Synthesis , antimicrobial evaluation and QSAR studies of N '-benzylidene / ( 1-phenylethylidene ) undec-10-enehydrazides

Article history: Received on: 15/01/2016 Revised on: 12/02/2016 Accepted on: 06/03/2016 Available online: 30/04/2016 A series of N'-benzylidene/(1-phenylethylidene)undec-10-enehydrazide was synthesized starting from undec-2enoic acid through multi-step reactions. Synthesized derivatives were evaluated for their in vitro antimicrobial activities against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Aspergillus niger and Candida albicans by tube dilution method. The preliminary results showed the significance of o-NO2, m-NO2 and mOCH3 groups at phenyl ring in describing antimicrobial activity of synthesized compounds. QSAR studies revealed that second order molecular connectivity index ( 2 χ) and Balaban topological index (J) are the key parameters for antimicrobial activity of synthesized hydrazide derivatives and can be cosidered as important factors for interaction with target site of different microorganisms. It is pertinent to note that multi-target QSAR models were more significant in demonstrating the antimicrobial activity than one-target QSAR models.


INTRODUCTION
In last 60 years the incidence of death rate due to multidrug resistant fungi, bacteria and other pathogenic microbial strains have become one of the serious health issue worldwide (Jee-Young et al., 2012, Jessica et al., 2015).Since multidrug resistant pathogenic strains flourish, the need for effectual treatment has inspired researchers for the development of novel antimicrobial molecules (Patel et al., 2012).Chemical compounds having azomethine -NHN=CH moiety (hydrazidehydrazone) represent an important class for new drug development (Narang et al., 2012a).Literature study of hydrazide-hydrazone derivatives have been claimed to possess antifungal, antibacterial (Bayrak et al., 2009), antitubercular (Nayyar et al., 2007) trypnocidal (Leite et al., 2006), antimalarial (Gemma et al., 2006), antiviral (Narang et al., 2012b), anti-inflammatory (Bhandari et al., 2008) and anti-tumour (Lembege et al., 2008) activities.Moreover, isoniazid (antitubercular, Martins et al., 2014), nifuroxazide (antidiarrheal and antitumor, Yang et al., 2015), nifurtimox (antiamoebic, Jackson et al., 2010), furacin (antibiotic, Johnson et al., 2012) and furazolidone (Safaralizadeh et al., 2006, antibacterial) are hydrazide containing important biologically active drug molecules.Structure activity relationship study of hydrazide compounds revealed that conversion to hydrazone based molecules and substituents attached to aromatic moiety at a particular position affect the antimicrobial activity to a great extent.(Narang et al., 2012c).Undec-10-enoic (undecylenic acid) is eleven carbon straight chain unsaturated fatty produced by cracking of castor oil under pressure.It is a natural fungicide used for the treatment of skin infections such as athlete's foot, ringworm and jock itch.Undecylenic acid has also antiviral properties that are effective on skin infections caused by herpes simplex.(Ereaux et al., 1949) Quantitative structure-activity relationship (QSAR) is a significant part of chemometrics, used to correlate experimentally determined biological activities with structural descriptors of chemical compounds and to develop QSAR models (Hansch et al., 1964).
The developed QSAR models can be further utilized to estimate biological activity of compounds not synthesized in the laboratory (Narang et al., 2013).In view of above findings and continuation of our research programme on antimicrobial evaluation of hydrazide-hydrazone derivatives (Narang et al., 2013;Narang et al., 2012bNarang et al., , 2012c;;Narang et al., 2011;Kumar et al., 2010;Kumar et al., 2009) we decided to synthesize hydrazone derivatives of undec-10-enoic acid, evaluated their antimicrobial activity and QSAR studies.

Experimental
Progress of the reaction was checked by TLC on silica gel sheets (Merck silica gel-G) and purity of intermediates and final products was confirmed by single spot TLC.Melting points were determined in open glass capillaries on Popular India melting point apparatus. 1H nuclear magnetic resonance ( 1 H NMR) spectra were recorded on Bruker Avance II 400 NMR spectrometer (400 MHz) at 298 K, in appropriate deuterated solvents.Chemical shifts were reported as δ (ppm) relative to tetramethylsilane (TMS) as internal standard.Infrared spectra (IR) were recorded as KBr pellet on Shimadzu FTIR spectrometer.The wave number is given in cm - 1 .Mass spectra were recorded on Waters Micromass Q-ToF Micro instrument.

