Predicting the bioconcentration factor through a conformation-independent QSPR study

The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 are pesticides. The BCF ANTARES data were used to derive a conformation-independent QSPR model. A large set of 27,017 molecular descr...

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Autores principales: Aranda, J.F., Bacelo, D.E., Leguizamón Aparicio, M.S., Ocsachoque, M.A., Castro, E.A., Duchowicz, P.R.
Formato: JOUR
Materias:
Bioconcentration factor (BCF)
molecular descriptors
pesticides
quantitative structure-property relationships
replacement method
organic compound
bioremediation
chemical model
chemistry
conformation
quantitative structure activity relation
risk assessment
statistical model
Biodegradation, Environmental
Linear Models
Models, Chemical
Molecular Conformation
Organic Chemicals
Quantitative Structure-Activity Relationship
Risk Assessment
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_1062936X_v28_n9_p749_Aranda
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_1062936X_v28_n9_p749_Aranda
record_format dspace
spelling todo:paper_1062936X_v28_n9_p749_Aranda2023-10-03T16:01:09Z Predicting the bioconcentration factor through a conformation-independent QSPR study Aranda, J.F. Bacelo, D.E. Leguizamón Aparicio, M.S. Ocsachoque, M.A. Castro, E.A. Duchowicz, P.R. Bioconcentration factor (BCF) molecular descriptors pesticides quantitative structure-property relationships replacement method organic compound bioremediation chemical model chemistry conformation quantitative structure activity relation risk assessment statistical model Biodegradation, Environmental Linear Models Models, Chemical Molecular Conformation Organic Chemicals Quantitative Structure-Activity Relationship Risk Assessment The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 are pesticides. The BCF ANTARES data were used to derive a conformation-independent QSPR model. A large set of 27,017 molecular descriptors was explored, with the main intention of capturing the most relevant structural characteristics affecting the studied property. The structural descriptors were derived with different freeware tools, such as PaDEL, Epi Suite, CORAL, Mold2, RECON, and QuBiLs-MAS, and so it was interesting to find out the way that the different descriptor tools complemented each other in order to improve the statistical quality of the established QSPR. The best multivariable linear regression models were found with the Replacement Method variable sub-set selection technique. The proposed QSPR model improves previous reported models of the bioconcentration factor in the present dataset. © 2017 Informa UK Limited, trading as Taylor & Francis Group. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_1062936X_v28_n9_p749_Aranda
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Bioconcentration factor (BCF)
molecular descriptors
pesticides
quantitative structure-property relationships
replacement method
organic compound
bioremediation
chemical model
chemistry
conformation
quantitative structure activity relation
risk assessment
statistical model
Biodegradation, Environmental
Linear Models
Models, Chemical
Molecular Conformation
Organic Chemicals
Quantitative Structure-Activity Relationship
Risk Assessment
spellingShingle Bioconcentration factor (BCF)
molecular descriptors
pesticides
quantitative structure-property relationships
replacement method
organic compound
bioremediation
chemical model
chemistry
conformation
quantitative structure activity relation
risk assessment
statistical model
Biodegradation, Environmental
Linear Models
Models, Chemical
Molecular Conformation
Organic Chemicals
Quantitative Structure-Activity Relationship
Risk Assessment
Aranda, J.F.
Bacelo, D.E.
Leguizamón Aparicio, M.S.
Ocsachoque, M.A.
Castro, E.A.
Duchowicz, P.R.
Predicting the bioconcentration factor through a conformation-independent QSPR study
topic_facet Bioconcentration factor (BCF)
molecular descriptors
pesticides
quantitative structure-property relationships
replacement method
organic compound
bioremediation
chemical model
chemistry
conformation
quantitative structure activity relation
risk assessment
statistical model
Biodegradation, Environmental
Linear Models
Models, Chemical
Molecular Conformation
Organic Chemicals
Quantitative Structure-Activity Relationship
Risk Assessment
description The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 are pesticides. The BCF ANTARES data were used to derive a conformation-independent QSPR model. A large set of 27,017 molecular descriptors was explored, with the main intention of capturing the most relevant structural characteristics affecting the studied property. The structural descriptors were derived with different freeware tools, such as PaDEL, Epi Suite, CORAL, Mold2, RECON, and QuBiLs-MAS, and so it was interesting to find out the way that the different descriptor tools complemented each other in order to improve the statistical quality of the established QSPR. The best multivariable linear regression models were found with the Replacement Method variable sub-set selection technique. The proposed QSPR model improves previous reported models of the bioconcentration factor in the present dataset. © 2017 Informa UK Limited, trading as Taylor & Francis Group.
format JOUR
author Aranda, J.F.
Bacelo, D.E.
Leguizamón Aparicio, M.S.
Ocsachoque, M.A.
Castro, E.A.
Duchowicz, P.R.
author_facet Aranda, J.F.
Bacelo, D.E.
Leguizamón Aparicio, M.S.
Ocsachoque, M.A.
Castro, E.A.
Duchowicz, P.R.
author_sort Aranda, J.F.
title Predicting the bioconcentration factor through a conformation-independent QSPR study
title_short Predicting the bioconcentration factor through a conformation-independent QSPR study
title_full Predicting the bioconcentration factor through a conformation-independent QSPR study
title_fullStr Predicting the bioconcentration factor through a conformation-independent QSPR study
title_full_unstemmed Predicting the bioconcentration factor through a conformation-independent QSPR study
title_sort predicting the bioconcentration factor through a conformation-independent qspr study
url http://hdl.handle.net/20.500.12110/paper_1062936X_v28_n9_p749_Aranda
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AT ocsachoquema predictingthebioconcentrationfactorthroughaconformationindependentqsprstudy
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