenyl ring), 7.42 (s, 1H, CH of C3 of 2,4-
dichlorophenyl ring), 8.46-8.48 (d, 2H, CH of C3 and C5 of
pyridine ring), 9.09-9.10 (d, 2H, CH of C2 and C6 of pyridine
ring), 10.65 (s, 1H, NH proton of N2), 11.40 (s, 1H, NH pro-
ton of N1). IR (KBr pellets) ꢁ cm-1: 3168.70 (NH str., am-
ide), 3025.58 (CH str., aromatic), 1690.65 (C=O str., Nicoti-
noyl), 1625.24 (C=O str., Acyl), 1534.78 (C=C str., skeletal
phenyl nucleus), 1280.68 (C-N str., coupled vibrations am-
ide), 819.36 (CH out of plane bending, 4-substituted pyri-
dine), 787.96 (OCN deformations, amide IV band), 638.16
(OCN deformations, amide VI band).
(400 MHz, DMSO) ꢀ ppm: 6.98 (s, 1H, OH), 7.21-7.24 (m,
1H, CH of C4 of phenyl ring), 7.32-7.36 (m, 2H, CH of C2
and C6 of phenyl ring), 7.53-7.57 (m, 1H, CH of C5 of phenyl
ring), 8.51-8.53 (d, 2H, CH of C3 and C5 of pyridine ring),
9.14-9.18 (d, 2H, CH of C2 and C6 of pyridine ring), 9.80 (s,
1H, NH proton of N2), 10.75 (s, 1H, NH proton of N1). IR
(KBr pellets) ꢁ cm-1: 3182.68 (NH str., amide), 3077.56 (CH
str., aromatic), 1719.61 (C=O str., Nicotinoyl), 1681.04
(C=O str., Acyl), 1509.36 (C=C str., skeletal phenyl nu-
cleus), 1283.68 (C-N str., coupled vibrations amide), 815.63
(CH out of plane bending, 4-substituted pyridine), 787.96
(OCN deformations, amide IV band), 632.68 (OCN defor-
mations, amide VI band).
Isonicotinic acid N'-(2-chloro-pyridine-3-carbonyl)-
hydrazide (8): Mp (°C) 160-163; Yield– 70.30%; 1H NMR
(400 MHz, DMSO) ꢀ ppm: 7.44-7.46 (t, 1H, CH of C5 of 2-
chloronicotinoyl ring), 7.98-8.02 (d, 2H, CH of C3 and C5 of
pyridine ring), 8.49-8.52 (d, 1H, CH of C6 of 2-
chloronicotinoyl ring), 8.81-8.85 (d, 2H, CH of C2 and C6 of
pyridine ring), 8.86-8.88 (d, 1H, CH of C4 of 2-
chloronicotinoyl ring), 9.90 (s, 1H, NH proton of N2), 10.80
(s, 1H, NH proton of N1). IR (KBr pellets) ꢁ cm-1: 3161.47
(NH str., amide), 1702.25 (C=O str., Nicotinoyl), 1585.55
(C=O str., Acyl), 1488.15 (C=C str., skeletal phenyl nu-
cleus), 1256.68 (C-N str., coupled vibrations amide), 832.32
(CH out of plane bending, 4-substituted pyridine), 761.91
(C-Cl str., aromatic), 652.93 (OCN deformations, amide IV
band), 542.02 (OCN deformations, amide VI band).
General Procedure for the Synthesis of Isonicotinic Acid
(3-phenyl-allylidene)-hydrazide (16)
Isonicotinic acid hydrazide (0.05 mol) and cinnamalde-
hyde (0.06 mol) in ethanol was refluxed for appropriate time.
At the completion of reaction the precipitates start to appear
which were filtered off and recrystallized from ethanol.
Isonicotinic acid (3-phenyl-allylidene)-hydrazide (16):
Mp (°C) 195-198; Yield– 61.9%; 1H NMR (400 MHz,
DMSO) ꢀ ppm: 6.97-7.05 (m, 2H, CH of –CH=CH-), 7.30-
7.32 (t, 1H, CH of C4 of phenyl ring), 7.37-7.40 (m, 2H, CH
of C3 and C5 of phenyl ring), 7.50-7.52 (m, 2H, CH of C2
and C6 of phenyl ring), 7.82-7.83 (d, 2H, CH of C3 and C5 of
pyridine ring), 8.25-8.27 (d, 1H, CH of N=CH), 8.75-8.76 (d,
2H, CH of C2 and C6 of pyridine ring), 11.94 (s, 1H, NH). IR
(KBr pellets) ꢁ cm-1: 3228.98 (NH str., amide), 3037.05 (CH
str., aromatic), 2988.83 (CH str., aliphatic), 1650.17 (C=O
str., Nicotinoyl), 1573.02 (C=C str., skeletal phenyl nucleus),
1153.48 (C-N str., coupled vibrations amide), 830.39 (CH
out of plane bending, 4-substituted pyridine), 676.08 (OCN
deformations, amide VI band).
Isonicotinic acid N'-(3-phenyl-acryloyl)-hydrazide (9):
1
Mp (°C) 208-211; Yield– 69.32%; H NMR (400 MHz,
DMSO) ꢀ ppm: 6.40-6.44 (d, 1H, CH of –CO-CH=), 6.83-
6.87 (d, 1H, CH of =CH-C6H5), 7.55-7.74 (m, 5H, C6H5),
8.55-8.56 (d, 2H, CH of C3 and C5 of pyridine ring), 9.09-
9.10 (d, 2H, CH of C2 and C6 of pyridine ring), 10.71 (s, 1H,
NH proton of N2), 11.63 (s, 1H, NH proton of N1). IR (KBr
pellets) ꢁ cm-1: 3195.22 (NH str., amide), 3011.98 (CH str.,

56 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
General Procedure for the Synthesis of Benzoic acid-N2-
(3-phenylallylidene)-N1-(pyridine-4-carbonyl)-hydrazide
(17):
ther refined by means of the semiempirical method PM3
(Parametric Method-3). We chose a gradient norm limit of
0.01 kcal/A˚ for the geometry optimization. The output files
were used for producing constitutional, topological, electro-
static, and semiempirical descriptors using TSAR 3.3 software
for Windows [23]. These quantitative descriptors contain in-
formation on the inter atom connections and the shape,
branching, symmetry, distribution of charge and quantum-
chemical properties of the molecule. Further, the regression
analysis was performed using the SPSS software package
[24]. The predictive powers of the equation were validated
by determination of cross-validated r2 (q2) using leave one
out (LOO) cross-validation method [25].
Isonicotinic acid-3-phenylallylidene hydrazide (16) was
dissolved in dichloromethane (0.001 mol) and a solution of
benzoyl chloride (0.001 mol) in dichloromethane was added
drop wise and kept for stirring on a magnetic stirrer till the
evaporation of dichloromethane. The product obtained was
checked for purity by TLC and recrystallized from ethanol.
Benzoic acid-N2-(3-phenylallylidene)-N1-(pyridine-4-
carbonyl)-hydrazide (17): Mp (°C) 203-206; Yield– 67.5%;
1H NMR (400 MHz, DMSO) ꢀ ppm: 7.33-7.58 (m, 10H,
phenyl rings), 7.97-8.03 (m, 2H, CH of –CH=CH-), 8.44-
8.46 (d, 2H, CH of C3 and C5 of pyridine ring), 8.65-8.67 (d,
1H, CH of N=CH), 8.93-8.96 (d, 2H, CH of C2 and C6 of
pyridine ring). IR (KBr pellets) ꢁ cm-1: 3217.40 (NH str.),
3016.80 (CH str., aromatic), 2906.85 (CH str., aliphatic),
1605.81 (C=O str), 1474.64 (C=C str., skeletal phenyl nu-
cleus), 1290.43 (C-N str., coupled vibrations amide), 840.04
(CH out of plane bending, 4-substituted pyridine), 674.15
(OCN deformations, amide VI band).
Calculation of Statistical Parameters [26, 27]
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 SSY (sum of
squares of response values)
These parameters were calculated from the following
equations.
Evaluation of Antimycobacterial Activity
PE = 2(1- r2)/3ꢀn
All compounds were screened for their in vitro antimy-
cobacterial activity against MTB, in Middlebrook 7H11agar
medium supplemented with OADC (Oleic Acid and Dex-
trose as Carbon source) by agar dilution method similar to
that recommended by the National Committee for Clinical
Laboratory Standards for the determination of MIC in tripli-
cate [19]. The minimum inhibitory concentration (MIC) is
defined as the minimum concentration of the compound re-
quired to give complete inhibition of bacterial growth.
Where, r, correlation coefficient and n, number of com-
pounds used.
2
LSE = ꢁ(Yobs-Ycalc
)
Where, Yobs and Ycalc are the observed and calculated values.
LOF = LSE/{1-(C+d · p/n)}2
Where, LSE, least square error; C, number of descriptors
+1; p, number of independent parameters; n, number of com-
pounds used; d, smoothing parameter which controls the bias
in the scoring factor between equations with different
number of terms and was kept 1.0.
Evaluation of Antimicrobial Activity
The antimicrobial activity was performed against Gram-
positive bacteria: S. aureus, B. sublitis, Gram-negative bacte-
rium: E. coli and fungal strains: C. albicans and A. niger by
tube dilution method [20]. Dilutions of test and standard
compounds [norfloxacin (antibacterial) and fluconazole
(antifungal)] were prepared in double strength nutrient broth
– I.P. (bacteria) and Sabouraud dextrose broth I.P. [21]
(fungi). The samples were incubated at 37 °C for 24 h (bac-
teria), at 25 °C for 7 d (A. niger) and at 37 °C for 48 h (C.
albicans), respectively, and the results were recorded in
terms of MIC (the lowest concentration of test substance
which inhibited the growth of microorganisms).
SEP = ꢀLSE/n
The Quality value, Q is given by
Q = r/Se
Where, r, correlation coefficient and Se, standard error.
The predictive ability of QSAR models was also quanti-
fied in terms of q2, which is defined as
q2 = 1- {ꢁ(Yobs-Ycalc)2/ ꢁ(Yobs-Ymean)2}
The resubstitution test statistical parameters [28] viz. re-
gression coefficient (r), root mean square error (RMSE) and
absolute average error (eꢂ) were calculated as:
QSAR STUDIES
Preparation of Data Set
Regression coefficient (r) = ꢀ{ 1 – (ꢁ(Ycalc - Yobs)2/ ꢁ(Ycalc
- Ymean)2)}
An Intel (R) Core (TM) 2 Duo personal computer (CPU
T 6600 at 2.20 GHz) with windows XP operating system
was used. To obtain a QSAR model, the compounds must be
represented by molecular descriptors that retain as much
structure information as possible. The descriptors were gen-
erated as follows: The structures of N2-acyl isonicotinic acid
hydrazide derivatives were first pre-optimized with the Mo-
lecular Mechanics Force Field (MM+) procedure included in
Hyperchem 6.03 [22] and the resulting geometries were fur-
The Absolute average error (eꢂ) is used to illustrate the
predictive accuracy more explicitly and given by
Absolute average error (eꢂ) = {ꢁ|Ycalc - Yobs|}/n
The root mean square error (RMSE) is calculated
mathematically as:
Root mean square error (RMSE) = ꢀ{ꢁ(Ycalc - Yobs)2}/n