General procedure for synthesis of hydrazide derivatives of undecylinic acid (2-20, Scheme 1) Synthesis of ethyl ester of undecylenic acid (2)
A solution of 0.065 mole of undec-10-enoic (1) and absolute ethanol (50 ml) was refluxed in presence of conc.sulphuric acid (4-5 drops) for 8-10 hr.The excess of acid was neutralized with saturated solution of sodium bicarbonate in water.Synthesized ester (2) was extracted by adding diethylether to the above solution and ether layer was separated.Further, ester of undec-10-enoic was obtained after evaporation of ether layer.

Antimicrobial studies
The antimicrobial activity was carried out against Gramnegative bacteria E. coli, Gram-positive bacteria S. aureus, B. subtilis, and fungal strains: C. albicans and A. niger by tube dilution method (Cappucino and Sherman, 1999).Ciprofloxacin and Fluconazole were used as a standard drug for antibacterial and antifungal evaluation.
The synthesized derivatives and standard drugs were dissolved in dimethylsulphoxide to prepare stock solution of 100 µg/mL.Further, dilutions (50-3.125 µg/mL) were done in double strength nutrient broth -I.P. for bacteria and Sabouraud dextrose broth I.P. for fungi (Pharmacopoeia of India, 2007).The dilutions were incubated at 37 °C for all bacteria (24 hr), and C. albicans (48 hr), 25 °C for A. niger (7 days), and minimum inhibitory concentration (MIC) was determined.

QSAR studies
The QSAR study was performed to correlate antimicrobial activity with physicochemical parameters of synthesized hydrazide derivatives.The structures of synthesized hydrazide derivatives were first pre-optimized with the Molecular Mechanics Force Field method (MM + ) included in Hyperchem 6. 03 (1993) and the resulting geometries were further refined by means of the semiempirical method PM3 (parametric method-3).Gradient norm limit of 0.01 kcal/A˚ was utilized for the geometry optimization.
TSAR 3.3 software for Windows (TSAR 3D Version 3.3, 2000) was used to calculate physicochemical parameters of lowest energy structures of synthesized hydazide derivatives.Further, the regression analysis was carried out using the SPSS software package (SPSS for Windows, 1999).
The predictive powers of the developed models were supported by cross-validated r 2 (q 2 ) using leave one out (LOO) cross-validation method (Schaper, 1999).The statistical qualities of equations were further confirmed by the parameters like standard error of estimate (s), correlation coefficient (r), variance ratio (F) at specified degrees of freedom, root mean square error (RMSE) and predicted error sum of square (PRESS) (Arora et al., 2015, Narang et al., 2012c).
Structures of synthesized compounds (2-20) were ascertained by their 1 H NMR, IR and mass spectral data.The emergence of singlet in the range of δ 9.14 to 10.52 ppm confirmed the presence of NH functionality in synthesized compounds.The singlet signal of CH proton in the range of δ 7.72-δ 8.35 ppm, confirmed the presence of N=CH bond in the synthesized compounds 5, 6, 8, 10, 11 and 12 The singlet signal of CH 3 proton in compounds 18, 19 and 20 at δ 2.29-3.34ppm, confirmed attachment of acetophenone moieties with undec-10-enehydrazide.
The appearance of multiplet in the range of δ 6.77-8.35ppm revealed the presence of aromatic protons.The absence of -NH 2 protons signals in the region from δ 3 to 4 ppm further confirmed the synthesis of hydrazone derivatives.The presence singlet signal at δ 3.94 ppm confirmed the existence of methoxy group in compound 10.The appearance of the stretching peak around 1630-1675 cm -1 indicated the presence of carbonyl group in synthesized hydrazide derivatives.The presence of aromatic ring was indicated by the appearance of the C=C str.band around 1600 cm -1 in synthesized hydrazide derivatives.The appearance of stretching band in the range of 3150-3280 cm -1 showed the presence of NH moiety in synthesized compounds.The appearance of C-Cl and C-F, bands at 750.33, 3410.41 cm -1 in compounds 5 and 8 showed the presence of chloro and hydroxy groups in their structures, respectively.The presence of methoxy group in compound 10 indicated by appearance of asymmetric C-O-C stretching and symmetric C-O-C stretching at 1278.85 cm -1 and 1116.82cm -1, respectively.Further, the symmetric NO 2 stretching around 1340 cm -1 and asymmetric NO 2 stretching 1520 cm -1 , showed the presence of NO 2 functionality in synthesized derivatives (11, 12 and 19).

