QSAR study in terms of conceptual density functional theory based descriptors in predicting toxicity of nitrobenzenes towards Tetrahymena pyriformis

Rajak, Sandip Kumar


Quantitative Structure -Activity Relationship (QSAR) models are enormously significant to understand the correlation of chemical structure with the biological activity and toxicity of chemicals. In the ongoing study reveals the prediction power of toxicity of 45 nitrobenzenes (NBs) entailing some conceptual density functional theory based reactivity descriptors namely electrophilicity index (ω), lowest unoccupied molecular orbital (εlumo) and molecular compressibility (β) along with the hydrophobicity index (logP). Multilinear Regression (MLR) method is adopted to develop the QSAR model. Stability of the present QSAR model is confirmed through the cross validation method and is potentially describe the 85% of the variance of the experimental toxicity.


CDFT; Nitobenzenes; QSAR; Regression; Toxicity

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