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 57
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.
50% of the cell cultures) in the presence of varying concen-
trations (100, 20, 4, ... ꢀg/ml) of the test compounds. Viral
cytopathicity was recorded as soon as it reached completion
in the control virus-infected cell cultures that were not
treated with the test compounds.
Variation Inflation Factor [29] is employed to determine
the multicolinearity between the physicochemical parame-
ters. The VIF value is calculated as
RESULTS AND DISCUSSION
Chemistry
VIF = 1/1-r2
Where, r2 is the squared multiple correlation coefficient of
one parameter effect on the remaining parameter. VIF values
greater than 5 indicate the presence of unacceptably large
multicolinearity between parameters in the correlation.
The synthesis of N2-acyl isonicotinic acid hydrazide de-
rivatives was carried out as demonstrated by Scheme 1. The
isonicotinic acid was refluxed with ethanol in the presence of
sulphuric 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 N2-acyl isonico-
tinic acid hydrazide derivatives (1-15) were synthesized by
the reaction of isonicotinic acid hydrazide, suspended in di-
chloromethane, with respective acyl chlorides which in turn
were obtained by refluxing the respective acids with thionyl
chloride. The isonicotinic acid (3-phenyl-allylidene)-
hydrazide (16) was synthesized by refluxing isonicotinic
acid hydrazide with cinnamaldehyde in ethanol and benzoic
acid-N2-(3-phenylallylidene)-N1-(pyridine-4-carbonyl)-
hydrazide (17) was prepared by the reaction of benzoyl chlo-
ride with Isonicotinic acid-3-phenylallylidene hydrazide
(16). The yield of target compounds was appreciable and
their physicochemical characteristics are presented in Table 1.
Theory of Stepwise Multiple Linear Regression (MLR)
[30]
Multiple linear regression (MLR) is the most widely used
multiple linear modeling techniques. Following is the regres-
sion equation:
Y = b0 + b1X1 + b2X2 + . . . . + bnXn
In this equation, Y is the property, that is, the dependent
variable; X1–Xn represents the specific descriptors, while b1–
bn represents the coefficient of those descriptors, and b0 is
the intercept of this equation. As is well known, MLR cannot
be used to model complex data, since in most cases the num-
ber of explanatory variables exceeds the number of objects.
Therefore, it is often used in combination with the stepwise
procedure for variable selection. The forward stepwise re-
gression procedure consists simply in a step-by-step addition
of the best descriptors to the model that leads to the smallest
standard deviation(s), until there is no other variable outside
the equation that satisfies the selection criteria.
The purity of N2-acyl isonicotinic acid hydrazide deriva-
tives was checked by single spot TLC and their IR and NMR
spectra were found in agreement with their assigned molecu-
lar structures. The singlet signals observed around ꢀ 10 ppm
and ꢀ 11 ppm represents the NH protons at N2 and N1 posi-
tion of the hydrazide portion in compounds 1, 2, 5, 8, 9, 12
and 13. This clearly signifies that the acyl group was at-
tached to the isonicotinic acid hydrazide by replacing one of
the two protons of NH2 group. Similarly two doublet signals,
in the region ꢀ 7.90 – 9.20 ppm, each having an integral
equivalent to two protons corresponds the presence of four
CH protons of the pyridine ring in compounds 1, 2, 5, 8, 9,
12, 13, 16 and 17. The presence of phenyl ring in the struc-
ture of compound 1 was confirmed by the multiplet signal
having integral of five protons at ꢀ 7.42 – 7.58 ppm. In com-
pound 2, a triplet at ꢀ 2.38 ppm revealed the presence of a
methyl group on the phenyl ring in its structure. The appear-
ance of signals for three aromatic protons and a singlet at ꢀ
3.70 ppm confirmed that 2,4-dichloro-phenyl)-acetyl group
was attached at N2 position in compound 5. The doublet sig-
nals at ꢀ 6.40 – 6.44 ppm and ꢀ 6.83 – 6.87 ppm correspond-
ing to CH protons of -CH=CH- group and multiplet of aro-
matic protons of phenyl nucleus at ꢀ 7.55 – 7.74 ppm con-
firmed the successful synthesis of isonicotinic acid N'-(3-
phenyl-acryloyl)-hydrazide (9). The structure of isonicotinic
acid N'-tetradecanoyl-hydrazide (12) was confirmed by the
presence of signals for CH3 group and methylene protons at ꢀ
0.82-0.85 ppm and above ꢀ 1.20 ppm respectively. The sin-
glet signal for NH proton of compound 16 was observed at ꢀ
11.94 ppm and disappearance of this signal in compound 17
confirmed the formation compounds 16 and 17 respectively.
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 cul-
tures using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-
tetrazolium bromide (MTT) method [31]. Briefly, virus
stocks were titrated in MT-4 cells and expressed as the 50%
cell culture infective dose (CCID50). MT-4 cells were sus-
pended in culture medium at 1 x 105 cells/ml and infected
with HIV at a multiplicity of infection of 0.02. Immediately
after viral infection, 100 ꢀl 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-d
incubation period at 37 °C, the number of viable cells was
determined using the MTT method. Compounds were tested
in parallel for cytotoxic effects in uninfected MT-4 cells.
Antiviral Assays
The antiviral assays [except anti-human immunodefi-
ciency 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 stomatitis
virus], Vero (parainfluenza-3, reovirus-1, Sindbis, Coxsackie
B4, and Punta Toro virus), HeLa (vesicular stomatitis virus,
Coxsackie virus B4, and respiratory syncytial virus) cell cul-
tures. 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
The IR spectra of compounds 1, 2, 5, 8, 9, 12 and 13 re-
vealed the presence of vibrational frequencies corresponding
to two C=O functional groups suggesting that the acyl resi-

58 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Cl
O
OH
C2H5OH
OC2H5
NH2NH2
O
O
NHNH2
O
CHO
NHN CH
O
O
N
N
N CH
O
N
N
N
N
16
17
COOH
R1
COCl
O
Y
O
Y
SOCl2
R1
R2
NH NH
R5
R4
O
R5
R4
NH NH
Y
O
RCOOH
RCOCl
R1
R2
X
R
R5
R4
X
R2
X
R3
R3
N
N
R3
10-12
1-9, 13-15
Y
Comp.
R1
R2
R3
R4
R5
X
R
1
2
H
H
H
H
Cl
OH
I
H
H
H
H
H
H
NO2
H
H
I
H
H
H
H
H
H
H
H
H
-
C
C
C
C
C
C
C
N
C
-
-
-
-
-
-
-
-
-
-
-
CH3
-
3
OCH3
OCH3
-
4
NO2
H
Cl
H
H
H
H
-
-
5
H
CH2
6
H
-
-
-
7
I
8
Cl
H
-
H
H
H
-
9
H
CH=CH
10
11
12
13
14
15
-
-
-
-
-
-
-
-CH=CH-CH3
-
-
-
-
-
-
-
-C6H12CH3
-
-
-
-
-
-C12H24CH3
H
H
H
OH
OCH3
H
H
H
H
H
H
H
H
H
H
C
C
N
-
-
-
Scheme 1. Synthetic route followed for the synthesis of n2-acyl isonicotinic acid hydrazide derivatives.
due has been added to the isonicotinic acid hydrazide mole-
cule. The amide I band was observed in the spectra of com-
pounds 1, 2, 5, 8, 9, 12 and 13 in the region 3200-3100 cm-1.
The presence of peaks slightly above and below 3000 cm-1
indicated the presence of an aromatic and aliphatic portion in
the synthesized compounds, respectively.
which represents the presence of aromatic nucleus in their
structure. Only one band corresponding to C=O function was
observed in the IR spectra of compounds 16 and 17 which
confirmed their synthesis as well as indicated that only one
C=O function was present in their structure.
Antimycobacterial Activity
The OCN deformations corresponding to amide IV and
amide VI bands were observed around 750-720 cm-1 and
650-630 cm-1 in the IR spectra of compounds 1, 2, 5, 8, 9 and
12. In compound 8, C-Cl stretching was observed at 761.91
cm-1 that depicted the presence of chloro group on aromatic
nucleus in the molecular structure. The skeletal C=C-
stretching bands (aromatic) were observed around 1513-
1466 cm-1 in the spectra of the synthesized compounds
The in vitro antitubercular activity of synthesized N2-acyl
isonicotinic acid hydrazide derivatives against Mycobacte-
rium tuberculosis (MTB) was carried out in Middlebrook
7H11agar medium supplemented with OADC by agar dilu-
tion method and the results are presented in Table 1. At the
commencement of this study in the preliminary screening,
compound (1), isonicotinic acid hydrazide with an unsubsti-

