Semi-empirical (PM3) Based Insillico Prediction of Acute Toxicity of Phenols

Ibraheem Wasiu Aderemi, Jangbe

Abstract

A toxicity data set of 58 phenols to Tetrahymena pyriformis expressed as pEC50 (Log to base 10 of EC50) was taken from literature. 70% (41 phenols) of the data was used as training set while 30% (17 phenols) was used as test set. Muti-linear Regression equations were built using the experimental pEC50as dependent variable and the various molecular descriptors as independent variables. The best Quantitative structure-toxicity relationship (QSTR) model hinted that the toxicity of phenol was dominantly influenced by octanol-water partition coefficient (XlogP) and moment of inertia (MOMI) descriptors. The results of the statistical analysis of the two parameter model include; n = 41, LOF score = 0.079, R2 = 0.6691, R2adj. = 0.6517, Q2LOO = 0.6260, F-value = 38.42. The generated QSTR model has been proven to possess statistical significance, high predictive power and wide applicability domain. Thus, it is recommended for environmental risk assessment of phenols.

Relevant Publications in Journal of Computational Methods in Molecular Design