Synthesis , molecular docking and QSAR studies of 2 , 4-disubstituted thiazoles as antimicrobial agents

Article history: Received on: 13/11/2014 Revised on: 04/12/2014 Accepted on: 22/01/2015 Available online: 27/02/2015 In present study a series of 2,4-disubstituted thiazole derivatives was synthesized and evaluated for their in vitro antibacterial and antifungal activities against B. subtilis, E. coli, S. aureus, C. albicans and A. niger by tube dilution method. The analysis of antimicrobial activity results indicated that the presence of NO2 and OCH3 groups at para position of phenyl group improved the antimicrobial activity significantly. Molecular docking studies also supported in vitro activity results and showed that NO2 and OCH3 groups containing compounds have greater affinity towards the target glucosamine-6-phosphate synthase. QSAR studies indicated that molecular connectivity index (χ) and Kier’s shape index (α3) are the key parameters for antimicrobial activity of synthesized thiazole 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 effectual in demonstrating the antimicrobial activity than one-target QSAR models.


INTRODUCTION
The treatment of infectious diseases caused by bacteria, parasites, viruses and fungi always remains a global health problem because of increasing number of multi-drug resistant pathogenic microbial strains (Narang et al., 2012).Despite the availability of large number of antibiotics for clinical use, the emergence of antibiotic resistance in recent years against Grampositive and Gram-negative bacterial and fungal strains constitutes an urgent need for the discovery of new class of antimicrobial agents (Perez et al., 2014;Narasimhan et al., 2009).Various sulfur and/or nitrogen containing heterocyclics belonging to the class of alkaloids, vitamins, pigments etc. possessing biological activities are reported in the literature (Ozdemir et al., 2007).1,3-thiazoles and their derivatives are important class of five membered heterocyclic compounds having sulphur and nitrogen at position-1 and -3, respectively.
Molecular docking is a computer-assisted drug design (CADD) method used to predict the favourable orientation of a ligand (viz.drug) to a target (viz.receptor) when bound to each other to form a stable complex.By understanding of the favoured orientation in turn can be used to find out the strength of binding affinity between ligand and target site, e.g. by docking score (Sarojini et al., 2010).Moreover, docking study can be used to find out type of interactions between ligand and receptor viz.hydrogen bonding and hydrophobic interactions.
Hence, molecular docking can be considered as first-line technique for a pharmaceutical lead discovery (Shoichet et al., 2002).Moreover, in silico studies on 2,5-dichloro thienyl substituted thiazole derivatives carried out by the research group of Sarojini and co-workers (2010) have found that thiazole based analogues have potential to bind with the enzyme, L-glutamine: D-fructose -6 -phosphate amidotransferase.
This reaction is involved in the formation of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), a product that is present in all class of organisms, but in case of fungi and bacteria it is solely used to build macromolecules related with cell wall assembly, e.g.chitins and mannoproteins in case of fungi and peptidoglycan in bacteria.Hence, the target glucosamine-6phosphate synthase was selected for performing the in silico studies in present study.Quantitative structure-activity relationship (QSAR) is a significant part of chemometrics used to correlate experimentally determined biological activities with structural descriptors of chemical compounds (Hansch et al., 1964).
The derived QSAR model can be further utilized to predict biological activity of compound not synthesized in the laboratory (Narang et al., 2013).In light of above facts and in continuation of our research program focused on design and synthesis of novel antimicrobial agents an attempt has been made to synthesize 2,4-disubstituted thiazole derivatives and screened them for in vitro antibacterial and antifungal activities (Narang et al., 2013;Narang et al., 2012;Narang et al., 2011;Kumar et al., 2010;Kumar et al., 2009).Further, to evaluate the active site interaction made by the synthesized compounds, molecular docking studies were carried out which is followed by 2D -QSAR studies to estimate the key descriptors that govern the antimicrobial activity of the compounds under investigation.

Experimental
Melting points of synthesized compounds were determined in open glass capillaries on a sonar melting point apparatus and are uncorrected.Reaction progress was monitored by thin layer chromatography on silica gel sheets (Merck silica gel-G). 1 H Nuclear magnetic resonance ( 1 H NMR) spectra were recorded on Bruker Avance II 400 NMR spectrometer (400 MHz) at 298 K, in appropriate deuterated dimethyl sulfoxide.Chemical shifts were reported as δ (ppm) relative to tetramethylsilane (TMS) as internal standard.Infrared (IR) spectra were recorded as KBr pellet on Perkin Elmer FTIR spectrometer.The wave number is given in cm -1 .