Antimicrobial evaluation
The synthesized undec-10-ene-hydrazide derivatives were evaluated for their in vitro antimicrobial activity against Gram-positive S. aureus, B subtilis and Gram-negative E coli and antifungal activity against C. albicans and A. niger by tube dilution method (Cappucino and Sherman, 1999).Double strength Nutrient broth I.P. and Sabouraud dextrose broth I.P. have been employed as media for growth of bacterial and fungal cells, respectively.The pMIC values of antimicrobial activity (in µM/ml) are presented in Table 2.In case of B. subtilis, compounds 15, 18 and 19 were found to be more active than the other synthesized derivatives, each having pMIC bs values 1.44 µM/ml (Table 2).Against S. aureus, compounds 10, 11, 12, 13, 15, 18 and 19 were found to be more active than the other synthesized derivatives with pMIC sa values of 2.05 µM/ml (Table 2) which is comparable to standard drug ciprofloxacin (pMIC sa = 2.61 µM/ml).Compounds 15, 18 and 19 derivatives were found to be most potent against the Gram-negative bacteria, E. coli having pMIC ec value 1.44 µM/ml (Table 2).
On the other hand, results of antifungal activity showed that the compounds having NO 2 group (11, 12 and 18) and OCH 3 group (10 and 15) were most potent among the synthesized compounds against C. albicans, having pMIC ca value 2.05 µM/ml.In case of A. niger, compounds 18 and 19 showed highest inhibitory activity as compared to other synthesized derivatives with pMIC an value 1.74 µM/ml (Table 2).Results of antimicrobial data indicated that (Table 2) synthesized hydrazides have higher antifungal activity against C. albicans, in comparison to A. niger.Further, the antimicrobial results showed that compounds 11 and 18 having nitro substituent at ortho and meta position, respectively displayed highest antimicrobial potential among the synthesized derivatives.

Structure activity relationship on the basis of antimicrobial activity results
1.The results of antimicrobial activity showed that substituted hydrazone derivatives (compounds 4-20) have higher antimicrobial potency as compared to undec-  8:2) a , Hexane: Ethylacetate (8.5:1.5)b , Hexane: Ethylacetate (7:3) c , Hexane: Ethylacetate (7.5:2.5)d , Chloroform: Hexane: Ethylacetate (2:3:2) e , Chloroform: Hexane: Ethylacetate (3:1:2) f 10-enoic acid, ester and hydrazide (compounds 1, 2 and 3). 2. The substitution of an electron-withdrawing nitro group at ortho and meta position of attached benzene ring (compounds 11 and 18, respectively) make them highly potent antimicrobial compounds.The role of nitro group in potentiating antimicrobial activity is similar to the observation of Sharma et al. (2004).3. Compound 16, a cinnamaldehyde derivative improved activity (pMIC range 1.10-2.00µM/ml) against tested strains.The presence of conjugated pie electrons in compound 16 can be involved in interaction with target site and this may be the reason of its good activity.This observation is similar to our earlier studies (Narasimhan et al. 2007).4. The substitution of NH 2 group (compound 3) with benzylidene/(1-phenyl-ethylidene) functionalities (compounds 4-20) higher antibacterial and antifungal potency of the synthesized derivatives.This may be due to the enhancement of lipophilic character of synthesized compounds (4-20), which may allow them to easily infiltrate the cell wall. 5.In general, antimicrobial results indicated the importance of both NO 2 and OCH 3 in improving both antibacterial and antifungal activities.Presence of nitro and methoxy groups in compounds 10, 11 and 18 causes maximum enhancement in both antibacterial and antifungal activities.6. Antimicrobial activity results showed that the types and position of functional groups attached to phenyl ring have a significant effect on antimicrobial activity of synthesized hydrazone derivatives.The SAR results are summarized in Fig. 1.