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 59
Table 1. Physicochemical Properties and Antimycobacterial Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives
MIC
Comp.
1
Mol. Formula
Mol. Wt.
M.p. (°C)
Rf*
% Yield
MTB-H37Rv
(ꢀM x 10-3)
Training Set
C13H11N3O2
241
180-183
0.83
89.40
52
2
3
C14H13N3O2
C15H15N3O4
C13H9N5O6
255
301
331
324
257
618
276
267
205
263
347
194-197
170-173
198-201
222-225
220-223
236-239
160-163
208-211
160-163
Above 242
194-197
0.87
0.73
0.68
0.64
0.76
0.54
0.75
0.62
0.76
0.61
0.54
85.68
68.95
66.28
59.35
67.49
69.37
70.30
69.32
46.12
71.27
65.48
49
42
9
4
5
C14H11N3O2Cl2
C13H11N3O3
C13H8N3O2I3
C12H9N4O2Cl
C15H13N3O2
C10H11N3O2
C14H21N3O2
C20H33N3O2
10
49
40
23
23
61
12
2
6
7
8
9
10
11
12
Test Set
13
14
C13H11N3O3
C14H13N3O3
C12H10N4O2
C15H13N3O
C22H17N3O2
257
271
242
251
355
182-185
206-209
226-2229
195-198
203-206
0.88
0.81
0.67
0.62
0.38
67.8
64.8
67.8
81.9
67.5
49
92
15
52
16
6
17
70
INH
ETBa
CFL
2.04
15.31
9.4
0.24
RIFa
*Mobile phase: Ethanol
a D. Sriram, P. Yogeeswari, P. Dhakla, P. Senthilkumar, D., Banerjee, Bioorg. Med. Chem. Lett. 17 (2007) 1888-1891.
tuted phenyl ring attached at N2 position through carbonyl
function, displayed poor antimycobacterial activity with a
MIC of 52 x 10-3 ꢀM. Therefore, compound 1 was taken as a
lead molecule and we planned to improve its antimycobacte-
rial activity by altering the substituent on phenyl ring. The
first step towards lead optimization was incorporation of
electron donating group (CH3) on phenyl ring. The addition
of electron donating group slightly improved the antitubercu-
lar activity evidenced by the small increase in the activity of
compound 2 (MIC = 49 x 10-3 ꢀM) in comparison to 1. Then
we replaced the methyl group with 3,4-dimethoxy substitu-
ents (Compound 3) on phenyl nucleus, which marginally
increased the antimycobacterial activity (MIC = 42 x 10-3
ꢀM). As the increment of antimycobacterial activity was not
highly appreciable that changed our mind to add some elec-
tron withdrawing groups as substituent on the phenyl nucleus
and compound 4 having 3,5-dinitro substitution was synthe-
sized. The compound 4 was found to be highly active with
MIC of 9 x 10-3 ꢀM. The next modification in the structure
was addition of electronegative chloro substituent on the
phenyl nucleus that resulted in the synthesis of compound 5,
which has 2,4-dichloro substitution on phenyl nucleus with
phenyl nucleus attached to carbonyl function with a methyl-
ene linker. Compound 5 was also found to be active antimy-
cobacterial agent with MIC of 10 x 10-3 ꢀM. In compound 6,
the phenyl nucleus was substituted with OH group at ortho
position, but this modification lead to decrease in activity
with MIC falling to 49 x 10-3 ꢀM. Therefore, the idea of ad-
dition of OH group was dropped and next change was addi-
tion of iodine group on the phenyl nucleus that resulted in
the synthesis of compound 7 having 2,3,5-triiodo substitu-
tion and this molecule showed better antimycobacterial ac-
tivity, with MIC of 40 x 10-3 ꢀM, than compound 6. Then we
planned to add some hetero atom in the phenyl nucleus and

60 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
synthesized compound 8 having hetero atom nitrogen at 3rd
position and electronegative chloro group as substituent at
2nd position on the phenyl nucleus. This idea also worked
and compound 8 was also found to be active with MIC of 23
x 10-3 ꢀM. In compound 9, the -CH=CH- group was inserted
between the phenyl nucleus and carbonyl group and this
compound was also equally active with MIC of 23 x 10-3
ꢀM. The next modification was the replacement of phenyl
nucleus with aliphatic chain of carbon atoms that resulted in
compound 10, which has 2-propene as substituent attached
to the carbonyl function. This change leads to a steep fall in
activity with MIC falling to 61 x 10-3 ꢀM. Then we added
heptane as side chain (octanoyl as N2 substituent) in com-
pound 11, and got a highly active molecule with MIC of 12 x
10-3 ꢀM. In compound 12, myristoyl group (acyl group of
myristic acid) was taken as substituent on N2 of hydrazide
and the resultant molecule was the most active antimycobac-
terial agent with MIC of 2 x 10-3 ꢀM, which was lowest
among the synthesized derivatives. The compound 12 was
found to be more active antitubercular agent than isoniazid.
the resultant compound was not active. This is similar to the
results of antimycobacterial activity of compound 6, which
confirms the fact that OH group decreases the antimycobac-
terial activity. It was observed from the SAR studies that
electron donating as well as electron withdrawing groups
increase the antimycobacterial activity which is contradic-
tory and in order to find out the real fact compound 14, hav-
ing OCH3 group at 3rd position of phenyl nucleus, was syn-
thesized and from the results of antimycobacterial activity it
was clear that OCH3 group decrease the antimycobacterial
activity as compound 14 was found to be least active with
MIC 92 x 10-3 ꢀM. The increased antimycobacterial activity
of compound 3 may be due to the presence of an additional
OCH3 group in its structure and it can be concluded that
OCH3 reduces activity only in position 3 and it increases the
activity in position 4. The presence of pyridine ring in the
structure confers antimycobacterial activity to the isoniazid,
keeping this fact in mind compound 15, having 3-pyridyl
ring in place of phenyl nucleus, was synthesized but the ac-
tivity was found to be very less (MIC = 52 x 10-3 ꢀM) and it
can be concluded that an additional pyridine ring in the
isonicotinic acid hydrazide structure has no impact on the
activity. This clearly indicates that the increase in antimyco-
bacterial activity of compound 8 may be due to the presence
of the electron withdrawing chloro group and not due to
presence of an additional pyridine nucleus. The hydrazones
of isonicotinic acid hydrazide have been reported to be active
antimycobacterial agents and appreciable antimycobacterial
activity of compound 9 (Isonicotinic acid N'-(3-phenyl-
acryloyl)-hydrazide) derived by acylation of isonicotinic acid
hydrazide with cinnamic acid inspired us for synthesis of
hydrazone of isoniazid with cinnamaldehyde and the resul-
tant compound 16 was highly active with MIC of 6 x 10-3
ꢀM. The fact that presence of phenyl substituent increased
the antimycobacterial activity lead us to the synthesis of
compound 17 in which the N1-proton of 16 was replaced
with benzoyl nucleus and this substitution decreased the an-
timycobacterial activity (MIC) to 70 x 10-3 ꢀM. It can be
seen from this result that presence of at least one NH group
is necessary for a molecule to be active antimycobacterial
agent.
From the results of antimycobacterial activity the follow-
ing conclusions regarding structure activity relationship
(SAR) can be drawn:
1. The replacement of the phenyl nucleus with long ali-
phatic chain (Compound 11 and 12) gave the mole-
cules with highly improved antimycobacterial activ-
ity. This is similar to one of our previous report in
which an increase in antimicrobial activity was ob-
served with long aliphatic chain compounds [32].
2. In contrast with Tripathi et al. [33] who stated that the
OH group at ortho position leads to a measurable
change in activity of the compounds, the presence of
the OH group at ortho position (Compound 6) de-
creased the activity of the compounds.
3. The presence of electron withdrawing groups on the
phenyl ring increases the antitubercular activity as
evidenced by the high antimycobacterial activity of
compounds 4 and 5. The role of electron withdrawing
group in improving activity is supported by the stud-
ies of Sharma et al. [34].
Summarizingly, it can be concluded that long alkyl chain
substituted derivatives were highly active antimycobacterial
agents with compound 12 having myristoyl substituent on
N2-position was more active than isoniazid. This may be due
to the fact that mycolic acid that constitutes the mycobacte-
rial cell wall contains long chain stearyl group in its molecu-
lar structure and compounds derived from long alky chains
may act as false substrate for the Mycobacterium and get
incorporated in the bacterial cell wall and give rise to a
pseudo cell wall and also carries the isonicotinic acid hydraz-
ide attached to its structure in to the bacterial cell thus lead-
ing to an increased uptake of isonicotinic acid hydrazide by
the Mycobacterium which may be cause of lysis of Myco-
bacterium and increased antimycobacterial potential of satu-
rated long chain N2-acyl isonicotinic acid hydrazide deriva-
tives.
4. Among the different electron withdrawing groups, ni-
tro group is most effective in conferring the antimy-
cobacterial activity to potential.
5. The compounds 5, 7, 11 and 12 having high log P
values were found to be more active than other syn-
thesized derivatives which is similar to the findings of
Sriram et al. [38] who observed that increased lipo-
philicity of 1-[(4-sub)phenyl]-3-(4-{1-[(pyridine-4-
carbonyl)hydrazono]ethyl}phenyl thiourea rendered
them more capable of penetrating various biomem-
branes.
Based on the SAR results, we have synthesized a test set
of isonicotinic acid hydrazide derivatives (13-17) so as to
validate the SAR findings by the results of antimycobacterial
activity of test set compounds. First of all, OH group was
added, with an idea that the electronegative oxygen atom of
OH group may facilitate the binding of N2-acyl isonicotinic
acid hydrazide derivatives by hydrogen bonding at the target
site, at 3rd position of the phenyl nucleus (Compound 13) and
Cytostatic, Cytotoxic and Antiviral Activity
Generally, none of the compounds were inhibitory to
DNA, RNA and retroviruses at subtoxic concentrations. The

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 61
Table 2. Anti-HIV Potential of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives in MT-4 Cellsa)
Compound
EC50 (ꢀg/ml)
CC50b (ꢀg/ml)
HIV-1 (IIIb)
HIV-2 (ROD)
Training Set
1
2
>125.00
>125.00
>125.00
>125.00
>125.00
>125.00
3
4
>105.15
>111.75
>104.53
>2.43
>105.15
>111.75
>104.53
>2.43
105.15 8.59
111.75 8.81
104.53 5.22
2.43 0.35
5
6
7
>61.85
>109.33
>25.83
>103.53
>83.65
>38.32
>61.85
>109.33
>25.83
>103.53
>83.65
>38.32
61.85 3.02
109.33 8.39
25.83 3.92
103.53 14.68
83.65 10.66
38.32 56.48
8
9
10
11
12
Test Set
13
>94.38
>125.00
>94.38
>125.00
>113.00
>12.14
94.38 29.33
>125.00
14
15
16
>113.00
>113.00 8.68
12.14 1.86
24.60 15.44
>4.0
>12.14
17
>24.60
>24.60
Nevirapine
Zidovudine
0.050 0.011
0.002 0.001
>4.0
0.002 0.001
>25
a50% Effective concentration or compound concentration required to inhibit virus-induced cytopathicity by 50%.
b50% Cytotoxic concentration or compound concentration required to reduce MT-4 cell viability by 50%.
results of antiviral activity against the various viruses are
presented in Tables 2-5. Compound 6 proved highly cy-
tostatic (CC50 for MT-4 cells: 2.4 ꢁg/ml), followed by com-
pounds 16, 9 and 12 (CC50: 12-38 ꢁg/ml). The other com-
pounds were not toxic at ꢀ 100 ꢁg/ml.
pounds 6 and 12 were found to be the most effective antibac-
terial agents having pMICbs values 2.31 and 2.14 ꢁM, re-
spectively. In case of S. aureus compounds 5 and 7 have
shown marked antibacterial potential at pMICsa values 2.41
and 3.30 ꢁM, respectively. For antibacterial activity against
E. coli compounds 7 and 12 had shown better antibacterial
activity with pMICec values of 3.00 and 2.44 ꢁM, respec-
tively. The antibacterial potential of compound 12 was found
to be better than the standard drug norfloxacin.
Antibacterial and Antifungal Activity
The synthesized N2-acyl isonicotinic acid hydrazide de-
rivatives [1-17] were evaluated, in vitro, for their antibacte-
rial activity against Gram positive Staphylococcus aureus,
Bacillus subtilis, Gram negative Escherichia coli and anti-
fungal activity against Candida albicans and Aspergillus
niger by the serial dilution method [20] using norfloxacin
and fluconazole as reference standards for antibacterial and
antifungal activity, respectively, and the results are presented
in Table 6.
The antifungal activity against C. albicans revealed that
compounds 5 and 7 were the potential candidates having
pMICca values 2.71 and 3.00 ꢁM, respectively. The antifun-
gal activity of compound 7 was higher than the standard drug
fluconazole against C. albicans. In case of A. niger com-
pounds 4 and 12 were found to be active with pMICan values
2.42 and 2.44 ꢁM, respectively.
It can be observed from the results presented in Table 6
that the synthesized N2-acyl isonicotinic acid hydrazide de-
rivatives have higher antifungal potential particularly against
The results of antibacterial activity against B. subtilis in-
dicated that all the synthesized derivatives have higher anti-
bacterial potential than isoniazid. In particular the com-

