Artículo
QSAR models for the fumigant activity prediction of essential oils
Duchowicz, Pablo Román
; Bennardi, Daniel Oscar; Ortiz, Erlinda del Valle
; Comelli, Nieves Carolina
Fecha de publicación:
12/2020
Editorial:
Elsevier Science Inc.
Revista:
Journal Of Molecular Graphics & Modelling
ISSN:
1093-3263
e-ISSN:
1873-4243
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The Quantitative Structure-Activity Relationships (QSAR) theory, which allows predicting the insecticidal activity of chemical compounds through calculations from the molecular structure, is applied on 23 essential oils composed of 402 structurally diverse compounds at different chemical compositions. A large number of 114,871 conformation-independent molecular descriptors are computed through different types of freely available open-source programs. Mixture descriptors are calculated based on molecular descriptors of the essential oil components and their composition. The best resulting three-descriptor linear regression models are established through the Replacement Method variable subset selection approach. The results obtained in the present work are interesting for predicting the fumigant activity of these essential oil complex mixtures, by means of simple non-conformational QSAR models.
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Articulos(INIFTA)
Articulos de INST.DE INV.FISICOQUIMICAS TEORICAS Y APLIC.
Articulos de INST.DE INV.FISICOQUIMICAS TEORICAS Y APLIC.
Articulos(SEDE CENTRAL)
Articulos de SEDE CENTRAL
Articulos de SEDE CENTRAL
Citación
Duchowicz, Pablo Román; Bennardi, Daniel Oscar; Ortiz, Erlinda del Valle; Comelli, Nieves Carolina; QSAR models for the fumigant activity prediction of essential oils; Elsevier Science Inc.; Journal Of Molecular Graphics & Modelling; 101; 12-2020; 1-7
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