Conformation-independent quantitative structure-property relationships study on water solubility of pesticides

Water solubility is a key physicochemical parameter in pesticide control and regulation, although sometimes its experimental determination is not an easy task. In this study, we present Quantitative Structure-Property Relationships (QSPRs) for predicting the water solubility at 20 °C of 1211 approve...

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Autores principales: Fioressi, S.E., Bacelo, D.E., Rojas, C., Aranda, J.F., Duchowicz, P.R.
Formato: JOUR
Materias:
CORAL software
Molecular descriptors
Pesticides
Quantitative structure-property relationships
Water solubility
pesticide
water
molecular analysis
pesticide residue
physicochemical property
quantitative analysis
regression analysis
software
solubility
Article
chemical structure
conformation
multiple linear regression analysis
quantitative structure property relation
chemistry
quantitative structure activity relation
statistical model
Linear Models
Molecular Conformation
Quantitative Structure-Activity Relationship
Solubility
Water
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01476513_v171_n_p47_Fioressi
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_01476513_v171_n_p47_Fioressi
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spelling todo:paper_01476513_v171_n_p47_Fioressi2023-10-03T15:00:42Z Conformation-independent quantitative structure-property relationships study on water solubility of pesticides Fioressi, S.E. Bacelo, D.E. Rojas, C. Aranda, J.F. Duchowicz, P.R. CORAL software Molecular descriptors Pesticides Quantitative structure-property relationships Water solubility pesticide pesticide water molecular analysis pesticide residue physicochemical property quantitative analysis regression analysis software solubility Article chemical structure conformation multiple linear regression analysis quantitative structure property relation solubility chemistry quantitative structure activity relation solubility statistical model Linear Models Molecular Conformation Pesticides Quantitative Structure-Activity Relationship Solubility Water Water solubility is a key physicochemical parameter in pesticide control and regulation, although sometimes its experimental determination is not an easy task. In this study, we present Quantitative Structure-Property Relationships (QSPRs) for predicting the water solubility at 20 °C of 1211 approved heterogeneous pesticide compounds, collected from the online Pesticides Properties Data Base (PPDB). Validated and generally applicable Multivariable Linear Regression (MLR) models were established, including molecular descriptors carrying constitutional and topological aspects of the analyzed compounds. The most representative descriptors were selected from the exploration of a large number of about 18,000 structural variables. A hybrid approach that involves a molecular descriptor, a fingerprint, and a flexible descriptor showed the best predictive performance. © 2018 Elsevier Inc. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01476513_v171_n_p47_Fioressi
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic CORAL software
Molecular descriptors
Pesticides
Quantitative structure-property relationships
Water solubility
pesticide
pesticide
water
molecular analysis
pesticide residue
physicochemical property
quantitative analysis
regression analysis
software
solubility
Article
chemical structure
conformation
multiple linear regression analysis
quantitative structure property relation
solubility
chemistry
quantitative structure activity relation
solubility
statistical model
Linear Models
Molecular Conformation
Pesticides
Quantitative Structure-Activity Relationship
Solubility
Water
spellingShingle CORAL software
Molecular descriptors
Pesticides
Quantitative structure-property relationships
Water solubility
pesticide
pesticide
water
molecular analysis
pesticide residue
physicochemical property
quantitative analysis
regression analysis
software
solubility
Article
chemical structure
conformation
multiple linear regression analysis
quantitative structure property relation
solubility
chemistry
quantitative structure activity relation
solubility
statistical model
Linear Models
Molecular Conformation
Pesticides
Quantitative Structure-Activity Relationship
Solubility
Water
Fioressi, S.E.
Bacelo, D.E.
Rojas, C.
Aranda, J.F.
Duchowicz, P.R.
Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
topic_facet CORAL software
Molecular descriptors
Pesticides
Quantitative structure-property relationships
Water solubility
pesticide
pesticide
water
molecular analysis
pesticide residue
physicochemical property
quantitative analysis
regression analysis
software
solubility
Article
chemical structure
conformation
multiple linear regression analysis
quantitative structure property relation
solubility
chemistry
quantitative structure activity relation
solubility
statistical model
Linear Models
Molecular Conformation
Pesticides
Quantitative Structure-Activity Relationship
Solubility
Water
description Water solubility is a key physicochemical parameter in pesticide control and regulation, although sometimes its experimental determination is not an easy task. In this study, we present Quantitative Structure-Property Relationships (QSPRs) for predicting the water solubility at 20 °C of 1211 approved heterogeneous pesticide compounds, collected from the online Pesticides Properties Data Base (PPDB). Validated and generally applicable Multivariable Linear Regression (MLR) models were established, including molecular descriptors carrying constitutional and topological aspects of the analyzed compounds. The most representative descriptors were selected from the exploration of a large number of about 18,000 structural variables. A hybrid approach that involves a molecular descriptor, a fingerprint, and a flexible descriptor showed the best predictive performance. © 2018 Elsevier Inc.
format JOUR
author Fioressi, S.E.
Bacelo, D.E.
Rojas, C.
Aranda, J.F.
Duchowicz, P.R.
author_facet Fioressi, S.E.
Bacelo, D.E.
Rojas, C.
Aranda, J.F.
Duchowicz, P.R.
author_sort Fioressi, S.E.
title Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
title_short Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
title_full Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
title_fullStr Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
title_full_unstemmed Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
title_sort conformation-independent quantitative structure-property relationships study on water solubility of pesticides
url http://hdl.handle.net/20.500.12110/paper_01476513_v171_n_p47_Fioressi
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AT bacelode conformationindependentquantitativestructurepropertyrelationshipsstudyonwatersolubilityofpesticides
AT rojasc conformationindependentquantitativestructurepropertyrelationshipsstudyonwatersolubilityofpesticides
AT arandajf conformationindependentquantitativestructurepropertyrelationshipsstudyonwatersolubilityofpesticides
AT duchowiczpr conformationindependentquantitativestructurepropertyrelationshipsstudyonwatersolubilityofpesticides
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