62 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 3. Cytotoxicity and Anti-DNA Virus Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives in HEL Cell
Cultures
EC50b (ꢀg/ml)
Minimum Cytotoxic
Compound
Concentrationa (ꢀg/ml)
Herpes Simplex
Virus-1 (KOS)
Herpes Simplex
Virus-2 (G)
Herpes Simplex Virus-
1 TK- KOS ACVr
Vaccinia Virus
Training Set
1
2
>100
>100
>100
>100
>100
ꢀ0.8
>100
>100
>100
>100
>100
>0.8
>20
>100
>100
>100
>100
>100
>0.8
>20
>100
>100
>100
>100
>100
>0.8
>20
>100
>100
>100
>100
>100
>0.8
>20
3
4
5
6
7
100
8
>100
>100
>100
>100
100
>100
>100
>100
>100
>20
>100
>100
>100
>100
>20
>100
>100
>100
>100
>20
>100
>100
>100
>100
>20
9
10
11
12
Test Set
13
14
15
16
17
>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
aRequired to cause a microscopically detectable alteration of normal cell morphology.
bRequired to reduce virus-induced cytopathicity by 50%.
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.
hanced the antimicrobial activity of the synthesized
derivatives (Compound 3). This fact is supported by
the results of Emami et al. [40].
4. The synthesized derivatives were more active to-
wards the Gram-negative bacterium E. coli than
Gram-positive B. subtilis and S. aureus. This finding
is in agreement with Sbardella et al. [41].
STRUCTURE ACTIVITY RELATIONSHIP
From the Results of Antimicrobial Activity, the Follow-
ing Structure Activity the Relationship can be Drawn
1. The antifungal potential of N2-acyl isonicotinic acid
hydrazide derivatives was higher than the antibacte-
rial activity, which shows that different structural re-
quirements are essential for antibacterial and antifun-
gal activity. These results are similar to those of
Sortino et al. [39].
5. It was observed from the results of antimicrobial ac-
tivity that the introduction of m-methyl group in com-
pound 2 in comparison to unsubstituted derivatives
(compound 1) did not appreciably enhanced the
growth inhibition potential of synthesized derivatives.
6. The compound 9, derived from cinnamic acid, has
better antibacterial activity as compared to unsubsti-
tuted derivative (compound 1). This may be due to
the presence of extended conjugation in cinnamic
acid residue which may be involved in effective bind-
ing of synthesized compound with the target site. This
fact is supported by one of our earlier studies [42].
2. Similar to the observations of Guven et al. [37], the
presence of substitutent at ortho position increased
the antibacterial and antifungal potential of the com-
pounds which can be seen from the antimicrobial ac-
tivity of compounds 5, 6, 7 and 8.
3. The results of antimicrobial activity depicted that
the presence of electron donating OCH3 group en-

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 63
Table 4. Cytotoxicity and Anti-RNA Virus Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives in HeLa Cell
Cultures
EC50b (ꢀg/ml)
Minimum Cytotoxic Concentrationa
Compound
Vesicular Stomatitis
Virus
(ꢀg/ml)
Coxsackie Virus B4
Respiratory Syncytial Virus
Training Set
>100
>100
>100
>100
>100
>4
1
2
>100
>100
>100
>100
>100
ꢀ4
>100
>100
>100
>100
>100
>4
>100
>100
>100
>100
>100
>4
3
4
5
6
7
100
>20
>20
>20
8
>100
100
>100
>20
>100
>20
>100
>20
9
10
11
12
>100
>100
100
>100
>100
>20
>100
>100
>20
>100
>100
>20
Test Set
>100
>100
>100
>100
>100
13
14
15
16
17
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
aRequired to cause a microscopically detectable alteration of normal cell morphology.
bRequired to reduce virus-induced cytopathicity by 50%.
Table 5. Cytotoxicity and Anti-RNA Virus Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives in Vero Cell Cul-
tures
EC50b (ꢀg/ml)
Minimum Cytotoxic
Compound
Concentrationa (ꢀg/ml)
Para Influenza-3
Virus
Sindbis
Virus
Coxsackie Virus
B4
Punta Toro
Virus
Reovirus-1
Training Set
1
2
3
4
5
6
7
8
>100
>100
>100
>100
>100
ꢀ4
>100
>100
>100
>100
>100
>4
>100
>100
>100
>100
>100
>4
>100
>100
>100
>100
>100
>4
>100
>100
>100
>100
>100
>4
>100
>100
>100
>100
>100
>4
100
>20
>20
>20
>20
>20
>100
>100
>100
>100
>100
>100

64 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 5. contd….
EC50b (ꢀg/ml)
Minimum Cytotoxic Concentra-
Compound
tiona (ꢀg/ml)
Para Influenza-3
Virus
Sindbis
Virus
Coxsackie Virus
B4
Punta Toro
Reovirus-1
Virus
9
>100
>100
>100
20
>100
>100
>100
>4
>100
>100
>100
>4
>100
>100
>100
>4
>100
>100
>100
>4
>100
>100
>100
>4
10
11
12
Test Set
13
14
15
16
17
>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
>100
>100
>100
>100
>100
aRequired to cause a microscopically detectable alteration of normal cell morphology.
bRequired to reduce virus-induced cytopathicity by 50%.
Replacement with long
alipahtic alkyl chain
Increases antimycobacterial activity
Increases antimicrobial activity
Increases antimycobacterial activity
Increases antifungal activity against A. niger
NO2
O
H
N
H
N
Y
O
C
Increases antimycobacterial activity
Increases antimicrobial activity
Cl
R'
Decreases antimycobacterial activity
Increases antimicrobial activity
X
OH
N
Increases antimycobacterial activity
Increases antimicrobial activity
I
Essential for
antimycobacterial activity
Decreases antimycobacterial activity
Decreases antimicrobial activity
CH3
Replacement with small
alipahtic alkyl chain
Decreases antimycobacterial activity
Decreases antimicrobial activity
Fig. (1). Structural requirements for the antimycobacterial and antimicrobial activity of synthesized N2-acyl isonicotinic acid hydrazide de-
rivatives.
7. Compound 7 having 2,3,5-triiodo substitution on
phenyl nucleus was found to be most active antimi-
crobial agent among the synthesized derivatives. This
may be attributed to the presence of iodine atom in
the molecular structure.
cans and Aspergillus niger and compound 13 which was less
active against Gram positive Bacillus subtilis. Compound 14
was equipotent to standard drug fluconazole for antifungal
activity against C. albicans. Compound 17 was highly active
antimicrobial agent against Gram negative Escherichia coli
and fungus Candida albicans and Aspergillus niger.
The SAR findings of the antimycobacterial and antimi-
crobial activity are summarized in Fig. (1).
QSAR STUDIES
The test set synthesized after the QSAR studies was also
evaluated for antimicrobial activity against all the strains
tested above. The results of antimicrobial activity studies
revealed that the synthesized test set was more active than
isonicotinic acid hydrazide except compound 15 which was
less active against Gram positive Staphylococcus aureus,
Gram negative Escherichia coli and fungus Candida albi-
Development of One-target (ot) QSAR Model
QSAR analysis is an area of computational research
which builds models of biological activity using physico-
chemical properties of a series of compounds. QSAR ap-
proach is based on the assumption that the behavior of a
compound, expressed by any measured activities, is corre-

