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Predicting the Thermal Stability of Nitroaromatic Compounds Using Chemoinformatic Tools.
Fayet, Guillaume; Del Rio, Alberto; Rotureau, Patricia; Joubert, Laurent; Adamo, Carlo.
Afiliação
  • Fayet G; Institut National de l'Environnement Industriel et des Risques (INERIS), Direction des Risques Accidentels, Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte, France.
  • Del Rio A; Laboratoire d'Electrochimie, Chimie des Interfaces et Modélisation pour l'Energie (LECIME), CNRS UMR-7575, Chimie ParisTech, 11 rue P. et M. Curie, 75231 Paris Cedex 05, France phone +33 1 44 2767 28.
  • Rotureau P; Dipartimento di Scienze Farmaceutiche, Università di Modena e Reggio Emilia, Via Campi 183, 41100 Modena, Italy. alberto.delrio@gmail.com.
  • Joubert L; Dipartimento di Patologia Sperimentale, Università di Bologna via S. Giacomo 14, 40126 Bologna, Italy phone +39 051 2094004. alberto.delrio@gmail.com.
  • Adamo C; Institut National de l'Environnement Industriel et des Risques (INERIS), Direction des Risques Accidentels, Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte, France.
Mol Inform ; 30(6-7): 623-34, 2011 Jun.
Article em En | MEDLINE | ID: mdl-27467162
ABSTRACT
In the framework of the European REACH regulation major attention was recently devoted to toxicological and ecotoxicological problems while little attention has been dedicated to other important applications concerning chemical hazards, for instance, explosive properties. In this work different chemoinformatic tools such as partial least squares, multilinear regressions, and decision trees have been used for the development of a novel quantitative structure-property relationships to predict the heat of decomposition of a series of nitroaromatic compounds. Models were conceived in order to follow the regulatory requirements according to OECD principles for the validation of QSAR methods. Three models derived with MLR, PLS and decision tree techniques were developed, validated (internally and externally) and their applicability domains have been defined and analyzed. All models proved to be reliable with remarkable robustness in terms of full cross-validation scheme and showed good predictive power toward the external validation set. These models also present a large applicability domain within nitrobenzene derivatives and are easy to implement and interpret in terms of subjacent mechanisms.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2011 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2011 Tipo de documento: Article