Development of one-target QSAR models (ot-QSAR)
Quantitative structure activity relationship (QSAR) is one of the most influential method for the prediction of biological activity of chemical compounds.QSAR technique also important in finding quantitative relationships between the molecular structure and biological activity of investigated compounds (Mohsen et al., 2010).In the present study, we have performed the QSAR studies by Hansch's analysis using the linear free energy relationship (LFER) model illustrated by Hansch and Fujita (1964).
In Hansch's approach, structural properties of compounds are calculated in terms of different physicochemical parameters and these parameters are correlated with biological activities through equation using regression analysis.Before using the biological activity data for QSAR study experimentally determined MIC values changed to -log MIC or pMIC (in micromole, Table 4) to obtain normal distribution of errors, all the values positive, and to get linear free energy relationship of antimicrobial activity values with different descriptors.Further, regression analysis was performed using calculated physicochemical parameters (Table 3 and 4) as independent variables and antimicrobial activity values as dependent variables (Table 2).
On the basis of intercorrelation between the independent variables and also their individual correlation with antimicrobial activity, different probable combinations of parameters were undertaken for linear regression (LR) and multiple linear regression (MLR) analysis.Statistically most significant QSAR models were chosen from hundreds of developed QSAR models.These models were developed in stepwise manner by forward selection method starting with best single physicochemical parameters and adding further important parameters as per their role in the equation that have the smallest standard deviation (s), until there is no other parameter outside the equation that gratifies the selection criterion.The different physicochemical parameters viz.topological, electronic, thermodynamic, and spatial (Hansch and Fujita, 1964;Hansch et al., 1973;Kier and Hall, 1976;Randic 1975;Balaban 1982;Wiener, 1947;Randic, 1993) were quantified using TSAR 3.3 software (TSAR 3D for Windows, Version 3.3, 2000) for synthesized hydazide derivatives and summarized in Table 3.The values of selected parameters are presented in Table 4.
In view of above facts, a data set of 20 synthesized hydrazide derivatives was used for model development.The predictive powers of derived QSAR models were confirmed by leave one out (LOO) method (Schaper, 1999), where a model is built with N -1 compounds and N th compound is predicted.Each compound was removed for model derivation and predicted in turn.The similar process was repeated by removal of a new compound until all the compounds have been removed once.
A correlation matrix was constructed for antibacterial activity against S. aureus is presented in Table 5.Both high and low colinearity was observed between different physicochemical properties.A highest interrelationship was observed between 2 χ and 1 χ (r = 0.992) and lowest interrelationship was observed between Log P and   (r = 0.053).The correlations of different parameters with antimicrobial activities are presented in Table 6.In general, a significant correlation (r > 0.7) was observed against all tested microbial strains (exception B. subtilis) with most of selected parameters except  3, α 3 and HOMO (Table 6).
Although there is high interrelationship between J and other parameters, still we go for the development of biparametric models to get better r value.The maximum rise in value of . .regression coefficient (r = 0.957, Eq. 2) was achieved on combination of J and zero order molecular connectivity index ( 0 χ).High r (0.957) and q 2 (0.900) values revealed the significance of 0 χ and J (Eq. 2) in describing antibacterial activity against S. aureus of synthesized hydrazide derivatives.
The values of r and q 2 for Eq. 2 are 0.957 and 0.900, which showed that the resulted QSAR equation could explain and predict 95.7% and 90.0% of variances, respectively.Generally, when value of q 2 is greater than 0.5, the model are supposed to have strong predictive power.However, several studies recommended that a high q 2 appear to be a necessary, but not enough condition for an equation to have a good predictive power (Oltulu et al., 2009).
Consequently, various other statistical approaches were used to validate the robustness and the practical applicability of the developed QSAR models.To demonstrate that the resulted equations have good prediction of antimicrobial activity, different parameters for evaluation of developed models have been used.Here, r 2 , elucidate variance for given set, was employed to establish the robustness of model's fit performance.Low values of PRESS and RMSE further confirmed the strength of developed QSAR equations.
Moreover, low residual values indicated that experimental and predicted antimicrobial activities are very close to each other, also confirmed the robustness of developed models (Table 7 and 8).
These are highly sensitive to bonding pattern, symmetry, content of heteroatom as well as degree of complexity of atomic neighborhoods.Since, connectivity order of the constituent atoms in a molecule can be explained by topological descriptors hence the aforementioned fact revealed the role of topological indices, in estimating biological activity, viz.antimicrobial activity.Consequently, topological parameters utilized for estimating biological activities of chemical compounds can be employed for drug development (Lather and Madan, 2005).The cross-validation of the developed models was performed by leave one out (LOO) method (Schaper, 1999).As per studies done by Golbraikh and Troposha for a valid QSAR model, the value of cross validated r 2 (q 2 ) should be more than 0.5 (Golbraikh and Tropsha et al., 2002).Consequentially, all the QSAR models developed in present study are statistically valid and reliable in predicting the antimicrobial activity of synthesized hydrazide derivatives.The plot of observed pMIC ec Vs predicted pMIC ec (Fig. 2) showed the accuracy of developed ot-QSAR model   (Eq.3).To examine the presence of a systemic error in developed QSAR equation (Eq.3), the observed pMIC ec values were plotted against the residuals pMIC ec values (Fig. 3).The presence of the residual points on both sides of zero indicated that no systemic error exists in the development of QSAR model.(Golbraikh and Tropsha et al., 2002).
Usually for QSAR analysis, the biological activity data of synthesized molecules should lies in between 2-3 orders of magnitude.Although, in present study the range of antimicrobial activities of synthesized hydrazide derivatives is within one order of magnitude, though the low residual values (Table 7) evidenced the high predictability of developed QSAR models (Eqs.1-5).This is in agreement with results suggested by earlier studies (Narasimhan et al., 2007;Sharma et al., 2006;Hatya et al., 2006;Kumar et al., 2006), which confirmed that the robustness of the QSAR model lies in its predictive ability, although the biological activity data existed in narrow range of magnitude.Moreover, Kim et al. (2007) recommended that developed QSAR models are acceptable if the value of standard deviation (S.D.) is not much higher than 0.3 (Table 2).Hence, the above facts justify the statistical acceptability of developed QSAR models (Eqs.1-5).