General procedure for synthesis of 2-amino-4-phenylthiazole derivatives (3-12, Scheme 1 and 2) Synthesis of 2-amino-4-phenylthiazole (2, 10)
To a mixture of acetophenone/p-nitroacetophenone (0.1 mol) and thiourea (0.2 mol) in absolute ethanol, bromine (0.2 mol) was added dropwise.After complete addition of bromine, reaction mixture was refluxed on a water-bath for 24 hrs.Then water was added to reaction mixture and heated until most of the solid was dissolved.The reaction mixture was filtered while hot.The filtrate was cooled and made alkaline using 20% ammonium hydroxide to obtain corresponding crude precipitate of 2-amino-4phenylthiazole derivatives (2 and 10).Recrystallization from ethanol yielded the corresponding required product.

Antimicrobial evaluation
The antimicrobial estimation of synthesized compounds was carried out against Gram-positive bacteria: Staphylococcus aureus MTCC 7443, Bacillus subtilis MTCC 441, Gram-negative bacterium: Escherichia coli MTCC 42 and fungal strains: Candida albicans MTCC 183 and Aspergillus niger MTCC 282 by tube dilution method (Cappucino and Sherman, 1999).The standard and test samples were dissolved in DMSO to give a concentration of 100 µg/ml.Dilutions of test and standard compounds were prepared in double strength nutrient broth -I.P. (bacteria) or Sabouraud dextrose broth I.P. (fungi) (Indian Pharmacopoeia, 2007).The samples were incubated at 37 °C for 24 h (bacteria), at 25 °C for 7 days (A.niger) and at 37 °C for 48 hrs (C.albicans) respectively, and the results were recorded in terms of MIC (the lowest concentration of compound inhibited the growth of microorganisms).

Molecular docking studies
Molecular docking studies of synthesized compounds were carried out on the target protein glucosamine-6-phosphate synthase (PDB Id: 1jxa) which catalysis the complex reaction involving ammonia transfer from L-glutamine to Fru-6-P, (Dutka-Malen et al., 1988;Bates et al., 1966) followed by isomerisation of the formed fructosamine-6-phosphate to glucosamine-6phosphate.The ligands were drawn in ChemBioDraw Ultra 12.0 followed by MM2 minimization of ligands (using ChemBio3D Ultra 12.0) by keeping a check on the connection error in the bonds.Protein and Grid preparation was done using Autodock Vina 1. 1.2 (Trott et al., 2010) and was used to perform molecular docking.

QSAR studies
The QSAR study was performed to correlate antimicrobial activity with physicochemical parameters of synthesized thiazole derivatives.The structures of synthesized thiazole 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 thiazole 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).

