A New QSPR Study on Relative Sweetness

Autores
Rojas Villa, Cristian Xavier; Tripaldi, Piercosimo; Duchowicz, Pablo Román
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The aim of this work was to develop predictive structure-property relationships (QSPR) of natural andsynthetic sweeteners in order to predict and model relative sweetness (RS). The data set was composedof 233 sweeteners collected from diverse sources in the literature, which was divided into training(163) and test (70) molecules according to a procedure based on k-means cluster analysis. A total of3763 non-conformational Dragon molecular descriptors were calculated which were simultaneouslyanalyzed through multivariable linear regression analysis coupled with the replacement methodvariable subset selection technique. The established six-parameter model was validated throughthe cross-validation techniques, together with Y-randomization and applicability domain analysis.The results for the training set and the test set showed that the non-conformational descriptors offerrelevant information for modeling the RS of a compound. Thus, this model can be used to predictthe sweetness of both un-evaluated and un-synthesized sweeteners.
Fil: Rojas Villa, Cristian Xavier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Fil: Tripaldi, Piercosimo. Universidad del Azuay; Ecuador
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Materia
Teoría Qspr
Relative Sweetness
K-Means Cluster Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/48870
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A New QSPR Study on Relative SweetnessRojas Villa, Cristian XavierTripaldi, PiercosimoDuchowicz, Pablo RománTeoría QsprRelative SweetnessK-Means Cluster Analysishttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The aim of this work was to develop predictive structure-property relationships (QSPR) of natural andsynthetic sweeteners in order to predict and model relative sweetness (RS). The data set was composedof 233 sweeteners collected from diverse sources in the literature, which was divided into training(163) and test (70) molecules according to a procedure based on k-means cluster analysis. A total of3763 non-conformational Dragon molecular descriptors were calculated which were simultaneouslyanalyzed through multivariable linear regression analysis coupled with the replacement methodvariable subset selection technique. The established six-parameter model was validated throughthe cross-validation techniques, together with Y-randomization and applicability domain analysis.The results for the training set and the test set showed that the non-conformational descriptors offerrelevant information for modeling the RS of a compound. Thus, this model can be used to predictthe sweetness of both un-evaluated and un-synthesized sweeteners.Fil: Rojas Villa, Cristian Xavier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Tripaldi, Piercosimo. Universidad del Azuay; EcuadorFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaIGI-Global2016-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/48870Rojas Villa, Cristian Xavier; Tripaldi, Piercosimo; Duchowicz, Pablo Román; A New QSPR Study on Relative Sweetness; IGI-Global; International Journal of Quantitative Structure-Property Relationships; 1; 1; 1-2016; 78-932379-7479CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.4018/IJQSPR.2016010104info:eu-repo/semantics/altIdentifier/url/https://www.igi-global.com/gateway/article/144691info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:25:54Zoai:ri.conicet.gov.ar:11336/48870instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:25:54.449CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A New QSPR Study on Relative Sweetness
title A New QSPR Study on Relative Sweetness
spellingShingle A New QSPR Study on Relative Sweetness
Rojas Villa, Cristian Xavier
Teoría Qspr
Relative Sweetness
K-Means Cluster Analysis
title_short A New QSPR Study on Relative Sweetness
title_full A New QSPR Study on Relative Sweetness
title_fullStr A New QSPR Study on Relative Sweetness
title_full_unstemmed A New QSPR Study on Relative Sweetness
title_sort A New QSPR Study on Relative Sweetness
dc.creator.none.fl_str_mv Rojas Villa, Cristian Xavier
Tripaldi, Piercosimo
Duchowicz, Pablo Román
author Rojas Villa, Cristian Xavier
author_facet Rojas Villa, Cristian Xavier
Tripaldi, Piercosimo
Duchowicz, Pablo Román
author_role author
author2 Tripaldi, Piercosimo
Duchowicz, Pablo Román
author2_role author
author
dc.subject.none.fl_str_mv Teoría Qspr
Relative Sweetness
K-Means Cluster Analysis
topic Teoría Qspr
Relative Sweetness
K-Means Cluster Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The aim of this work was to develop predictive structure-property relationships (QSPR) of natural andsynthetic sweeteners in order to predict and model relative sweetness (RS). The data set was composedof 233 sweeteners collected from diverse sources in the literature, which was divided into training(163) and test (70) molecules according to a procedure based on k-means cluster analysis. A total of3763 non-conformational Dragon molecular descriptors were calculated which were simultaneouslyanalyzed through multivariable linear regression analysis coupled with the replacement methodvariable subset selection technique. The established six-parameter model was validated throughthe cross-validation techniques, together with Y-randomization and applicability domain analysis.The results for the training set and the test set showed that the non-conformational descriptors offerrelevant information for modeling the RS of a compound. Thus, this model can be used to predictthe sweetness of both un-evaluated and un-synthesized sweeteners.
Fil: Rojas Villa, Cristian Xavier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Fil: Tripaldi, Piercosimo. Universidad del Azuay; Ecuador
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
description The aim of this work was to develop predictive structure-property relationships (QSPR) of natural andsynthetic sweeteners in order to predict and model relative sweetness (RS). The data set was composedof 233 sweeteners collected from diverse sources in the literature, which was divided into training(163) and test (70) molecules according to a procedure based on k-means cluster analysis. A total of3763 non-conformational Dragon molecular descriptors were calculated which were simultaneouslyanalyzed through multivariable linear regression analysis coupled with the replacement methodvariable subset selection technique. The established six-parameter model was validated throughthe cross-validation techniques, together with Y-randomization and applicability domain analysis.The results for the training set and the test set showed that the non-conformational descriptors offerrelevant information for modeling the RS of a compound. Thus, this model can be used to predictthe sweetness of both un-evaluated and un-synthesized sweeteners.
publishDate 2016
dc.date.none.fl_str_mv 2016-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/48870
Rojas Villa, Cristian Xavier; Tripaldi, Piercosimo; Duchowicz, Pablo Román; A New QSPR Study on Relative Sweetness; IGI-Global; International Journal of Quantitative Structure-Property Relationships; 1; 1; 1-2016; 78-93
2379-7479
CONICET Digital
CONICET
url http://hdl.handle.net/11336/48870
identifier_str_mv Rojas Villa, Cristian Xavier; Tripaldi, Piercosimo; Duchowicz, Pablo Román; A New QSPR Study on Relative Sweetness; IGI-Global; International Journal of Quantitative Structure-Property Relationships; 1; 1; 1-2016; 78-93
2379-7479
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.4018/IJQSPR.2016010104
info:eu-repo/semantics/altIdentifier/url/https://www.igi-global.com/gateway/article/144691
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IGI-Global
publisher.none.fl_str_mv IGI-Global
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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