QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT

Detalhes bibliográficos
Autor(a) principal: Mahmud, Aliyu Wappah
Data de Publicação: 2019
Outros Autores: Shallangwa, Gideon Adamu, Uzairu, Adamu
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista de Engenharia Química e Química
Texto Completo: https://periodicos.ufv.br/jcec/article/view/8010
Resumo: Quantitative structure–activity relationships (QSAR) has been a reliable study in the development of models that predict biological activities of chemical substances based on their structures for the development of novel chemical entities. This  study was carried out on 44 compounds of 4-amidinoquinoline and 10-amidinobenzonaphthyridine derivatives to develop a model that relates their structures to their activities against Plasmodium falciparum. Density Functional Theory (DFT) with basis set B3LYP/6-31G? was used to optimize the compounds. Genetic Function Algorithm (GFA) was employed in selecting descriptors and building the model. Four models were generated and the model with best internal and external validation has internal squared correlation coefficient (
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spelling QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENTQSARAntimalariaPlasmodium falciparum and 4-AmidinoquinolineQuantitative structure–activity relationships (QSAR) has been a reliable study in the development of models that predict biological activities of chemical substances based on their structures for the development of novel chemical entities. This  study was carried out on 44 compounds of 4-amidinoquinoline and 10-amidinobenzonaphthyridine derivatives to develop a model that relates their structures to their activities against Plasmodium falciparum. Density Functional Theory (DFT) with basis set B3LYP/6-31G? was used to optimize the compounds. Genetic Function Algorithm (GFA) was employed in selecting descriptors and building the model. Four models were generated and the model with best internal and external validation has internal squared correlation coefficient (Universidade Federal de Viçosa - UFV2019-06-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/801010.18540/jcecvl5iss3pp0271-0282The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0271-0282The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0271-0282The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0271-02822527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/8010/3406Mahmud, Aliyu WappahShallangwa, Gideon AdamuUzairu, Adamuinfo:eu-repo/semantics/openAccess2019-08-14T20:37:03Zoai:ojs.periodicos.ufv.br:article/8010Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2019-08-14T20:37:03Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
title QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
spellingShingle QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
Mahmud, Aliyu Wappah
QSAR
Antimalaria
Plasmodium falciparum and 4-Amidinoquinoline
title_short QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
title_full QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
title_fullStr QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
title_full_unstemmed QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
title_sort QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT
author Mahmud, Aliyu Wappah
author_facet Mahmud, Aliyu Wappah
Shallangwa, Gideon Adamu
Uzairu, Adamu
author_role author
author2 Shallangwa, Gideon Adamu
Uzairu, Adamu
author2_role author
author
dc.contributor.author.fl_str_mv Mahmud, Aliyu Wappah
Shallangwa, Gideon Adamu
Uzairu, Adamu
dc.subject.por.fl_str_mv QSAR
Antimalaria
Plasmodium falciparum and 4-Amidinoquinoline
topic QSAR
Antimalaria
Plasmodium falciparum and 4-Amidinoquinoline
description Quantitative structure–activity relationships (QSAR) has been a reliable study in the development of models that predict biological activities of chemical substances based on their structures for the development of novel chemical entities. This  study was carried out on 44 compounds of 4-amidinoquinoline and 10-amidinobenzonaphthyridine derivatives to develop a model that relates their structures to their activities against Plasmodium falciparum. Density Functional Theory (DFT) with basis set B3LYP/6-31G? was used to optimize the compounds. Genetic Function Algorithm (GFA) was employed in selecting descriptors and building the model. Four models were generated and the model with best internal and external validation has internal squared correlation coefficient (
publishDate 2019
dc.date.none.fl_str_mv 2019-06-28
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/jcec/article/view/8010
10.18540/jcecvl5iss3pp0271-0282
url https://periodicos.ufv.br/jcec/article/view/8010
identifier_str_mv 10.18540/jcecvl5iss3pp0271-0282
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/8010/3406
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0271-0282
The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0271-0282
The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0271-0282
2527-1075
reponame:Revista de Engenharia Química e Química
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str Revista de Engenharia Química e Química
collection Revista de Engenharia Química e Química
repository.name.fl_str_mv Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv jcec.journal@ufv.br||req2@ufv.br
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