A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector
- Autores
- Saavedra Reyes, Laura Marcela; Romanelli, Gustavo Pablo; Duchowicz, Pablo Román
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- A set of 263 plant-derived compounds with larvicidal activity against Aedes aegypti L. (Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non-conformational quantitative structure-activity relationships (QSAR) approach. The balanced subsets method (BSM) is employed to split the complete dataset into training, validation and test sets. From 26,775 freely available molecular descriptors, the most relevant structural features of compounds affecting the bioactivity are taken. The molecular descriptors are calculated through four different freewares, such as PaDEL, Mold², EPI Suite and QuBiLs-MAS. The replacement method (RM) variable subset selection technique leads to the best linear regression models. A successful QSAR equation involves 7-conformation-independent molecular descriptors, fulfiling the evaluated internal (loo, l30‰, VIF and Y-randomization) and external (test set with Ntest = 65 compounds) validation criteria. The practical application of this QSAR model reveals promising predicted values for some natural compounds with unknown experimental larvicidal activity. Therefore, the present model constitutes the first one based on a large molecular set, being a useful computational tool for identifying and guiding the synthesis of new active molecules inspired by natural products.
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
Centro de Investigación y Desarrollo en Ciencias Aplicadas
Facultad de Ciencias Agrarias y Forestales - Materia
-
Ciencias Exactas
Química
QSAR analysis
MLR method
Larvicidal activity
Aedes aegypti vector
Freeware - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/136686
Ver los metadatos del registro completo
id |
SEDICI_4f7c4b87e4827c5a3cd922149e8a66ab |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/136686 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
spelling |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vectorSaavedra Reyes, Laura MarcelaRomanelli, Gustavo PabloDuchowicz, Pablo RománCiencias ExactasQuímicaQSAR analysisMLR methodLarvicidal activityAedes aegypti vectorFreewareA set of 263 plant-derived compounds with larvicidal activity against <i>Aedes aegypti</i> L. (Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non-conformational quantitative structure-activity relationships (QSAR) approach. The balanced subsets method (BSM) is employed to split the complete dataset into training, validation and test sets. From 26,775 freely available molecular descriptors, the most relevant structural features of compounds affecting the bioactivity are taken. The molecular descriptors are calculated through four different freewares, such as PaDEL, Mold², EPI Suite and QuBiLs-MAS. The replacement method (RM) variable subset selection technique leads to the best linear regression models. A successful QSAR equation involves 7-conformation-independent molecular descriptors, fulfiling the evaluated internal (loo, l30‰, VIF and Y-randomization) and external (test set with N<sub>test</sub> = 65 compounds) validation criteria. The practical application of this QSAR model reveals promising predicted values for some natural compounds with unknown experimental larvicidal activity. Therefore, the present model constitutes the first one based on a large molecular set, being a useful computational tool for identifying and guiding the synthesis of new active molecules inspired by natural products.Instituto de Investigaciones Fisicoquímicas Teóricas y AplicadasCentro de Investigación y Desarrollo en Ciencias AplicadasFacultad de Ciencias Agrarias y Forestales2020-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf6205-6214http://sedici.unlp.edu.ar/handle/10915/136686enginfo:eu-repo/semantics/altIdentifier/issn/1614-7499info:eu-repo/semantics/altIdentifier/issn/0944-1344info:eu-repo/semantics/altIdentifier/doi/10.1007/s11356-019-06630-9info:eu-repo/semantics/altIdentifier/pmid/31865579info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:02Zoai:sedici.unlp.edu.ar:10915/136686Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:02.346SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
title |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
spellingShingle |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector Saavedra Reyes, Laura Marcela Ciencias Exactas Química QSAR analysis MLR method Larvicidal activity Aedes aegypti vector Freeware |
title_short |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
title_full |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
title_fullStr |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
title_full_unstemmed |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
title_sort |
A non-conformational QSAR study for plant-derived larvicides against Zika <i>Aedes aegypti</i> L. vector |
dc.creator.none.fl_str_mv |
Saavedra Reyes, Laura Marcela Romanelli, Gustavo Pablo Duchowicz, Pablo Román |
author |
Saavedra Reyes, Laura Marcela |
author_facet |
Saavedra Reyes, Laura Marcela Romanelli, Gustavo Pablo Duchowicz, Pablo Román |
author_role |
author |
author2 |
Romanelli, Gustavo Pablo Duchowicz, Pablo Román |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Exactas Química QSAR analysis MLR method Larvicidal activity Aedes aegypti vector Freeware |
topic |
Ciencias Exactas Química QSAR analysis MLR method Larvicidal activity Aedes aegypti vector Freeware |
dc.description.none.fl_txt_mv |
A set of 263 plant-derived compounds with larvicidal activity against <i>Aedes aegypti</i> L. (Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non-conformational quantitative structure-activity relationships (QSAR) approach. The balanced subsets method (BSM) is employed to split the complete dataset into training, validation and test sets. From 26,775 freely available molecular descriptors, the most relevant structural features of compounds affecting the bioactivity are taken. The molecular descriptors are calculated through four different freewares, such as PaDEL, Mold², EPI Suite and QuBiLs-MAS. The replacement method (RM) variable subset selection technique leads to the best linear regression models. A successful QSAR equation involves 7-conformation-independent molecular descriptors, fulfiling the evaluated internal (loo, l30‰, VIF and Y-randomization) and external (test set with N<sub>test</sub> = 65 compounds) validation criteria. The practical application of this QSAR model reveals promising predicted values for some natural compounds with unknown experimental larvicidal activity. Therefore, the present model constitutes the first one based on a large molecular set, being a useful computational tool for identifying and guiding the synthesis of new active molecules inspired by natural products. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas Centro de Investigación y Desarrollo en Ciencias Aplicadas Facultad de Ciencias Agrarias y Forestales |
description |
A set of 263 plant-derived compounds with larvicidal activity against <i>Aedes aegypti</i> L. (Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non-conformational quantitative structure-activity relationships (QSAR) approach. The balanced subsets method (BSM) is employed to split the complete dataset into training, validation and test sets. From 26,775 freely available molecular descriptors, the most relevant structural features of compounds affecting the bioactivity are taken. The molecular descriptors are calculated through four different freewares, such as PaDEL, Mold², EPI Suite and QuBiLs-MAS. The replacement method (RM) variable subset selection technique leads to the best linear regression models. A successful QSAR equation involves 7-conformation-independent molecular descriptors, fulfiling the evaluated internal (loo, l30‰, VIF and Y-randomization) and external (test set with N<sub>test</sub> = 65 compounds) validation criteria. The practical application of this QSAR model reveals promising predicted values for some natural compounds with unknown experimental larvicidal activity. Therefore, the present model constitutes the first one based on a large molecular set, being a useful computational tool for identifying and guiding the synthesis of new active molecules inspired by natural products. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-02 |
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/10915/136686 |
url |
http://sedici.unlp.edu.ar/handle/10915/136686 |
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/issn/0944-1344 info:eu-repo/semantics/altIdentifier/doi/10.1007/s11356-019-06630-9 info:eu-repo/semantics/altIdentifier/pmid/31865579 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
dc.format.none.fl_str_mv |
application/pdf 6205-6214 |
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 |
_version_ |
1844616199881621504 |
score |
13.070432 |