Chemistry
The synthesis of the intermediate (2 and 10) and target compounds (3-8 and 11-12) were performed according to the reactions outlined in Scheme 1 and 2. Acid chloride was synthesized by refluxing acid with distilled thionyl chloride.Then, corresponding acid chlorides and synthesized thiazole derivatives were stirred at 0-10 ºC in dry pyridine to yield the target N-(4phenyl-thiazol-2-yl)-benzamide/amide derivatives (3-7 and 11-12).On the other hand, compound N-(3,4-dimethoxybenzylidene)-4phenylthiazol-2-amine (8) was synthesized by condensation of intermediate ( 2) with veratraldehyde in presence of acetic acid.In this study we obtained some thiazole derivatives in good yield and some in moderate to low yield.The physicochemical properties of synthesized compounds are presented in Table 1.
Chemical structures of synthesized compounds (2-8 and 10-12) were ascertained on the basis of their 1 H NMR and IR spectral data.The appearance of singlet signal ranging from δ 6.75 to 7.38 ppm in the synthesized compounds confirmed the presence of CH of thiazole ring (compounds 2-8).The presence of singlet signal of NH proton in compounds (3-6 and 10-12) in the range of δ 12.35-12.68ppm revealed the formation of amide bond in the synthesized derivatives.The presence of aromatic protons in synthesized derivatives was confirmed by the multiplet signal in the range of δ 7.01 to δ 8.65 ppm.The presence of methoxy group in compounds 5, 8 and 12 was confirmed by singlet peak present in the region of δ 3.69-3.90ppm.Moreover, the absence of singlet peak of NH 2 protons at δ 6.78 ppm in target compounds (3-8 and 11-12) and presence of same peak in intermediate ( 2) confirmed their synthesis.
The presence of the C=O functional group (compounds 3-7, 11-12) was indicated by the appearance of a stretching band around 1675 cm -1 , which is the characteristic of an amide linkage.The presence of the C=C str.(aromatic) was indicated by the appearance of a stretching band around 1450-1600 cm -1 in compounds 2-12.The appearance of IR band around 3100-3400 cm -1 showed the presence of NH linkage of amide bond in synthesized derivatives.The appearance of C-S band around 650 cm -1 in compounds 2-12 indicated the presence of thiazole nucleus.In compounds 5, 8 and 12 stretching band around 2940 cm -1 revealed the presence of methoxy group.Further, the aromatic nitro stretching around 1550 cm -1 (asymmetric NO 2 stretching) and 1350 cm -1 (symmetric NO 2 str.) depicted the presence of nitro functional group in synthesized compounds 4, 11 and 12.The presence of C-N bond in synthesized compounds was indicated by stretching band around 1334 cm -1 .In compounds 5, 8 and 12 stretching at around 1130 cm -1 (symmetric C-O-C stretching) and 1250 cm -1 (asymmetric C-O-C stretching) revealed the presence of methoxy group.

Antimicrobial activity
The synthesized thiazole derivatives (2-12) were evaluated for their in vitro antibacterial activity against Grampositive 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 (Indian Pharmacopoeia, 2007).
The pMIC values of antimicrobial activity (µM ml -1 ) are presented in Table 2.In case of B. subtilis, compounds 4, 8, 11 and 12 were found to be more active than the other synthesized derivatives with pMIC bs value range 3.92-4.01µM ml -1 .Against S. aureus, compounds 4, 8 and 12 were found to be most active than the other synthesized derivatives (pMIC sa range = 4.51-4.60µM ml -1 ).Again compounds 4, 8 and 12 were found to be most potent against the Gram-negative bacteria, E. coli having pMIC ec value 4.51-4.60µM ml -1 among synthesized derivatives.
On the other hand, results of antifungal activity revealed that the compounds 4, 8, 11 and 12 were able to produce good inhibitory activity against C. albicans (pMIC ca = 3.92-4.01µM ml - 1 ).For antifungal activity against A. niger compounds 11 and 12 showed more potent activity having pMIC an value 4.01-4.23 µM ml -1 than other synthesized derivatives.Results of antimicrobial (antibacterial and antifungal) activities showed that compounds having phenyl substituted p-methoxy and p-nitro moities were the most potent ones (pMIC range = 3.79-4.60µM ml -1 ) as compared to other synthesized derivatives.Moreover, compounds with pnitro phenyl moiety (11 and 12) attached at 4 th position of thiazole ring were the most potent ones against tested antifungal strains (pMIC = 3.93-4.23µM ml -1 ).Further, it is observed that compound 12 having p-methoxy and p-nitro substituted phenyl ring showed most potent antimicrobial activity (pMIC = 4.60) among synthesized derivatives against S. aureus and E. coli.