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 65
lated with the molecular features of the compound, termed
descriptors. After calculation of the molecular descriptors,
the commonly used linear methods, such as linear regression
(LR) and multiple linear regression (MLR), can be used in
the development of a relationship between the structure de-
scriptors and the activity [30]. By definition, a model is not
reality and does not replace reality (e.g. experiments and
observations). A model considers some selected and relevant
elements of a phenomenon and attempts to mimic their be-
havior in such a way that predictions can be made. A model
is useful in those situations in which either we do not want or
we cannot carry out direct experiments. Thus, the key fea-
tures of a model are (a) the phenomenological elements that
it represents and (b) the accuracy of the representation [43].
To obtain suitable equations two factors were taken into ac-
count [44].
In the present study, a training data set of 13 compounds
(12 N2-acyl isonicotinic acid hydrazide derivatives along
with isoniazid itself) was subjected to linear free energy re-
gression analysis for model generation. During the regres-
sion analysis studies it was observed that the response values
of compound 6 were outside the limits of response values of
other synthesized N2-acyl isonicotinic acid hydrazide deriva-
tives. Thus compound 6 was designated as an outlier and it
was not involved in the data set for QSAR model generation.
In multivariate statistics, it is common to define three types
of outliers [53].
1. X/Y relation outliers are substances for which the
relationship between the descriptors (X variables) and
the dependent variables (Y variables) is not the same
as in the (rest of the) training data.
2. X outliers. Briefly, a substance is an X outlier if the
molecular descriptors for this substance do not lie in
the same range as the (rest of the) training data.
1. A ratio of compounds to variables greater than 5.
2. An intercorrelation among the independent variables
smaller than 0.6.
3. Y outliers are only defined for training or test sam-
ples. They are substances for which the reference
value of response is invalid.
In order to identify the substituent effect on the antimi-
crobial activity, quantitative structure activity relationship
(QSAR) studies between the in vitro antimicrobial activity
and descriptors coding for lipophilic, electronic, steric and
topological properties of the 12 synthesized N2-acyl isonico-
tinic acid hydrazide derivatives were undertaken, using the
linear free energy relationship model (LFER) described by
Hansch and Fujita [45]. Biological activity data determined
as MIC values was first transformed into pMIC values (i.e. –
log MIC) to get all the values positive, normal distribution of
errors and to get linear free energy relationship of these data
with physicochemical properties and used as dependent vari-
able in QSAR study.
A compound was considered as an outlier for deriving a
particular model when the residual value exceeded twice the
standard error of estimate of the model [54]. In light of the
above guidelines, Compound 6 was considered as outliers
because its response values (antimicrobial activity) were
outside the range in comparison to the other compounds in-
cluded in the present study.
Based on the colinearity problem among the descriptors
and their contribution towards the biological activity, differ-
ent descriptors and/or a combination of descriptors were sub-
jected to linear regressions using SPSS. Preliminary analysis
was carried out in terms of correlation analysis. A correlation
matrix constructed for antibacterial activity against S. aureus
is presented in Table 8. The correlations of different molecu-
lar descriptors with antibacterial and antifungal activity are
presented in Table 9. In general, high colinearity (r > 0.8)
was observed between different parameters. The highest in-
The thermodynamic, spatial, electronic and topological
parameters calculated for QSAR analysis are presented in
Table 7. Thermodynamic parameters describe free energy
change during drug receptor complex formation. Spatial pa-
rameters are the quantified steric features of drug molecules
required for its complimentary fit with receptor. Electronic
parameters describe weak non-covalent bonding between
drug molecules and receptor [46]. The different molecular
descriptors (independent variables) like log of octanol–water
partition coefficient (log P), molar refractivity (MR), Kier’s
0
1
terrelationship was observed between ꢀ and ꢀ (r = 0.994)
and lowest interrelationship was observed between Cosmic E
3
and ꢀv (r = -0.103). The correlation matrix indicated the
predominance of topological parameters in describing the
antimicrobial activity of the synthesized compounds. The
statistical quality of the models was gauged by the parame-
ters like correlation coefficient (r) or squared correlation
coefficient (r2), standard error of estimate (s), variance ratio
(F). In order to corroborate the validity of the derived QSAR
models, leave-one-out (LOO) method was used. Each com-
pound is eliminated once, a model is derived from the re-
maining compounds and the eliminated compounds are pre-
dicted from this model. The same procedure is repeated after
elimination of another compound until all the compounds
have been eliminated once. Sum of squared prediction errors
called predictive residual sum of squares (PRESS) statistic is
calculated as the sum of squares of the differences between
predicted and observed values of the activity. Standard de-
viation of prediction (Spress), the cross-validated correlation
coefficient (q2) and standard deviation error of predictions
0
1
1
2
2
molecular connectivity (0ꢀ, ꢀv, ꢀ, ꢀv, ꢀ, ꢀv) and shape
(ꢁ1, ꢁ2, ꢁ3, ꢁꢀ1, ꢁꢀ2, ꢁꢀ3) topological indices, Randic topo-
logical 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 (ꢀ), nuclear re-
pulsion energy (Nu.E) and electronic energy (Ele.E), calcu-
lated for isoniazid derivatives are presented in Table 7 [47-
52].
For Hansch analysis, regression was performed using
pMIC values as dependent variables and calculated parame-
ters as independent variables. Out of hundreds of equations
generated, some of the best QSAR equations are given be-
low. These equations were generated in stepwise manner by
forward selection method starting with best single variable
and adding further significant variable according to their
contribution to the model.

66 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 6. Antibacterial and Antifungal Potential (ꢀM/mL) of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives
Comp.
pMICbs
pMICsa
pMICec
pMICca
pMICan
pMICb
pMICf
pMICam
Training Set
2.59
1
2
1.98
2.01
1.78
1.82
2.11
2.31
1.79
2.04
2.03
1.91
2.02
2.14
1.74
0.15
1.98
2.01
2.08
2.12
2.41
2.01
3.30
2.04
2.03
1.91
2.02
2.14
2.04
0.38
2.29
2.31
2.38
2.12
2.11
2.31
3.00
2.34
2.33
2.21
2.02
2.44
1.74
0.25
2.29
2.31
2.38
2.42
2.41
2.31
2.09
2.34
2.03
1.91
2.32
2.44
2.04
0.17
2.08
2.11
2.08
2.02
2.21
2.21
2.70
2.14
2.13
2.01
2.02
2.24
1.84
0.19
2.44
2.31
2.53
2.42
2.56
2.46
2.55
2.34
2.18
1.91
2.32
2.44
2.19
0.18
2.23
2.19
2.26
2.18
2.35
2.31
2.64
2.22
2.15
1.97
2.14
2.32
1.98
0.16
2.31
3
2.68
4
2.42
5
2.71
6
2.61
7
3.00
8
2.34
9
2.33
10
11
12
INH
S.D.a
1.91
2.32
2.44
2.34
0.27
Test Set
2.61
13
14
15
16
17
1.71
2.04
1.99
2.00
2.15
2.61*
2.31
2.34
1.68
2.00
2.15
2.31
2.04
1.68
2.30
2.45
2.61*
2.31
2.34
2.11
2.14
1.78
2.10
2.25
2.61*
2.46
2.49
2.25
2.28
1.74
2.18
2.33
2.62
2.64
1.68
1.68
1.68
2.30
2.30
2.30
2.45
2.45
2.45
Std.
2.61*
2.64**
2.64**
2.64**
*Norfloxacin
**Fluconazole
a Standard deviation
(SDEP) were calculated for each model and taken as an es-
timate of the predictability of the models.
indices are numerical quantifiers of molecular topology and
are sensitive to bonding pattern, symmetry, content of het-
eroatom as well as degree of complexity of atomic neighbor-
hoods [55]. The valence third order molecular connectivity
index (3ꢀv) represents the molecules with highly branched
structure. In this case, the positive correlation was observed
between 3ꢀv and antibacterial activity against S. aureus which
means the activity will increase with increase in value of
molecular descriptor 3ꢀv. The results presented in the Table 6
are in concordance with the model expressed by Eq. 1 and
values of 3ꢀv shown in Table 7 which depicts that compounds
The QSAR model represented by Eq. 1 correlates the an-
tibacterial activity of synthesized N2-acyl isonicotinic acid
hydrazide derivatives against S. aureus with molecular de-
scriptors and demonstrated that the antibacterial potential is
governed by the valence third order molecular connectivity
topological index (3ꢀv) (Eq. 1).
QSAR Model for Antibacterial Activity Against S. aureus
3
5 and 7 having high ꢀv values (0.680 and 1.375) have got
pMICsa = 1.058 3ꢀv + 1.727
n = 12 r = 0.950
q2 = 0.640 s = 0.123 F = 93.05
Eq. 1
the highest antibacterial potential (2.41 and 3.30). The value
of r2 for Eq. 1 is 0.903 which means the QSAR model is able
to predict the 90.30% of variance.
Here and thereafter, n - number of data points, r - corre-
lation coefficient, q2 - cross validated r2 obtained by leave
one out method, s - standard error of the estimate and F -
Fischer statistics.
To systematically assess a prediction algorithm, a reliable
validation is required. Usually, a predictive method is evalu-
ated by the predictive results for a training data set and test-
ing data set, respectively. According to the statistical termi-
nology, the former is called a test of resubstitution, and the
latter is a test of cross-validation. By the test of resubstitu-
For antibacterial activity against S. aureus, the developed
QSAR model (Eq. 1) describes the importance of valence
third order molecular connectivity index (3ꢀv). Topological

