Predicting multiple ecotoxicological profiles in agrochemical fungicides: A multi-species chemoinformatic approach

Alejandro Speck-Planche, Valeria V. Kleandrova, Feng Luan, M. Natália D.S. Cordeiro

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

63 Citas (Scopus)

Resumen

Agriculture is needed to deal with crop losses caused by biotic stresses like pests. The use of pesticides has played a vital role, contributing to improve crop production and harvest productivity, providing a better crop quality and supply, and consequently contributing with the improvement of the human health. An important group of these pesticides is fungicides. However, the use of these agrochemical fungicides is an important source of contamination, damaging the ecosystems. Several studies have been realized for the assessment of the toxicity in agrochemical fungicides, but the principal limitation is the use of structurally related compounds against usually one indicator species. In order to overcome this problem, we explore the quantitative structure-toxicity relationships (QSTR) in agrochemical fungicides. Here, we developed the first multi-species (ms) chemoinformatic approach for the prediction multiple ecotoxicological profiles of fungicides against 20 indicators species and their classifications in toxic or nontoxic. The ms-QSTR discriminant model was based on substructural descriptors and a heterogeneous database of compounds. The percentages of correct classification were higher than 90% for both, training and prediction series. Also, substructural alerts responsible for the toxicity/no toxicity in fungicides respect all ecotoxicological profiles, were extracted and analyzed.

Idioma originalInglés
Páginas (desde-hasta)308-313
Número de páginas6
PublicaciónEcotoxicology and Environmental Safety
Volumen80
DOI
EstadoPublicada - 1 jun. 2012
Publicado de forma externa

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