QSAR study for the fish toxicity of benzene derivatives

We searched Quantitative Structure-Toxicity models for predicting the fish toxicity against Poecilia reticulata elicited by a diverse set of 92 benzene derivatives. The simultaneous linear regression analyzes on 1176 constitutional, topological, geometrical, electronic, and lipophilic molecular desc...

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Detalles Bibliográficos
Autores principales: Duchowicz, Pablo Román, Marrugo, Juan J., Ortiz, Erlinda V., Castro, Eduardo Alberto, Vivas Reyes, Ricardo
Formato: Articulo
Lenguaje:Inglés
Publicado: 2009
Materias:
Química
QSAR theory
replacement method
benzene derivatives
poecilia reticulata
pC
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/177409
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
Descripción
Sumario:We searched Quantitative Structure-Toxicity models for predicting the fish toxicity against Poecilia reticulata elicited by a diverse set of 92 benzene derivatives. The simultaneous linear regression analyzes on 1176 constitutional, topological, geometrical, electronic, and lipophilic molecular descriptors derived from the software Dragon lead to a three-parameter relationship characterized with correlation coefficient of calibration of R=0.953, Leave-one-out Cross Validation of Rloo=0.947, and test set validation of Rval=0.889, and compares fairly well with a previously reported model based on extended topo-chemical atom (ETA) indices. Our developed QSAR involves a topological descriptor as the most relevant variable for the set of chemicals, a 3D-MoRSE and a Radial Distribution Function descriptor that show low inter-correlations.

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