QSAR Modeling of Acute Toxicity for Nitrobenzene Derivatives Towards Rats: Comparative Analysis by MLRA and Optimal Descriptors

Abstract

Quantitative Structure -Activity Relationships (QSAR) have been developed for a set of 28 benzene derivatives. LD 50 oral toxicity of these compounds towards rats has been modeled by Multiple Linear Regression Analysis (MLRA) based on descriptors generated by DRAGON software and by optimal descriptors approach. Twenty-eight benzene derivatives have been split into training (n ¼ 14) and test (n ¼ 14) sets. In the case of MLRA, a two-variable model has the best predictive potential. Comparison of the quality of MLRA and optimal descriptor models showed that the predictive potential of a onevariable model based on optimal descriptors is better than a two-variable MLRA model.

QSAR model as a random event: A case of rat toxicity

“…41 The comparison of models which are calculated by means of Eqs. 5-14 with the above-mentioned QSAR models taken in the literature 36,[39][40][41] indicates that suggested approach can be useful for QSAR analysis of toxicity in rat.…”

“…37 There are QSAR models for toxicity in rat described in the literature. 36,[39][40][41][42] The comparison of statistical quality of models for toxicity in rat which are calculated with Eqs. 5-14 and models described in 36 indicates a paradoxical situation: correlation coefficients for Eqs.…”

“…36 This paradox probably is result of difference in the assortment of compounds which were studied here and compounds which were studied in. 36 The comparison of statistical quality of QSAR models for toxicity in rat described in 39 has shown (i) the DRAGON generated descriptors and optimal descriptors give similar quality of prediction for this endpoint; (ii) the increase of the number of descriptors involved in building up QSAR can lead to overtraining; and (iii) statistical quality of the best QSAR suggested in 39 is the following n = 14, r 2 = 0.9154 (test set). In other words, the correlation coefficient is higher than the correlation coefficients of Eqs.…”

In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study

“…Previously only small datasets for in vivo toxicity of nitroaromatics were investigated, and in the case of large datasets, only in vitro toxicity toward different kinds of bacteria was considered [30][31][32]. To our knowledge, this is the largest dataset to date containing rodent toxicity data for nitrocompounds.…”

“…To our knowledge, this is the largest dataset to date containing rodent toxicity data for nitrocompounds. Previously only small datasets for in vivo toxicity of nitroaromatics were investigated, and in the case of large datasets, only in vitro toxicity toward different kinds of bacteria was considered [30][31][32]. Experimental data for the compounds were analyzed and compiled utilizing data from the US National Library of Medicine's ToxNet-ChemID database [27].…”