Open AccessQSAR studies for the acute toxicity of nitrobenzenes to the Tetrahymena pyriformis
Author(s) -
Dandan Wang,
Lin-Lin Feng,
Guangyu He,
Haiqun Chen
Publication year - 2014
Publication title -
journal of the serbian chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 45
eISSN - 1820-7421
pISSN - 0352-5139
DOI - 10.2298/jsc130910025w
Subject(s) - tetrahymena pyriformis , quantitative structure–activity relationship , nitrobenzene , tetrahymena , toxicity , acute toxicity , chemistry , biological system , mathematics , stereochemistry , biology , biochemistry , organic chemistry , catalysis
Quantitative structure-activity relationship (QSAR) models play a key role in finding the relationship between molecular structures and the toxicity of nitrobenzenes to Tetrahymena pyriformis. In this work, genetic algorithm, along with partial least square (GA-PLS) was employed to select optimal subset of descriptors that have significant contribution to the toxicity of nitrobenzenes to Tetrahymena pyriformis. A set of five descriptors, namely G2, HOMT, G(Cl…Cl), Mor03v and MAXDP, was used for the prediction of the toxicity of 45 nitrobenzene derivatives and then were used to build the model by multiple linear regression (MLR) method. It turned out that the built model, whose stability was confirmed using the leave-one-out validation and external validation test, showed high statistical significance (R2=0.963, Q2LOO=0.944). Moreover, Y-scrambling test indicated there was no chance correlation in this model