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 67
tion, the value of each compound in a training data set is
predicted using the rules derived from the same set. Al-
though this test gives somewhat optimistic error estimate
because the same compounds are used to derive the predic-
tion rules and to predict themselves, the resubstitution test is
absolutely necessary due to its ability of reflecting the self-
consistency of a given method. On the other hand, a cross-
validation test for an independent testing data set is also
needed because it can reflect the generalizing effectiveness
of a predictive method. Of various cross-validation tests, the
LOO test is thought to be a reliable one. Both tests of resub-
stitution and LOO [28] were used to evaluate the prediction
of models developed in the current study. In the resubstitu-
tion test, three statistical parameters viz. regression coeffi-
cient (r), root mean square error (RMSE) and absolute aver-
age error (eꢀ) were used to evaluate the performance. The
QSAR model expressed by Eq. 1 was cross validated by its
high q2 values (q2 = 0.640) obtained with leave one out
(LOO) method. The value of q2 greater than 0.5 is the basic
requirement for qualifying a QSAR model to be valid one
[56]. The comparison of observed and predicted antibacterial
activities is presented in Table 10. It can be seen from the
results 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 re-
sidual pMIC activity values were also developed to check
the statistical validity of QSAR models. The plot of pre-
dicted pMICsa against observed pMICsa (Fig. 2) also favors
the model expressed by Eq. 1. Further, the plot of observed
pMICsa Vs residual pMICsa (Fig. 3) indicated that there was
no systemic error in model development as the propagation
of error was observed on both sides of zero [29].
QSAR Model for Antifungal Activity Against C. Albicans
pMICca = 0.609 3ꢃv + 2.192
Eq. 6
n = 12 r = 0.757 q2 = 0.431 s = 0.186 F = 13.43
QSAR Model for Antifungal Activity Against C. Albicans
Developed by MLR
pMICcaMLR = 0.090 0ꢃv - 0.063 ꢁ2 + 1.920
n = 12 r = 0.819 q2 = 0.354
s = 0.172 F = 9.17
QSAR Model for Antifungal Activity Against A. Niger
Eq. 7
pMICan = 0.0000236 NuE + 1.832
Eq. 8
n = 12 r = 0.712 q2 = 0.338 s = 0.133 F = 10.34
QSAR Model for Antifungal Activity Against A. Niger
Developed by MLR
pMICanMLR = - 0.0076 MR + 0.126 1ꢃ + 1.627
n = 12 r = 0.763 q2 = 0.298 s = 0.129 F = 6.27
Eq. 9
The model expressed by Eq. 2 demonstrated that antibac-
terial activity against B. subtilis is governed by the cosmic
energy of the molecule (Cosmic E). The model expressed by
Eq. 2 is a monoparametric one and if we go for multiple lin-
ear regression model generation we got the biparametric
QSAR models with higher r values which is represented by
Eq. 3 and indicated that addition of molecular descriptor
valence third order molecular connectivity index (3ꢃv) in-
creased the r value from 0.779 to 0.841. The model ex-
pressed by Eq. 3 has good predictability as evidenced by the
low residual values in Table 10.
Equations 2-9 were developed to predict the antibacterial
and antifungal activity of N2-acyl isonicotinic acid hydrazide
derivatives against B. subtilis, E. coli, C. albicans and A.
niger.
In case of E. coli, the model expressed by Eq. 4 depicts
the importance of valence zero order molecular connectivity
index (0ꢃv) in describing the antibacterial activity of synthe-
sized derivatives. Similarly in this case also, the biparametric
model expressed by Eq. 5, obtained by multiple linear re-
gression demonstrated that a combination of valence zero
order molecular connectivity index (0ꢃv) and Kier’s first or-
der alpha shape topological index (ꢁꢂ1) best describes the
antibacterial activity of the synthesized derivatives which
can be seen from the low residual values obtained by Eq. 5
(Table 10).
QSAR Model for Antibacterial Activity Against B. Sub-
tilis
pMICbs = - 0.00693 Cosmic E + 1.997
n = 12 r = 0.779 q2 = 0.168 s = 0.089 F = 15.47
Eq. 2
QSAR Model for Antibacterial Activity Against B. Sub-
tilis Developed by MLR
pMICbsMLR = - 0.0072 Cosmic E - 0.128 3ꢃv + 2.053 Eq. 3
n = 12 r = 0.841 q2 = 0.262 s = 0.081 F = 10.87
The model described by Eq. 6 demonstrated the impor-
tance of valence third order molecular connectivity index
(3ꢃv) governs the antifungal activity of N2-acyl isonicotinic
acid hydrazide derivatives against C. albicans. The positive
correlation of the molecular descriptor with antifungal activ-
ity reveals that increase in 3ꢃv value will lead to an increase in
antifungal activity against C. albicans (Table 7). In this case
also, the multiple linear regression analysis was found to be
superior and demonstrated that model represented by Eq. 7
obtained by combining valence zero order molecular connec-
tivity index (0ꢃv) and Kier’s third order shape topological
index (ꢁ3) is effective in describing the antifungal activity of
N2-acyl isonicotinic acid hydrazide derivatives against C.
albicans.
QSAR Model for Antibacterial Activity Against E. Coli
pMICec = 0.0762 0ꢃv + 1.419
Eq. 4
n = 12 r = 0.783 q2 = 0.362 s = 0.195 F = 15.89
QSAR Model for Antibacterial Activity Against E. Coli
Developed by MLR
pMICecMLR = 0.166 0ꢃv -0.083 ꢁꢂ1 + 1.646
n = 12 r = 0.884 q2 = 0.616 s = 0.154 F = 16.16
Eq. 5

68 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 7. Value of Selected Descriptors Used in the Regression Analysis
Cosmic
E
Comp.
log P
MR
0ꢁ
0ꢁv
1ꢁ
2ꢁ
3ꢁ
3ꢁv
ꢂ3
ꢂꢀ
ꢂꢀ
Te
Ele.E
Nu.E
1
3
Training Set
-
14927.8
00
1
2
9.772
6.076
1.565
2.033
1.060
1.473
2.534
1.281
5.338
1.607
1.973
0.756
2.262
4.640
0.020
65.489
70.530
78.415
80.138
79.648
67.183
102.713
69.167
75.732
55.637
72.948
100.554
36.930
12.795
13.665
15.949
17.690
15.242
13.665
15.405
13.665
14.209
11.096
13.924
18.167
7.400
9.460
10.383
12.122
11.833
12.403
9.830
8.771
9.165
10.651
11.380
10.059
9.182
9.986
9.182
9.754
7.236
9.236
12.236
4.840
7.328
7.962
8.840
10.405
8.949
7.856
9.007
7.856
8.139
5.847
7.261
9.382
2.750
0.805
1.093
1.138
1.805
1.382
1.010
1.491
1.010
0.895
0.691
0.691
0.691
0.269
0.435
0.387
0.492
0.680
0.322
1.375
0.391
0.290
0.193
0.207
0.207
1.710
4.566
4.795
5.263
6.046
5.606
4.500
4.733
4.500
6.120
5.040
8.000
12.907
8.100
12.486
13.461
16.323
17.503
15.989
13.422
17.572
14.068
14.185
11.624
15.866
21.852
7.250
3.510
3.744
4.226
4.573
4.828
3.480
4.845
3.804
4.763
4.059
7.086
11.901
121.00
-3075.320
-3231.190
-4026.950
-4736.730
-3951.280
-3395.970
-4075.950
-3500.280
-3358.530
-2691.500
-3343.390
-4278.400
-1804.500
18003.1
00
-
16581.8
00
19813.0
00
-
22383.1
00
26410.1
00
3
17.813
17.235
-5.663
2.965
-
24982.1
00
4
29718.9
00
-
19171.5
00
5
23122.8
00
-
16753.0
00
6*
7
20149.0
00
-
19653.7
00
7.990
16.918
10.448
10.615
8.228
23729.6
00
-
16821.1
00
8
-3.267
-0.866
-3.726
-3.546
-3.525
47.800
20321.4
00
-
16833.8
00
9
20192.3
00
-
11492.4
00
10
11
12
INH
14183.9
00
-
17377.8
00
11.316
15.558
5.240
20721.2
00
-
25739.7
00
30018.1
00
-
8006.92
0
6202.42
0
3.780
Test Set
1.093
-
17118.6
00
13
14
15
16
2.411
7.970
1.281
1.313
0.718
2.987
4.898
67.183
71.952
63.300
75.800
105.538
13.665
14.372
12.795
13.339
18.899
9.830
10.791
9.330
9.165
9.703
8.771
9.360
13.254
7.962
8.131
7.328
7.517
10.967
0.343
0.337
0.269
0.231
0.404
4.795
5.058
4.566
5.878
6.780
13.422
14.400
12.808
13.637
18.878
3.724
3.991
3.680
4.765
5.288
-3395.920
-3551.220
-3140.290
-3037.820
-4308.300
20514.5
00
-
18627.4
00
1.009
0.805
0.606
1.058
22178.7
00
-
14980.4
00
2.532
18120.7
00
-
14415.5
00
13.515
37.021
10.231
14.473
17453.3
00
-
26850.1
00
17
31158.4
00
*Outlier

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 69
Table 8. Correlation Matrix for Antibacterial Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives Against S.
Aureus
Cosmic E
1.000
log P
0ꢁ
1ꢁ
2ꢁ
3ꢁ
3ꢁv
ꢂ1
Te
Ele.E
Nu.E
pMICsa
Cosmic E
log P
0ꢁ
-0.449
-0.491
-0.519
-0.457
-0.136
-0.103
-0.520
0.408
1.000
0.617
0.614
0.575
0.306
0.645
0.636
-0.578
-0.577
0.575
0.734
1.000
0.994
0.972
0.642
0.345
0.983
-0.975
-0.993
0.992
0.278
1ꢁ
1.000
0.961
0.586
0.296
0.982
-0.951
-0.983
0.983
0.232
2ꢁ
1.000
0.783
0.462
0.914
-0.980
-0.960
0.953
0.344
3ꢁ
1.000
0.701
0.508
-0.773
-0.645
0.625
0.511
3ꢁv
1.000
0.237
-0.465
-0.328
0.307
0.950
ꢂ1
1.000
-0.931
-0.976
0.979
0.213
Te
1.000
0.978
-0.971
-0.378
Ele.E
Nu.E
pMICsa
0.405
1.000
-1.000
-0.267
-0.403
-0.031
1.000
0.250
1.000
Table 9. Correlation of Molecular Descriptors with Antimicrobial Activity of Synthesized N2-acyl Isonicotinic Acid Hydrazide
Derivatives
Mol. Descriptor
pMICbs
pMICsa
pMICec
pMICca
pMICan
pMICb
pMICf
pMICam
Cosmic E
log P
MR
0ꢁ
-0.779
0.318
0.284
0.321
0.225
0.380
0.367
0.264
0.243
-0.160
-0.234
0.385
0.546
0.589
0.369
0.519
0.561
0.380
-0.246
0.398
-0.184
-0.245
0.253
-0.031
0.734
0.611
0.278
0.685
0.232
0.563
0.344
0.744
0.511
0.950
0.213
-0.001
-0.055
0.361
0.144
0.067
0.232
-0.187
0.160
-0.378
-0.267
0.250
-0.378
0.762
0.768
0.510
0.783
0.511
0.699
0.538
0.773
0.416
0.732
0.459
0.286
0.186
0.548
0.368
0.257
0.511
-0.436
0.374
-0.509
-0.473
0.466
0.105
0.571
0.598
0.416
0.642
0.404
0.544
0.486
0.667
0.523
0.757
0.329
0.081
-0.033
0.412
0.166
0.047
0.404
-0.503
0.298
-0.490
-0.431
0.421
-0.192
0.217
0.442
0.674
0.418
0.681
0.467
0.651
0.378
0.390
-0.001
0.661
0.543
0.449
0.608
0.491
0.417
0.681
-0.373
0.647
-0.657
-0.708
0.713
-0.371
0.883
0.803
0.484
0.843
0.470
0.759
0.525
0.878
0.476
0.880
0.434
0.256
0.185
0.565
0.379
0.287
0.470
-0.376
0.364
-0.515
-0.443
0.432
-0.016
0.522
0.649
0.625
0.669
0.620
0.621
0.666
0.668
0.568
0.553
0.556
0.319
0.191
0.591
0.356
0.234
0.620
-0.544
0.527
-0.672
-0.653
0.648
-0.269
0.847
0.845
0.609
0.882
0.597
0.801
0.656
0.906
0.579
0.858
0.544
0.317
0.211
0.651
0.419
0.302
0.597
-0.501
0.481
-0.650
-0.592
0.581
0ꢁv
1ꢁ
1ꢁv
2ꢁ
2ꢁv
3ꢁ
3ꢁv
ꢂ1
ꢂ2
ꢂ3
ꢂꢀ
1
ꢂꢀ
2
ꢂꢀ
3
R
J
W
Te
Ele.E
Nu.E

