The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants

Autores
Ortiz, Erlinda V.; Bennardi, Daniel Oscar; Bacelo, Daniel E.; Fioressi, Silvina E.; Duchowiczblo
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (kOH) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: R2 train = 0:88, RMStrain = 0.21, while for the test set is R2 test = 0:87, RMStest = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
Facultad de Ciencias Agrarias y Forestales
Materia
Química
Reaction rate constant
Water micropollutant
Quantitative structure-property relationships
Replacement method
Molecular descriptors
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/103999
Acceder
id SEDICI_8116962a14028b570ba1b37a1a257fff
oai_identifier_str oai:sedici.unlp.edu.ar:10915/103999
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutantsOrtiz, Erlinda V.Bennardi, Daniel OscarBacelo, Daniel E.Fioressi, Silvina E.DuchowiczbloQuímicaReaction rate constantWater micropollutantQuantitative structure-property relationshipsReplacement methodMolecular descriptorsIn advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k<sub>OH</sub>) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: R<sup>2</sup> <sub>train</sub> = 0:88, RMS<sub>train</sub> = 0.21, while for the test set is R<sup>2</sup> <sub>test</sub> = 0:87, RMS<sub>test</sub> = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.Instituto de Investigaciones Fisicoquímicas Teóricas y AplicadasFacultad de Ciencias Agrarias y Forestales2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/103999enginfo:eu-repo/semantics/altIdentifier/issn/1614-7499info:eu-repo/semantics/altIdentifier/doi/10.1007/s11356-017-0315-5info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:22:38Zoai:sedici.unlp.edu.ar:10915/103999Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:22:39.076SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
title The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
spellingShingle The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
Ortiz, Erlinda V.
Química
Reaction rate constant
Water micropollutant
Quantitative structure-property relationships
Replacement method
Molecular descriptors
title_short The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
title_full The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
title_fullStr The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
title_full_unstemmed The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
title_sort The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants
dc.creator.none.fl_str_mv Ortiz, Erlinda V.
Bennardi, Daniel Oscar
Bacelo, Daniel E.
Fioressi, Silvina E.
Duchowiczblo
author Ortiz, Erlinda V.
author_facet Ortiz, Erlinda V.
Bennardi, Daniel Oscar
Bacelo, Daniel E.
Fioressi, Silvina E.
Duchowiczblo
author_role author
author2 Bennardi, Daniel Oscar
Bacelo, Daniel E.
Fioressi, Silvina E.
Duchowiczblo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Química
Reaction rate constant
Water micropollutant
Quantitative structure-property relationships
Replacement method
Molecular descriptors
topic Química
Reaction rate constant
Water micropollutant
Quantitative structure-property relationships
Replacement method
Molecular descriptors
dc.description.none.fl_txt_mv In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k<sub>OH</sub>) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: R<sup>2</sup> <sub>train</sub> = 0:88, RMS<sub>train</sub> = 0.21, while for the test set is R<sup>2</sup> <sub>test</sub> = 0:87, RMS<sub>test</sub> = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
Facultad de Ciencias Agrarias y Forestales
description In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k<sub>OH</sub>) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: R<sup>2</sup> <sub>train</sub> = 0:88, RMS<sub>train</sub> = 0.21, while for the test set is R<sup>2</sup> <sub>test</sub> = 0:87, RMS<sub>test</sub> = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/103999
url http://sedici.unlp.edu.ar/handle/10915/103999
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1614-7499
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11356-017-0315-5
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.070432

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