Structure activity relationship on the basis of antimicrobial activity results
1.The replacement of hydrogen of NH 2 group (2 and 10) with benzamide (3-5 and 11-12), amide (6-7) and 3,4dimethoxybenzylidene (8) led to a noticeable increase in antimicrobial activity of the synthesized compounds against S. aureus and E. coli.This may be due to the increase in lipophilicity of synthesized derivatives, which may allow them to easily penetrate the microbial membrane (Fig. 1).2. The higher antimicrobial activity of compounds 4, 11 and 12 may be due to the presence of electron withdrawing NO 2 group at para position of phenyl ring.Role of electron withdrawing group in improving antimicrobial activity is in accordance with the finding of Sharma et al. (2004).3. Synthesized derivatives demonstrated low antibacterial and antifungal activity compared to reference drugs Ciprofloxacin and Fluconazole respectively, against all tested microbial species.4. The presence of electron donating OCH 3 group (5, 8 and 12) conferred higher antibacterial activity to the synthesized thiazole derivatives, specifically against S. aureus and E.coli (pMIC range = 4.49-4.60). 5. Compound (6) synthesized from cinnamic acid, has displayed better activity as compared to unsubstituted derivative (2).This may be due to the presence of extended conjugation in cinnamic acid, which may be involved in binding of synthesized compound with target site.This fact is supported by study of Narasimhan et al. (2007).6.The aforementioned results indicated the fact that different structural requirements are essential for a compound to be selected as antibacterial or antifungal agent.This is similar to the results obtained by Sortino et al. (2007).

Molecular docking studies
Molecular docking studies were carried out to understand the binding profile of synthesized thiazole derivatives and to support the in vitro antimicrobial activity data.Automated docking was used to determine the orientation of inhibitors bound in the active site of bacterial glucosamine-6-phosphate synthase (PDB ID 1jxa) (Sarojini et al., 2010).A Lamarckian genetic algorithm method, implemented in the program AutoDock Vina 1.1.2,was employed.The 3D-structure of bacterial glucosamine-6-phosphate synthase is presented in Fig. 2.
The docking of series of ligands (2-12) with glucosamine-6-phosphate synthase (GlcN-6-P synthase) indicated that all the synthesized compounds have potential of binding with one or the other amino acids in the active pockets as evident from the docking scores provided in Table 3.The 2D structure of ligand was drawn on ChemBioDrawUltra 12.0.and 3D coordinates were developed using ChemBio3D ultra 12.0 after performing MM2 minimization.
The protein structure file (PDB ID: 1jxa) taken from RCSB Protein Data Bank (PDB) was prepared for docking by removal of water molecules, adding polar hydrogens and Kollman charges to the structure file.In silico prediction of amino acids involved in the active site of protein responsible for binding with the ligands are obtained from the co-crystallized endogenous ligand from the PDB file.Ligand preparation is done by adding Gasteiger charges.Different conformations of ligands were built by allowing rotation of all torsions during docking.
Theoretically all the synthesized compounds showed very good binding scores ranging from -5.4 to -9.1 kcal/mol.Out of the ten compounds nine have shown docking scores much better than the docking score of co-crystallized ligand (-5.9 kcal/mol).Molecular docking studies revealed that compounds 11 and 12 is showing excellent binding score of more than -9.0 kcal/mol as the nitro group at para position in these compounds is making hydrogen bonding interaction with Arg383 and Arg173 (in 11) and with Glu396 and Gln346 (in 12) (Figure 3).
These compounds are also showing strong hydrophobic interaction with Pro177.In case of compound 12, an extra πstacking interaction which is generally known as sandwich type πstacking interaction is being shown by Phe205 and Pro177 through the phenyl moiety carrying methoxy group.It can be justified as result of electron releasing effect of methoxy group which might increased the electron density of the π -cloud of the aromatic ring of the ligand and helps in providing sufficient stabilization.
Thus, hydrophobic interactions also tend to stabilize the binding site and thus should be considered as important parameter for drug design.The stabilization of receptor-ligand binding state through hydrophobic interactions is also reported by Singh et al. (2014) for biguanide based compounds for quorum sensing activity.The present data supports the in vitro results which suggest that compounds 11 and 12 are showing high antimicrobial activity against all the tested microorganisms.Hence, it can be predicted that activity may be due to inhibition of enzyme GlcN-6-P synthase, which catalyses a reaction which involves transfer of amine group from L-glutamine to Fru-6-P, followed by isomerisation of the fructosamine-6-phosphate to glucosamine-6phosphate.