70 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 10. Comparison of Observed and Predicted Antibacterial and Antifungal Activity Obtained by ot-QSAR Model
pMICsa (Eq. 1)
pMICbsMLR (Eq. 3)
pMICecMLR (Eq. 5)
Obs. Pre. Res.
pMICcaMLR (Eq. 7)
pMICanMLR (Eq. 9)
Comp.
Obs.
Pre.
Res.
Obs.
Pre.
Res.
Obs.
Pre.
Res.
Obs.
Pre.
Res.
Training Set
1
2
1.98
2.01
2.08
2.12
2.41
3.30
2.04
2.03
1.91
2.02
2.14
2.04
2.01
2.19
2.14
2.25
2.45
3.18
2.14
2.03
1.93
1.95
1.95
1.87
-0.03
-0.18
-0.06
-0.13
-0.04
0.12
1.98
2.01
1.78
1.82
2.11
1.79
2.04
2.03
1.91
2.02
2.14
1.74
1.95
1.95
1.88
1.87
2.01
1.82
2.03
2.02
2.06
2.05
2.05
1.69
0.03
0.06
-0.10
-0.05
0.10
-0.03
0.01
0.01
-0.15
-0.03
0.09
0.05
2.29
2.31
2.38
2.12
2.11
3.00
2.34
2.33
2.21
2.02
2.44
1.74
Test Set
2.31
2.31
2.04
1.68
2.30
2.45
2.18
2.25
2.30
2.16
2.38
3.00
2.21
2.23
2.05
2.21
2.41
1.91
0.11
0.06
0.08
-0.04
-0.27
0.00
0.13
0.10
0.16
-0.19
0.03
-0.17
2.59
2.31
2.68
2.42
2.71
3.00
2.34
2.33
1.91
2.32
2.44
2.34
2.37
2.44
2.57
2.49
2.57
3.03
2.47
2.38
2.23
2.32
2.37
2.15
0.22
-0.13
0.11
2.29
2.31
2.38
2.42
2.41
2.09
2.34
2.03
1.91
2.32
2.44
2.04
2.24
2.25
2.38
2.45
2.29
2.11
2.26
2.28
2.12
2.24
2.41
1.96
0.05
0.06
0.00
-0.03
0.12
-0.02
0.08
-0.25
-0.21
0.08
0.03
0.08
3
4
-0.07
0.14
5
7
-0.03
-0.13
-0.05
-0.32
0.00
8
-0.10
0.00
9
10
11
12
INH
-0.02
0.07
0.19
0.07
0.17
0.19
6
2.01
2.31
2.34
1.68
2.00
2.15
2.07
2.10
2.09
2.02
1.98
2.16
-0.06
0.21
0.25
-0.34
0.02
-0.01
2.31
1.71
2.04
1.99
2.00
2.15
1.99
1.99
1.96
2.00
1.93
1.74
0.32
-0.28
0.08
-0.01
0.07
0.41
2.14
2.14
2.22
2.11
2.19
2.47
0.17
0.17
2.61
2.61
2.64
1.68
2.30
2.45
2.39
2.37
2.44
2.34
2.34
2.65
0.22
0.24
2.31
2.31
2.34
1.68
2.30
2.45
2.27
2.27
2.30
2.25
2.23
2.50
0.04
0.04
0.04
-0.57
0.07
-0.05
13
14
14
16
17
-0.18
-0.43
0.11
0.20
-0.66
-0.04
-0.20
-0.02
.2
.1
3.2
3.0
2.8
2.6
2.4
2.2
0.0
-.1
-.2
2.0
1.8
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
Observed pMICsa
Observed pMICsa
Fig. (3). Plot of residual pMICsa against the experimental pMICsa
for the linear regression model developed by Eq. 1.
Fig. (2). Plot of observed pMICsa against the predicted pMICsa for
the linear regression model developed by Eq. 1.

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 71
For antifungal activity against A. niger, the developed
QSAR model (Eq. 8) indicated the predominance of nuclear
repulsion energy in describing the antifungal activity. The
nuclear repulsion energy between two atoms (A and B) is
given by
narrow range. Further, recent literature reveals that the
QSAR have been applied to describe the relationship be-
tween narrow range of biological activity and physicochemi-
cal properties of the molecules [42, 61-63]. When biological
activity data lies in the narrow range, the presence of mini-
mum standard deviation of the biological activity justifies its
use in QSAR studies [42, 29]. The minimum standard devia-
tion (Table 6) observed in the antimicrobial activity data
justifies its use in QSAR studies. The value of PRESS (pre-
dictive residual sum of squares which is also termed as least
square error (LSE)) < sum of squares of response values
(SSY) is an indicative of statistical significance of prediction
of QSAR models [64] which can be easily clarified by their
values listed in Table 11. In 2D-QSAR, the internal consis-
tency of the models using q2 is assessed with the ratio RQR
= q2/r2 [65]. Considering RQR for the QSAR models repre-
sented by Eq. 1, 3, 5, 7 and 9 (Table 12), it is pleasing that
the lowest value is RQR = 0.371 for QSAR Model 3 and
there is a gradual, roughly monotonic increase across the
series to RQR = 0.788. Thus the QSAR models we present
are statistically robust. The low value of probable error of
the coefficient of correlation (PE), least square error (LSE),
Friedman’s lack of fit measure (LOF), standard error of pre-
diction (SEP), and SSY (sum of squares of response values),
standard deviation of prediction (Spress), and standard de-
viation error of predictions (SDEP), root mean square error
(RMSE) and absolute average error (eꢂ) and high value of
quality value (Q), r2 and the cross-validated correlation coef-
ficient (q2) (Table 12 and Table 13) revealed the statistical
significance of the model described by Eq. 1, 3, 5, 7 and 9.
Also the value VIF < 5 indicates that MLR models expressed
by Eq. 3, 5, 7 and 9 are statistically valid [29]. The validity
of the developed ot-QSAR models was also confirmed the
prediction of antimicrobial activity of the test set compounds
by using these developed ot-QSAR models. The low residual
values of compounds 13-17 clearly indicated that the devel-
oped ot-QSAR models are statistically valid.
ENuE (AB) = ZAZB/RAB
where A – given atomic species; B – another atomic species;
ZA - charge of atomic nucleus A; ZB - charge of atomic nu-
cleus B; RAB - distance between the atomic nuclei, A and B
[57].
The coefficient of nuclear repulsion energy (NuE) is
positive, which shows that the antifungal activity will in-
crease with the increase in nuclear repulsion energy of the
synthesized compounds, which can be clearly seen from the
results of antifungal activity against A. niger (Table 6) and
values of nuclear repulsion energy presented in Table 7 that
compounds 4 and 12 having high NuE values (24982.100
and 25739.700 respectively) had got the highest antifungal
activity of 2.42 and 2.44 ꢀM. Further, the biparametric
model obtained by MLR analysis (Eq. 9) revealed that molar
refractivity (MR) and first order molecular connectivity in-
dex (1ꢁ) effectively describes the antifungal activity of syn-
thesized derivatives which can be seen from low residual
values of Eq. 9 (Table 10).
The molar refractivity is a constitutive additive property
that is calculated by Lorenz-Lorentz formula [58], as given
below
MR = (n2 -1 * MW)/( n2 + 2 * d)
Where MW is molecular weight, n is `the refraction index
and d is the density, and its value depends on the wave longi-
tude of the light used to measure the refraction index.
The low residual values presented in Table 10 are in
agreement with the fact that models expressed by Eq. 3, Eq.
5, Eq. 7 and Eq. 9 are also valid ones.
As in case of Eq. 1, the high q2 values (q2>0.5) supported
the validity of developed QSAR models described by Eq. 5.
The cross validated correlation coefficient (q2 > 0.5) values
obtained for best QSAR model indicated their reliability in
predicting the antimicrobial activity of synthesized com-
pounds. In case of all other developed QSAR models the
value of q2 is less than 0.5, which shows that the developed
model is an invalid one. But according to the recommenda-
tions of Kim et al. [59], 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 all of
these cases is less than 0.3, so the developed QSAR models
are valid.
Development of Multi-target (mt) QSAR Model
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 spe-
cies. 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 activity [66-70].
Generally for QSAR studies, the biological activities of
compounds should span 2-3 orders of magnitude. But in the
present study the range of antibacterial and antifungal activi-
ties of the synthesized compounds is within one order of
magnitude. It is important to note that the predictability of
the QSAR models developed in the present study is high
which is evidenced by their low residual values. This is in
agreement with results suggested by the Bajaj et al. [60],
who stated that the reliability of the QSAR model lies in its
predictive ability even though the activity data are in the
In the present study we have attempted to develop three
different 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 compounds
against C. albicans and A. niger as well a common mt-
QSAR model for describing the antimicrobial (overall anti-

