QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds

Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative st...

Full description

Autores:
Cabrera, Nicolas
Mora, Jose R
Márquez, E.
Flores-Morales, Virginia
Calle, L.
Cortés, E.
Tipo de recurso:
http://purl.org/coar/resource_type/c_816b
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7618
Acceso en línea:
https://hdl.handle.net/11323/7618
https://doi.org/10.1080/1062936X.2020.1848914
https://repositorio.cuc.edu.co/
Palabra clave:
Leishmaniasis
QSAR
Docking analysis
Protozoan parasites
Organic selenium compounds
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_20d8dd3df95f94fa3ca092a24e0316ac
oai_identifier_str oai:repositorio.cuc.edu.co:11323/7618
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
title QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
spellingShingle QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
Leishmaniasis
QSAR
Docking analysis
Protozoan parasites
Organic selenium compounds
title_short QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
title_full QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
title_fullStr QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
title_full_unstemmed QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
title_sort QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds
dc.creator.fl_str_mv Cabrera, Nicolas
Mora, Jose R
Márquez, E.
Flores-Morales, Virginia
Calle, L.
Cortés, E.
dc.contributor.author.spa.fl_str_mv Cabrera, Nicolas
Mora, Jose R
Márquez, E.
Flores-Morales, Virginia
Calle, L.
Cortés, E.
dc.subject.spa.fl_str_mv Leishmaniasis
QSAR
Docking analysis
Protozoan parasites
Organic selenium compounds
topic Leishmaniasis
QSAR
Docking analysis
Protozoan parasites
Organic selenium compounds
description Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative structure-activity relationship (QSAR) analysis. The antileishmanial activity was measured by L. donovani β carbonic anhydrase inhibition (Ki) and the half-maximal inhibitory concentration (IC50) against L. infantum amastigotes. The dataset was divided into training (75%) and test sets (25%) by using a k-means clustering algorithm. For pKi prediction, model M3 with seven 3D topographic descriptors was characterized by the following statistical parameters: r 2 = 0.879, Q 2 LOO = 0.822, and Q 2 ext = 0.840. For pIC50 prediction, model M12 with six attributes was characterized by the following statistical parameters: r 2 = 0.907, Q 2 LOO = 0.824, and Q 2 ext = 0.795. Both models met all the requirements of Tropsha´s test, which implies predictions of pIC50 and pKi activities with high accuracy. Concomitantly, favourable interactions of the sulphonamide group with the Zn atom in the protein were revealed by the docking analysis.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-12-21T19:11:21Z
dc.date.available.none.fl_str_mv 2020-12-21T19:11:21Z
dc.date.issued.none.fl_str_mv 2020-11-26
dc.date.embargoEnd.none.fl_str_mv 2021-11-30
dc.type.spa.fl_str_mv Pre-Publicación
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_816b
dc.type.content.spa.fl_str_mv Text
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dc.identifier.issn.spa.fl_str_mv 1029-046X
1062-936X
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/7618
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1080/1062936X.2020.1848914
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 1029-046X
1062-936X
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/7618
https://doi.org/10.1080/1062936X.2020.1848914
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.rights.spa.fl_str_mv CC0 1.0 Universal
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dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
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rights_invalid_str_mv CC0 1.0 Universal
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eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Corporación Universidad de la Costa
dc.source.spa.fl_str_mv SAR and QSAR in Environmental Research
institution Corporación Universidad de la Costa
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spelling Cabrera, NicolasMora, Jose RMárquez, E.Flores-Morales, VirginiaCalle, L.Cortés, E.2020-12-21T19:11:21Z2020-12-21T19:11:21Z2020-11-262021-11-301029-046X1062-936Xhttps://hdl.handle.net/11323/7618https://doi.org/10.1080/1062936X.2020.1848914Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative structure-activity relationship (QSAR) analysis. The antileishmanial activity was measured by L. donovani β carbonic anhydrase inhibition (Ki) and the half-maximal inhibitory concentration (IC50) against L. infantum amastigotes. The dataset was divided into training (75%) and test sets (25%) by using a k-means clustering algorithm. For pKi prediction, model M3 with seven 3D topographic descriptors was characterized by the following statistical parameters: r 2 = 0.879, Q 2 LOO = 0.822, and Q 2 ext = 0.840. For pIC50 prediction, model M12 with six attributes was characterized by the following statistical parameters: r 2 = 0.907, Q 2 LOO = 0.824, and Q 2 ext = 0.795. Both models met all the requirements of Tropsha´s test, which implies predictions of pIC50 and pKi activities with high accuracy. 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