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 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 described 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 activity 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) to get all the values positive, normal distribution of errors and to get linear free energy relationship of these data with physicochemical parameters.Further, regression analysis was performed using calculated physicochemical parameters (Table 4 and 5) 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 subjected to linear regression (LR) and multiple linear regression (MLR) analysis.Out of hundreds of equations generated, some of the best QSAR equations having significant statistical values are selected.
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 that leads to the smallest standard deviation (s), until there is no other variable outside the equation that satisfies the selection criteria.
In view of above facts, a data set of 10 synthesized thiazole 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 is eliminated for model derivation and predicted in turn.The same procedure is repeated after elimination of another compound until all the compounds have been eliminated once.
A correlation matrix constructed for antibacterial activity against S. aureus is presented in Table 6.Both high and low colinearity was observed between different physicochemical properties.A highest interrelationship was observed between 1 χ v and MR (r = 0.997) and lowest interrelationship was observed between 3 χ and log P (r = 0.376).The correlations of different parameters with antimicrobial activities are presented in Table 7.
A significant correlation (r > 0.7) was observed against all tested microbial strains with most of selected parameters except 3 χ (Table 7).
Although there is high interrelationship (r = 0.950, Eq. 1) between 2 χ v and other parameters, still we go for the development of biparametric models to get better regression coefficient.The maximum increase in r value was observed on combination of 2 χ v and Kier's shape topological index ( 3 ) (r = 0.979, Eq. 2).High r (0.979) and q 2 (0.946) values revealed the significance of 2 χ v and  3 (Eq.2) in describing antibacterial activity against S. aureus of synthesized thiazole derivatives.
The values of r and q 2 for Eq. 2 are 0.979 and 0.946, which means that the resulted QSAR model could explain and predict 97.9% and 94.6% of variances, respectively.Generally, when q 2 are larger than 0.5, the model are considered to have sound predictive power.However, several studies recommended that a high q 2 appear to be a necessary, but not sufficient, condition for a model to have a highly accurate 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 of selected thiazole derivatives, some different methods of evaluation of model performance have been used.Here, r 2 , which presents the explained variance for given set, was used to determine the goodness of model's fit performance.Low values of RMSE and PRESS further confirmed the validity of developed QSAR models.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 8).ot-QSAR model for antibacterial activity against E. coli pMIC ec = 0.462 (±0.054) 2 χ v +1.834 (± 0.278) eq.3 n = 10 r = 0.950 r 2 = 0.903 q 2 = 0.891 s = 0.135 F = 74.361pMIC ec =1.039(± 0.195) 2 χ v -0.468(±0.156) 3 +0.852(±0.381)eq.4 n = 10 r = 0.979 r 2 = 0.958 q 2 = 0.946 s = 0.096 F = 79.084PRESS = 0.064 RMSE = 0.253 QSAR analysis of E. coli once again revealed the significance of 2 χ v and  3 in demonstrating antimicrobial activity.Further, developed QSAR model indicated that antimicrobial activity is positively correlated with 2 χ v and negatively correlated with  3 (Eq. 3 and Eq. 4).
ot-QSAR model for antibacterial activity against B. subtilis pMIC bs = 2.50 (± 0.772) 3 χ v + 2.575 (± 0.368) eq.5 n = 10 r = 0.753 r 2 = 0.567 q 2 = 0.513s = 0.188 F = 10.492pMIC bs =1.681 (± 0.823) 3 χ v + 0.163 (± 0.091) log P + 2.365 (± 0.347) Eq. 6 n = 10 r = 0.839 r 2 = 0.704 q 2 = 0.618 s = 0.166 F = 8.30 PRESS = 0.196 RMSE = 0.442 In case of B. subtilis the developed QSAR model (Eq.5) showed that there is a positive correlation between antibacterial activity of synthesized thiazole derivatives and their 3 χ v values.This is supported by antibacterial activity values of synthesized thiazole derivatives (Table 2) and their 3 χ v values (Table 5).Further, during multiple linear regression (MLR) study there was a significant increment in r value on addition of log P to 3 χ v .[r = 0.753 (Eq.5) to r = 0.839 (Eq.6)].Topological indices parameters (e.g. 1 χ and 3 χ v ) are numerical descriptors of a topology of a molecule.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 described by topological descriptors hence the information based upon connectivity can reveal the role of structural or sub-structural information of a molecule in estimating biological activity, viz.antimicrobial activity.Therefore, topological descriptors developed for predicting physicochemical properties and biological activities of chemical substance can be used for drug design (Lather and Madan, 2005).ot-QSAR model for antifungal activity against C. albicans pMIC ca = 0.258 (± 0.050) 2 χ v +2.432 (± 0.262) eq.7 n = 10 r = 0.876 q 2 = 0.738 s = 0.127 F = 26.343pMIC ca = 0.896(± 0.128) 2 χ v -0.519(± 0.102)  3 +1.345(±0.250)eq.8n = 10 r = 0.975 q 2 = 0.936 s = 0.063 F = 66.691PRESS = 0.028 RMSE = 0.166 In case of C. albicans 2 χ v found to be the major factor influencing the antifungal activity (Eq.7).Further, on combination of  3 with 2 χ v , statistical more significant biparametric model was developed, as the value of r increased from 0.876 (Eq.7) to 0.975 (Eq.8).Hence Eq. 8 has more predictability than Eq. 7, which can also be observed from low residual values (Table 8).Consequently, the topological parameter 2 χ v as well Kier's shape topological parameter,  3 playing a significant role in determining the activity of thiazole derivatives against C. albicans.ot-QSAR model for antifungal activity against A. niger pMIC an = 0.123 (± 0.018) 2 χ +2.770 (± 0.162) eq.9 n = 12 r = 0.922 r 2 = 0.850 q 2 = 0.831 s = 0.093 F = 45.290PRESS = 0.068 RMSE = 0.261 The developed QSAR equation (Eq.9) for A. niger depicted that second order connectivity index ( 2 χ) is positively correlated with antifungal activity of synthesized substituted thiazole derivatives.These results can be evidenced by high 2 χ values (9.97 and 10.76, Table 5) of compounds 11 and 12 having highest antifungal activity (pMIC an = 4.23 and 4.01, Table 2) against A. niger, respectively.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 thiazole derivatives.The plot of observed pMIC sa Vs predicted pMIC sa (Fig. 4) showed the accuracy of developed ot-QSAR model (Eq.2).To examine the presence of a systemic error in developed QSAR equation (Eq.2), the observed pMIC sa values were plotted against the residuals pMIC sa 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).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 thiazole derivatives is within one order of magnitude, though the low residual values (Table 8) evidenced the high predictability of developed QSAR models (Eqs.1-9).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 is not much higher than 0.3.Hence, the above facts justify the statistical acceptability of developed QSAR models (Eqs.1-9).

