Application of Physicochemical and Topological Descriptors in Predicting Toxicity of Aliphatic Carboxylic Acids

In the present investigation the applicability of various topological indices and physicochemical descriptor are tested for the QSAR study on aliphatic carboxylic acids. Quantitative Structure-Activity Relationship (QSAR) models are useful in understanding how chemical structure relates to the biological activity and the toxicity of natural and synthetic chemicals. The topological indices used for the QSAR analysis were Randic (1X) (the first order molecular connectivity), Balaban (J), Wiener(W), hyperWiener (WW), Wiener polarity (Wp) and Harary (H) indices and the physicochemical descriptor is log P (1-octanol/water partition coefficient). For obtaining appropriate QSAR model we have used multiple linear regression (MLR) techniques and followed back ward regression analysis. The results have shown that the best models are obtained by multi parametric analysis.The toxicity (pIGC50) of 28 aliphatic carboxylic acids is well predicted by a two parametric model consisting of hyperWiener (WW) and partition coefficient (logP) as the correlating parameters. The predictive ability of the model is discussed on the basis of predictive correlation coefficient. The best model in this study are included, with values of the correlation coefficient (r=0.965), the standard error (s=0.105mg/L), the Fisher-ratio (F=168.183), the adjusted coefficient of determination (= 0.925) and Durbin-Watson value (D=1.234), which indicate that these descriptors, play an important role in effect on toxicity of aliphatic carboxylic acids.

Keywords:

QSAR , Topological indices , Toxicity , physicochemical descriptors , carboxylic acid