Hydrophobicity versus electrophilicity: A new protocol toward quantitative structure–toxicity relationship

Abstract

Abstract QSAR / QSPR / QSTR modeling and chemical grouping approach are presented to provide information on the biological properties of various substituted benzene derivatives. A novel descriptor, viz., the square of electrophilicity index ( ω 2 ) is proposed to provide a compact correlation between the structure of the compounds and their biological properties which is marginally superior to electrophilicity index ( ω ) or ω 3 in most of the cases, and more or less similar to that obtained from hydrophobicity (or lipophilicity). Besides the straightforward case study, neural networks ( NN ) are employed to ascertain the robustness of the QSAR model obtained by implementing multiple linear regression ( MLR ).