QSAR Modeling of Acute Toxicity for Nitrobenzene Derivatives Towards Rats: Comparative Analysis by MLRA and Optimal Descriptors
Andrey A. ToropovComputational Center for Molecular Structure and Interactions, Department of Chemistry, Jackson State University, 1400 JR. Lynch Street, PO. Box 17910, Jackson, MS 39217, USABakhtiyor RasulevComputational Center for Molecular Structure and Interactions, Department of Chemistry, Jackson State University, 1400 JR. Lynch Street, PO. Box 17910, Jackson, MS 39217, USAJerzy LeszczyńskiComputational Center for Molecular Structure and Interactions, Department of Chemistry, Jackson State University, 1400 JR. Lynch Street, PO. Box 17910, Jackson, MS 39217, USA
2007en
ABI
Annotatsiya
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= 14) and test ( n =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 one‐variable model based on optimal descriptors is better than a two‐variable MLRA model.
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