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Blessy Jacob*, Lata K. Bisht, Naveen S, Deena David, Anjana Antony
T John College of Pharmacy, No. 88/1, Gottigere Bannerghatta Road, Bangalore, Karnataka , India.


Quantitative structure activity relationship studies have been conducted on a series (19 compounds) of long chain quaternary ammonium derivatives using Chem Office v 8.0 software. The best predictions have been obtained for antibacterial activity (r= 0.9, r2=0.91, Boots strapping r2=0.8). Both equations are validated by a test set of compounds and give satisfactory predictive r2 values of 0.9 respectively. The equations selected emphasized the importance of Dipole, Non Vander Wall energy on biological activity i.e. Dipole moment, and Non VDW energy of molecule might be influencing the selective antibacterial activity.

Keywords: Long Chain Quaternary Ammonium Compounds, quantitative Structure Activity Relationship, soft antibacterial agent.


Soft drugs are defined as drugs, which are characterized by predictable and controllable in vivo destruction (i.e. metabolism) to form non-toxic products after they have achieved their therapeutic role. Quaternary ammonium compounds, such as benzalkonium chloride, are hard antibacterial agents. Their toxicity limits their usage in humans and animals, and their chemical stability limits their usage for general environmental sanitation. Furthermore, due to their stability they are prone to induce selective antimicrobial pressure and bacterial resistance. These soft analogues consist of long alkyl chain connected to a polar head group via chemically labile spacer group. They are characterized by facile non enzymatic and enzymatic degradation to form their original nontoxic building blocks. However, their chemical stability has to be adequate in order for them to have antimicrobial effects. Stability studies and antibacterial and antiviral activity measurements revealed relationship between activity, lipophilicity, and stability. Their minimum inhibitory concentration (MIC) was as low as 1 microg/mL, and their viral reduction was in some cases greater than 6.7 log.2 The long chain quaternary ammonium derivatives were considered as an interesting moiety and found to exhibit as effective action on Enterococcus  faecalis 3.


To obtain structural requirement, responsible, for exhibiting antibacterial action by using three dimensional quantitative structure activity relationship. 3D QSAR helped in designing potent antibacterial agents.


All computational studies were performed using ChemOffice v 8.0 software and Valstat:4,5 A PC based program developed using C++ language was used. It provides sequential and stepwise multiple regression analysis with linear and parabolic relationship to generate the QSAR model 6. Series of long chain quaternary ammonium derivatives were reported by Thorsteinn Thorsteinsson et al. A series of long chain quaternary ammonium derivatives containing 19 compounds as antibacterialagent was used in this analysis. The predictive power of the equation was validated by leave one out cross validation method. The cross validated square correlation coefficient (q2) and predictive residual sum of square (spress) and standard deviation of error of prediction (SDEP) suggested a good internal consistency as well as predictive ability of the equation. The bootstrapping r2 is at par with conventional squared correlation coefficient (r2) 7.

When a molecule acts as a lewis base (an electron pair donor) in bond formation, the electrons are supplied from the molecule’s HOMO. Molecules with high HOMO are more able to donate their electrons in charge transfer phenomenon and hence are relatively reactive compared to molecules with low HOMO; thus the HOMO descriptors measures the nucleophilicity of a molecule 8-9.


Table 1: Observed, Calculated and Predicted log10 values of compounds.

COMPOUNDNO: STRUCTURE Enterococcus faecalis

Log MIC(mg/ml)



1a 3.301247 3.30929 51.7997
1b   1.20412 0.718584 0.68485
2a   3.000434 2.99587 -11.9483
2b   1.50515 0.712574 0.65706
2c   0.90309 0.677495 0.661232
3a   -0.30103 0.70258 0.77335
3c   1 0.671998 0.648191
3e   0.30103 0.676726 0.703837
3g   0.90309 0.67788 0.66165
3h   0.90309 0.677197 0.660904
3i   0.60206 0.526046 0.519845
3k   0.875061 0.681237 0.667307
3o   0.60206 0.678492 0.683997
3p   0 0.809102 0.863899
3q   4.10721 4.07071 -5.80539
3v   0.60206 0.67752 0.68296
3y   2.39794 2.40031 95.7578
4b   0.60206 0.753053 0.763449
4c   0.60206 0.694075 0.70062


Equation 1(optimized model)

BA= [0.677403( ± 0.259926)] +NVDWE [5.75418e-006( ± 1.75409e-006)] +HOMO [1.47878e-006( ± 5.83771e-007)] +LUMO [-5.38006e-005( ± 3.23956e-005)] +CC [1.07687e-006]  


n = 19,r= 0.851,r2= 0.724,variance= 0.052,STD= 0.227,F=13.145,FIT= 140.833


Q2= 0.552,Bootstrapping  r2= 0.768,Bootstrapping STD= 0.101,Chance< 0.001,Spress= 0.290,

SDEP= 0.258


Table 2: Correlation matrix between descriptors of equation 1

NVDWE 1.000000
HOMO 0.057384 1.000000
LUMO 0.056382 0.052806 1.000000
CC 0.057576 0.058819 0.057890 1.000000

Figure 1: Observed Vs Calculated


Figure 2: Observed Vs predicted


QSAR analysis using 19 compounds was successfully carried out to be statistically significant models possessing good correlative and predictive ability. The study revealed that anti-fungal activity exhibited by series is explained by steric and electronic factor and modulation of any of these properties could be used to optimize activity.


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