Antimicrobial activity assessment of certain anilide derivatives

Several physiochemical, structural and quantum-mechanics based descriptors were derived for a set of anilide derivatives, using DFT-B3LYP/6-311G (d, p) level of theory. The aim of this study was to develop QSAR model using multiple linear regression to predict the antimicrobial activity of anilides towards E. Coli in terms of several electronic and molecular descriptors. The best-fit model involved electrophilicity index (w) in conjunction with molecular weight (W) and logarithm of the octanol-water partition co-efficient (Log P) as antimicrobial activity descriptors. A comparison of the QSARs [ pIMC = -2.163 ELUMO+ 0.050 log P + 0.81, R2 adj = 0.738, RSS = 0.109, F = 110.743], [ pIMC= 0.058 w + 0.047 Log P+ 0.772, R2 adj = 0.771, RSS =0.095, F= 132.361], [ pIMC = -0.088ELUMO+ 0.012 á + 0.248, R2 adj = 0.688, RSS = 0.129, F = 87.307] and [ pIMC = 0.053w +0.011á + 0.253, R2 adj = 0.722, RSS = 0.115, F = 102.235] suggesting that w is marginally a better descriptor than ELUMO and Log P is slightly a superior descriptor than á for parameterization of electrophilic reactivity and hydrophobicity of molecules respectively