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  niger by tube dilution method.Chemical structures of synthesized compounds were ascertained on the basis of their spectral data (IR and 1 H NMR). The analysis of antimicrobial activity results indicated that the presence of NO 2 and OCH 3 groups at para position of phenyl ring improved the antimicrobial activity of the synthesized thiazole derivatives.The replacement of NH 2 group (2) with substituted phenyl ring (3-8 and 11-12) led to a noticeable increase in antimicrobial activity of the synthesized compounds against S. aureus and E. coli.Molecular docking studies revealed that compounds 11 and 12 is showing excellent binding score of -9.2 kcal/mol and -9.1 kcal/mol, respectively as the nitro head group at para position is making strong hydrogen bonding interaction with Arg383, Arg173, Glu396 and Gln346 amino acid residues.These compounds also have potential to show sandwich type π-stacking interactions.Further, QSAR studies indicated that the molecular connectivity index ( 2 χ v ) and Kier's shape index (α 3 ) are key parameters for the antimicrobial activity of synthesized thiazole derivatives.The developed QSAR equations satisfy the statistical validation criteria to a considerable extent and can be a valuable theoretical base for proposing more potent 2,4disubstituted thiazole derivatives.

Fig. 4 :
Fig. 4: Plot of observed pMICsa values against predicted pMICsa values for the multiple linear regression developed model by Eq. 2

Table 3 :
Docking score of synthesized thiazole derivatives against A chain amino acid present in active site of glucosamine-6-phosphate synthase.

Table 4 :
Brief description of some molecular descriptors used in the present study

Table 5 :
Value of selected descriptors used in the regression analysis

Table 6 :
Correlation matrix for antimicrobial activity of synthesized thiazole derivatives against S. aureus.

Table 7 :
Correlation of molecular descriptors with antimicrobial activity of synthesized thiazole derivatives

Table 8 :
Comparison of observed and predicted antibacterial and antifungal activity obtained by ot-QSAR models

Table 9 :
Comparison of observed and predicted antimicrobial activity obtained by mt-QSAR models.