72 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 11. PE, LSE, LOF, SEP, Q and SSY Values Calculated for the Derived Models for Modeling Antimicrobial Activity of Synthe-
sized N2-acyl Isonicotinic Acid Hydrazide Derivatives
S. No.
Descriptor
PE
LSE
LOF
SEP
Q
SSY
Eq. 1
Eq. 3
3ꢀv
0.018
0.056
0.042
0.063
0.081
0.012
0.106
0.009
0.0150
0.0621
0.0179
0.2656
0.1485
0.0276
0.2160
0.0162
0.0122
0.0031
0.0009
0.0131
0.0073
0.0014
0.0180
0.0008
0.0322
0.0208
0.0112
0.0429
0.0321
0.0138
0.0387
0.0106
7.724
10.383
5.740
4.762
5.915
17.304
4.634
23.240
0.558
0.150
0.376
0.517
0.252
0.057
0.306
0.040
Cosmic E, 3ꢀv
0ꢀv, ꢁꢀ1
Eq. 5
Eq. 7
0ꢀv, ꢁ
2
Eq. 9
1ꢀ, MR
log P, ꢁꢀ3
Te
Eq. 11
Eq. 12
Eq. 14
2ꢀv, ꢁ
3
Table 12. RMSE, eꢀ, SPress, SDEP, VIF, r2 and RQR Values Calculated for the Derived Models for Modeling Antimicrobial Activity
of Synthesized N2-acyl Isonicotinic Acid Hydrazide Derivatives
S.No.
Descriptor
RMSE
eꢀ
SPress
SDEP
VIF
r2
RQR
Eq. 1
Eq. 3
3ꢀv
0.112
0.072
0.134
0.149
0.111
0.048
0.134
0.037
0.093
0.059
0.112
0.122
0.084
0.038
0.105
0.030
0.356
0.114
0.265
0.223
0.137
0.200
0.125
0.170
0.117
0.075
0.140
0.155
0.116
0.050
0.140
0.038
-
0.903
0.707
0.782
0.671
0.583
0.939
0.452
0.953
0.709
0.371
0.788
0.528
0.511
0.937
0.469
0.925
Cosmic E, 3ꢀv
0ꢀv, ꢁꢀ1
3.41
4.59
3.04
2.39
16.39
-
Eq. 5
Eq. 7
0ꢀv, ꢁ
2
Eq. 9
1ꢀ, MR
log P, ꢁꢀ3
Te
Eq. 11
Eq. 12
Eq. 14
2ꢀv, ꢁ
21.09
3
bacterial and antifungal) activity of synthesized isoniazid
derivatives against all the above mentioned microorganisms.
mt-QSAR Model for Antibacterial Activity Developed by
MLR
In order to develop mt-QSAR models, initially we have
calculated the average antibacterial activity, antifungal activ-
ity and antimicrobial activity values of N2-acyl isonicotinic
acid hydrazide derivatives which are presented in Table 6.
These average activity values were also correlated with the
molecular descriptors of synthesized compounds (Table 9).
pMICbMLR = 0.169 log P - 0.044 ꢁꢀ3 + 1.994
n = 12 r = 0.969 q2 = 0.880 s = 0.056 F = 70.08
Eq. 11
The mt-QSAR model for antifungal activity revealed the
importance of total energy (Te) in describing antifungal ac-
tivity of synthesized derivatives and represented by Eq. 12.
The mt-QSAR model for antibacterial activity depicted
the importance of lipophilic parameter (log P) in describing
the antibacterial activity of synthesized N2-acyl isonicotinic
acid hydrazide derivatives, and presented in the model ex-
pressed by Eq. 10.
mt-QSAR Model for Antifungal Activity
pMICf = -0.00016 Te + 1.785
n = 12 r = 0.672 q2 = 0.212 s = 0.145 F = 8.23
Eq. 12
mt-QSAR Model for Antibacterial Activity
The mt-QSAR model for antimicrobial activity depicted
that valence second order molecular connectivity index (2ꢂv)
effectively describes the overall antimicrobial activity of the
synthesized derivatives and MLR models developed by the
combination of valence second order molecular connectivity
index (2ꢂv) with Kier’s third order shape topological index
(ꢁ3) and the models are represented by Eq. 13 and Eq. 14
respectively.
pMICb = 0.121 log P + 1.878
n = 12 r = 0.883 q2 = 0.457 s = 0.102 F = 35.39
Eq. 10
In this case also the MLR analysis gave the valid QSAR
modelwith high r and q2 values and elaborated that correlati-
on of logP with Kier’s third order shape topological index
(ꢂꢀ3) best describes the antibacterial potential of synthesized
derivatives and given by the model expressed by Eq.11.

Synthesis and Antimicrobial Evaluation of N2-Acyl Isonicotinic Acid Hydrazides
Medicinal Chemistry, 2013, Vol. 9, No. 1 73
mt-QSAR Model for Antimicrobial Activity
2.7
2.6
2.5
2.4
2.3
2.2
2.1
pMICam = 0.104 2ꢃv + 1.771
n = 12 r = 0.906 q2 = 0.685 s = 0.078 F = 45.74
Eq. 13
mt-QSAR Model for Antimicrobial Activity Developed
by MLR
pMICamMLR = 0.133 2ꢃv - 0.0298 ꢁ3 + 1.821
n = 12 r = 0.976 q2 = 0.882 s = 0.042
Eq. 14
F = 91.41
It was observed from mt-QSAR models [Eq. 10-14] that
the antibacterial, antifungal and overall antimicrobial activity
of synthesized N2-acyl isonicotinic acid hydrazide deriva-
tives is governed by energy parameters, viz. total energy (Te)
describing the antifungal activity and combination of log P
and Kier’s third order shape topological index (ꢁꢂ3) de-
scribes the antibacterial potential of the N2-acyl isonicotinic
acid hydrazide derivatives and the combination of valence
second order molecular connectivity index (2ꢃv) with Kier’s
third order shape topological index (ꢁ3) best describes the
overall antimicrobial activity. The developed mt-QSAR
models were statistically valid as they had the high r and q2
values and low residual values (Table 13). As in the case of
ot-QSAR models, the plot of predicted pMICamMLR against
observed pMICamMLR (Fig. 4) also favors the developed
model expressed by Eq. 14. Further, the plot of observed
pMICamMLR Vs residual pMICamMLR (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 negative residual values were observed.
The low value of probable error of the coefficient of correla-
tion (PE), least square error (LSE), Friedman’s lack of fit
measure (LOF), standard error of prediction (SEP), and SSY
(sum of squares of response values), standard deviation of
prediction (Spress), and standard deviation error of predic-
tions (SDEP), root mean square error (RMSE) and absolute
average error (eꢀ) and high value of quality value (Q) and
the cross-validated correlation coefficient (q2) (Table 11 and
Table 12) revealed the statistical significance of the model
described by Eq. 11 and 14. Similarly Considering RQR for
the QSAR models represented by Eq. 11, and 14 (Table 12),
it is observed that QSAR models form Eq. 11 and Eq. 14 has
got the RQR value of 0.933 and 0.925. Thus, here also the
QSAR models are statistically robust. The validity of the
developed mt-QSAR models was also confirmed the predic-
tion of antimicrobial activity of the test set compounds by
using these models and the low residual values of com-
pounds 13-17 clearly indicated that the developed mt-QSAR
models are statistically valid.
2.0
1.9
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
Observed pMICamMLR
Fig. (4). Plot of observed pMICamMLR against the predicted pMI-
CamMLR for the multiple linear regression model developed by
Eq. 14.
.10
.08
.06
.04
.02
0.00
-.02
-.04
-.06
-.08
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
Oberved pMICamMLR
Fig. (5). Plot of residual pMICamMLR against the experimental
pMICamMLR for the multiple linear regression model developed
by Eq. 14.
B. subtilis, E. coli, C. albicans and A. niger and the results
indicated that compounds with dichloro, hydroxyl, triiodo
and N2 –tetradecanoyl substituents were the most active an-
timicrobial agents. Compound 6 proved most cytostatic in
cell culture. To find out the correlation between physico-
chemical parameters and antibacterial and antifungal activity
of N2-acyl isonicotinic acid hydrazide derivatives, 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 antimicrobial activity of N2-
acyl isonicotinic acid hydrazide derivatives in comparison to
the one target models and indicated that the combination of
valence second order molecular connectivity index (2ꢃv) with
Kier’s third order shape topological index (ꢁ3) best describes
the overall antimicrobial activity.
CONCLUSION
A series of N2-acyl isonicotinic acid hydrazide deriva-
tives (1-17) was synthesized and tested for its in vitro an-
timycobacterial activity against Mycobacterium tuberculosis
and the compounds with dinitro, dichloro, N2-octanoyl and
N2-tetradecanoyl groups were found to be the most effective
and compound 12 was more active antitubercular agent than
isoniazid. The results of antiviral activity testing showed that
none of the tested compounds was active against any of the
viruses investigated. The synthesized compounds were also
screened for their antimicrobial potential against S. aureus,
DISCLOSURE
Some part of the information included in this paper has
been previously published in Drug Design & Discovery
Volume 8, Number 9, November 2011.

74 Medicinal Chemistry, 2013, Vol. 9, No. 1
Judge et al.
Table 13. Comparison of Observed and Predicted Antibacterial, Antifungal and Antimicrobial Activity Obtained by mt-QSAR
Model
pMICbMLR (Eq. 11)
Pre.
pMICf (Eq. 12)
Pre.
pMICamMLR (Eq. 14)
Pre.
Comp.
Obs.
Res.
Obs.
Res.
Obs.
Res.
Training Set
1
2
2.08
2.11
2.08
2.02
2.21
2.70
2.14
2.13
2.01
2.02
2.24
1.84
2.10
2.17
1.99
2.04
2.21
2.68
2.10
2.12
1.94
2.06
2.25
1.92
-0.02
-0.06
0.09
-0.02
0.00
0.02
0.04
0.01
0.07
-0.04
-0.01
-0.08
2.44
2.31
2.53
2.42
2.56
2.55
2.34
2.18
1.91
2.32
2.44
2.19
2.28
2.30
2.43
2.55
2.42
2.44
2.35
2.33
2.22
2.32
2.47
2.08
0.16
0.01
0.10
-0.13
0.14
0.11
-0.01
-0.15
-0.31
0.00
-0.03
0.11
2.23
2.19
2.26
2.18
2.35
2.64
2.22
2.15
1.97
2.14
2.32
1.98
2.15
2.21
2.22
2.22
2.33
2.66
2.20
2.16
2.03
2.17
2.30
1.98
0.08
-0.02
0.04
3
4
-0.04
0.02
5
7
-0.02
0.02
8
9
-0.01
-0.06
-0.03
0.02
10
11
12
INH
0.00
Test Set
6
2.21
2.11
2.14
1.78
2.10
2.25
2.05
2.05
2.04
1.98
2.23
2.46
0.16
0.06
2.46
2.46
2.49
1.68
2.30
2.45
2.32
2.32
2.35
2.27
2.25
2.48
0.14
0.14
0.14
-0.59
0.05
-0.03
2.31
2.25
2.28
1.74
2.18
2.33
2.17
2.16
2.18
2.13
2.13
2.36
0.14
0.09
0.10
-0.39
0.05
-0.03
13
14
15
16
17
0.10
-0.20
-0.13
-0.21
kinase inhibitors based on different alignment methods. Bioorg.
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CONFLICT OF INTEREST
[2]
[3]
Ali, M.A.; Yar, M.S.; Kumar, M.; Pandian, G.S. Synthesis and
antitubercular activity of substituted novel pyrazoline derivatives.
Nat. Prod. Res., 2007, 21(7), 575-579.
The authors report no conflicts of interest. The authors
alone are responsible for the content and writing of the
paper.
Ragno, R.; Marshall, G.R.; Santo, R.D.; Costi, R.; Massa, S.; Rom-
pei, R.; Artico, M. Antimycobacterial pyrroles: synthesis, antimy-
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ACKNOWLEDGEMENTS
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, Mrs.
Kristien Erven, Mr. Kris Uyttersprot, Mrs. Anita Camps,
Mrs. Lies Van den Heurck, Mr. Steven Carmans and Mrs.
Leen Ingels, Rega Institute for Medical Research, Belgium
for excellent technical assistance in the evaluation of
antiviral activity. Financial support was provided by the
GOA (no. 10/014) of the K.U. Leuven.
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[64]
Received: July 29, 2011
Revised: May 10, 2012
Accepted: May 27, 2012