Development of multi-target QSAR model (mt-QSAR)
Aforementioned ot-QSAR models showed that five different equations have to be used to predict the activity of synthesized derivatives against the respective bacterial and fungal strains.But results of our earlier studies recommended that use of ot-QSAR equations is not much practicable, when we have to predict the activity of synthesized compounds against more than one target.
As different ot-QSAR equations have to be used for different targets.Above facts inspired us to develop multi-target QSAR (mt-QSAR) models.In compare to ot-QSAR, the mt-QSAR model is a single equation that considers common and .essential physicochemical parameters for elucidation of antimicrobial activity for different targets (Prado-Prado et al., 2008;Gonzalez-Diaz et al., 2007, 2008a;Gonzalez-Diaz and Prado-Prado 2008;Cruz-Monteagudo et al., 2007).In the present research work three mt-QSAR models were developed, Eq. 6 for relating antibacterial activity of synthesized derivatives with B. subtilis, S. aureus, and E. coli, Eq. 7 for relating antifungal activity with C. albicans and A. niger as well a common mt-QSAR model (Eq.8) for relating antimicrobial (overall antibacterial and antifungal) activity of synthesized udecanoic hydrazide derivatives with all the above mentioned microbial strains.In order to develop mt-QSAR equations, firstly we have calculated the average antibacterial, antifungal and antimicrobial activities values of synthesized compounds, presented in Table 2. Further, these average antimicrobial activity values were interrelated with the physicochemical parameters (Table 4) of synthesized compounds.

