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Título : QSAR study for predicting the ecotoxicity of NADES towards Aliivibrio fischeri. Exploring the use of mixing rules (Versión suministrada)
Autor: Giner Parache, Beatriz SCOPUSID
Lafuente, Carlos ORCID RESEARCHERID SCOPUSID
Lapeña-Gil, David ORCID SCOPUSID
Errazquin, Diego
Lomba Eraso, Laura ORCID RESEARCHERID SCOPUSID
Palabras clave : QSAR; NADES; Aliivibrio fischeri; Multiple regression model; Ecotoxicity
Fecha de publicación: 15-mar-2020
Editorial : Elsevier
Citación : Giner B, Lafuente C, Lapeña D, Errazquin D, Lomba L. QSAR study for predicting the ecotoxicity of NADES towards Aliivibrio fischeri. Exploring the use of mixing rules. Ecotoxicol Environ Saf. 2020 Mar 15;191:110004. doi: 10.1016/j.ecoenv.2019.110004. Epub 2019 Dec 3. PMID: 31810589.
Resumen : (Eco)toxicological information of natural deep eutectic solvents (NADES) is scarce, and thus, quantitative structure activity relationship (QSAR) models are an important tool for achieving the prediction of toxicity in this case. For that reason, in this manuscript, a new QSAR model for predicting the ecotoxicity of NADES towards the Aliivibrio fischeri biomodel, using mixing rules, is proposed. The main advantage of the method is that the individual components of the mixtures are molecularly modelled, and then, a mixing rule is used, which simplifies the process. For developing the model, a total of 11 descriptors for each component is used: the dissociation constant, partition coefficient, Van der Waals volume, Van der Waals surface area, topological polar surface area, solvent accessible surface area, minimum projection area, maximum projection area, minimum projection radius, maximum projection radius and molecular weight. The final obtained model includes the topological polar surface area and the dissociation constant, mechanistically interpreted as the ability of a NADES to transport through biological membranes and the severe negative effect of pH on the toxicity and biological response of Aliivibrio fischeri bacteria. The OECD Guidance Document on the Validation of (Quantitative) Structure-Activity Relationships is followed to develop the mathematical model.
URI : https://repositorio.usj.es/handle/123456789/1082
ISSN : 1090-2414
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