INIFTA   05425
INSTITUTO DE INVESTIGACIONES FISICO-QUIMICAS TEORICAS Y APLICADAS
Unidad Ejecutora - UE
artículos
Título:
Predicting the Bioconcentration Factor Through a Conformation- Independent QSPR Study
Autor/es:
J.F.ARANDA; MARCO.A.OCSACHOQUE; J.F.ARANDA; MARCO.A.OCSACHOQUE; M.SILVIA LEGUIZAMÓN APARICIO; PABLO DUCHOWICZ; M.SILVIA LEGUIZAMÓN APARICIO; PABLO DUCHOWICZ; D.E.BACELO; E.CASTRO; D.E.BACELO; E.CASTRO
Revista:
SAR AND QSAR IN ENVIRONMENTAL RESEARCH
Editorial:
TAYLOR & FRANCIS LTD
Referencias:
Lugar: Londres; Año: 2017 p. 749 - 763
ISSN:
1062-936X
Resumen:
The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 of them are pesticides. In this Special Issue devoted to "Computational Toxicology and Fate of Pesticides", we predict the Bioconcentration Factor of the ANTARES dataset by means of a conformation independent QSPR approach. A large number of 27,017 molecular descriptors are explored, with the main intention of capturing the most relevant structural characteristics affecting the studied property. The structural descriptors are derived with different freewares, such as PaDEL, Epi Suite, CORAL, Mold2, RECON and QuBiLs-MAS, and so it is interesting to find out the way that the different descriptor softwares complement each other in order to improve the statistical quality of the established QSPR. The best multivariable linear regression models are found with the Replacement Method variable subset selection technique. The proposed QSPR model improves previous reported models of the bioconcentration factor in the present dataset.