mt-QSAR model for antibacterial activity
pMIC ab = 0.129 2 χ + 0.437 Eq. 6 n = 20 r = 0.943 r 2 = 0.889 q 2 = 0.871 s = 0.074 F = 145.70RMSE = 0.070 PRESS = 0.098 Eq. 6 showed the importance of 2 χ in illustrating the overall antibacterial activity against all three tested bacterial strains.Developed mt-QSAR model (Eq.6) once again evident that as the values of 2 χ (Table 4) increases the value of pMIC ab enhances (Table 2).Moreover, statistical parameters indicated that mt-QSAR model (Eq.6) have better predictive ability than ot-QSAR models, as in case of ot-QSAR model there is no statistical significant model was developed against B. subtilis.As in case of C. albicans, QSAR analysis of synthesized derivatives once again revealed that J values are negatively correlated with overall antifungal activity.This information can be further supported by high pMIC af values of compound 18 (MIC=1.90,Table 2) has small J values (3.68,Table 4).

mt-QSAR model for antimicrobial activity
pMIC am = 0.147 2 χ + 0.345 Eq. 8 n = 20 r = 0.938 r 2 = 0.880 q 2 = 0.866 s = 0.088 F = 132.53RMSE = 0.084 PRESS = 0.142 The developed mt-QSAR model (Eq.8) indicated that the 2 χ is positively correlated with overall antimicrobial activity against all tested bacterial and fungal strains.This is clearly obvious from Table 4, that compounds (10, 11, and 18) having high 2 χ values, 9.12, 9.25 and 9.78 have highest pMIC am activity values, i.e. 1.73, 1.73 and 1.74, respectively (Table 2).Moreover, compounds 1, 2 and 3 with lowest 2 χ values 4.66, 4.78 and 4.78 (Table 4) have lowest pMIC am activity values i.e. 0.93, 1.08 and 1.02, respectively (Table 2).Further, there is no statistically significant improvement in values of r and q 2 was observed, when we go for development of multiparametric models except S. aureus (Eq.2).The plot of observed pMIC am Vs predicted pMIC am (Fig. 4) showed the accuracy of developed ot-QSAR model (Eq.8).To examine the presence of a systemic error in developed QSAR equation (Eq.8), the observed pMIC am values were plotted against the residuals pMIC am values (Fig. 5).The presence of the residual points on both sides of zero indicated that no systemic error exists in the development of QSAR model (Golbraikh and Tropsha et al., 2002).

CONCLUSION
In present study, a series of hydrazide derivatives of undecylenic acid (4-20) have been synthesized successfully in appreciable yields and evaluated for their in vitro antibacterial and antifungal activities against selected strains.The results of antimicrobial activity indicated that the NO 2 and OCH 3 groups improved the antimicrobial activity.The NO 2 group containing acetophenone derivatives have more antimicrobial activity as compare to NO 2 group containing aldehyde derivatives.Compounds having NO 2 (11, 12, 18 and 19) and OCH 3 (10 and 15) groups showed comparable antibacterial activity (pMIC= 2.05 µM/ml) against S. aureus and antifungal activity (pMIC=2.05µM/ml) against C. albicans to that of standard drug Ciprofloxacin (pMIC=2.61µM/ml) and Fluconazole (pMIC=2.64 µM/ml) respectively.QSAR studies showed that second order molecular connectivity index ( 2 χ) and Balaban topological index (J) are the key parameters for antimicrobial activity of synthesized hydrazide derivatives.It is important to note that multi-target QSAR models were more significant in demonstrating the antimicrobial activity than one-target QSAR models.

Fig. 2 :
Fig. 2: Plot of predicted pMICec values against observed pMICec values for the linear regression developed model by Eq. 3.

Fig. 3 :
Fig. 3: Plot of residual pMICec values against observed pMICec values for the linear regression developed model Eq. 3.

Fig. 4 :
Fig. 4: Plot of predicted pMICam values against observed pMICam values for the linear regression developed model by Eq. 8.

Fig. 5 :
Fig. 5: Plot of residual pMICam values against observed pMICam values for the linear regression developed model Eq. 8.

Table 3
Brief description of some molecular descriptors used in the present study.

Table 4 :
Value of selected descriptors used in the regression analysis.

Table 5 :
Correlation matrix for antimicrobial activity of synthesized hydrazide derivatives against S. aureus.

Table 6 :
Correlation of molecular descriptors with antimicrobial activity of synthesized hydrazide derivatives.

Table 7 :
Comparison of observed and predicted antibacterial and antifungal activity obtained by ot-QSAR models.

Table 8 :
Comparison of observed and predicted antimicrobial activity obtained by mt-QSAR models.