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(0.015 mol) was added to ethanolic solution of ester (0.01 mol) synthesized above and refluxed for 5 h. The reaction
mixture was then cooled, and the precipitated hydrazide was separated and recrystallized from ethanol. A solution of
0.01 mol of above hydrazide and 0.01 mol of appropriate aldehyde, in ethanol, was heated under reflux for 4–5 h. The
precipitate obtained was filtered off, washed with water and recrystallized from ethanol.
Compound 9: 1H NMR (400 MHz, CDCl3): d 6.53–7.07 (m, 6H, Ar–OH and Ar–(OCH3)2), 1.33–1.36 (t, 3H, terminal
CH3 ofOCH2CH3), 4.04–4.07(q, 2H, CH2 ofOCH2CH3), 8.2(s, 1H, NHofCO–NH), 3.75(s, 6H, OCH3 ofAr–(OCH3)2),
5.2 (1H, S, OH of Ar–OH). Compound 10: 1H NMR (400 MHz, CDCl3): d 6.71–7.08 (m, 3H, Ar–OH), 9.28–9.36 (m, 3H,
Ar–(NO2)2), 1.38–1.41 (t, 3H, terminal CH3 of OCH2CH3), 3.96–3.98 (q, 2H, CH2 of OCH2CH3), 8.0 (s, 1H, NH of CO–
NH), 4.92 (s, 1H, OH of Ar–OH); Compound 19: 1H NMR (400 MHz, CDCl3): d 6.68–7.10 (m, 3H, Ar–(OCH3)2), 7.94–
1
8.27 (m, 3H, Ar–(NO2)), 3.92 (s, 6H, OCH3 of Ar–(OCH3)2), 8.4 (s, 1H, NH of CO–NH); Compound 20: H NMR
(400 MHz, CDCl3): d 8.07–8.41 (m, 4H, ArH of ArNO2), 9.17–9.23 (s, 3H, ArH of Ar(NO2)2), 10.17 (s, 1H, NH).
1.2. Evaluation of antimicrobial activity-determination of MIC
The antimicrobial activity was performed against Gram-positive bacteria: Staphylcococcus aureus, Bacillus
sublitis, Gram-negative bacterium: Escherichia coli and fungal strains: Candida albicans and Aspergillus niger by
tube dilution method [10] using double strength nutrient broth – I.P. (bacteria) or Sabouraud dextrose broth I.P. (fungi)
as media [11]. The samples were incubated at 37 8C for 24 h (bacteria), at 25 8C for 7 d (A. niger) and at 37 8C for 48 h
(C. albicans), and the results were recorded in terms of MIC.
1.3. QSAR studies
The structure of synthesized hydrazides was optimized by energy minimization and the physicochemical properties
were calculated using TSAR 3.3 software for Windows [12]. Further, the regression analysis was performed using the
SPSS software package [13]. The predictive powers of the equations were validated by leave one out (LOO) cross
validation method [14].
2. Results and discussion
The synthesis of target compounds was carried out as outlined in Scheme 1. All the compounds were obtained in
appreciable yield and their spectral and elemental analysis data are found in agreement with the assigned molecular
structures. The synthesized compounds (1–20) were screened for their in vitro antimicrobial activity and the results are
presented inTable 1. Itcanbeseenfrom theresults ofantimicrobialactivitythat theactivityincreaseswithincreaseinchain
length of acid portion of synthesized compounds (1–4 and 11–14). This is similar to one of our previous reports [9]. The
presence of electron withdrawing group (NO2) in compounds 10 and 20 makes them highly active antimicrobial agents.
The role ofelectronwithdrawing group inincreasing the antimicrobialactivityis similarto the results ofSharma etal. [15].
2.1. Development of multi-target QSAR model
QSAR studies were undertaken using linear free energy relationship (LFER) model of Hansch and Fujita [16].
Biological activity data determined as MIC values was first transformed to pMIC on molar basis, which was used as
dependent variable in QSAR study. The mt-QSAR model is a single equation that considers the nature of molecular
descriptors which are common and essential for describing the antimicrobial activity [17]. In the present study we have
developed mt-QSAR models for antibacterial, antifungal and antimicrobial activities of substituted benzylidene
hydrazides by taking average antibacterial, antifungal and antimicrobial activities respectively.
pMICb ¼ 0:4193x þ 0:873
(1)
(n = 20, r = 0.812, q2 = 0.571, s = 0.110, F = 34.80).
The mt-QSAR model described by Eq. (1) depicts the importance of third order molecular connectivity index (3x)
for antibacterial activity of substituted benzylidene hydrazides. We have attempted to combine different parameters so
as to increase the regression coefficient (r value), by multiple linear regressions.