IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.

Detalhes bibliográficos
Autor(a) principal: Ovaku, Momohjimoh Idris
Data de Publicação: 2020
Outros Autores: Abech, Stephen Eyije, 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/8629
Resumo: Abstract: The toxicity and high resistance to the commercially sold breast-cancer drugs have become more alarming and the demand to produce new and less toxic breast-cancer drugs arises. In silico studies was carried out on some quinoline derivatives to investigate their reported activities against breast cancer and thereby generate a model with a better activity against breast cancer. The chemical structures of the compounds were optimized using Spartan software at Density Functional Theory (DFT) level, utilizing the B3LYP/ 6-31G* basis set. Four QSAR models were generated using Multi-Linear Regression (MLR) and Genetic Function Approximation (GFA) method. Equation one was chosen as the best model based on the validation parameters. The validation parameters was found to be statistically signi?cant with square correlation coefficient (R2) of 0.9853, adjusted square correlation coef?cient ( ) of 0.9816, cross validation coefficient ( ) of 0.9727 and an external correlation coefficient square ( ) of 0.6649 was used to validate the model. The built model was a good and robust one for it passed the minimum requirement for generating a QSAR model.
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spelling IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.KeywordsQSAR modelmodel validationsBreast cancerquinoline derivatives.Abstract: The toxicity and high resistance to the commercially sold breast-cancer drugs have become more alarming and the demand to produce new and less toxic breast-cancer drugs arises. In silico studies was carried out on some quinoline derivatives to investigate their reported activities against breast cancer and thereby generate a model with a better activity against breast cancer. The chemical structures of the compounds were optimized using Spartan software at Density Functional Theory (DFT) level, utilizing the B3LYP/ 6-31G* basis set. Four QSAR models were generated using Multi-Linear Regression (MLR) and Genetic Function Approximation (GFA) method. Equation one was chosen as the best model based on the validation parameters. The validation parameters was found to be statistically signi?cant with square correlation coefficient (R2) of 0.9853, adjusted square correlation coef?cient ( ) of 0.9816, cross validation coefficient ( ) of 0.9727 and an external correlation coefficient square ( ) of 0.6649 was used to validate the model. The built model was a good and robust one for it passed the minimum requirement for generating a QSAR model.Universidade Federal de Viçosa - UFV2020-01-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/862910.18540/jcecvl6iss1pp0008-0014The Journal of Engineering and Exact Sciences; Vol. 6 No. 1 (2020); 0008-0014The Journal of Engineering and Exact Sciences; Vol. 6 Núm. 1 (2020); 0008-0014The Journal of Engineering and Exact Sciences; v. 6 n. 1 (2020); 0008-00142527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/8629/5227Ovaku, Momohjimoh IdrisAbech, Stephen EyijeShallangwa, Gideon AdamuUzairu, Adamuinfo:eu-repo/semantics/openAccess2021-02-23T20:11:47Zoai:ojs.periodicos.ufv.br:article/8629Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2021-02-23T20:11:47Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
title IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
spellingShingle IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
Ovaku, Momohjimoh Idris
Keywords
QSAR model
model validations
Breast cancer
quinoline derivatives.
title_short IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
title_full IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
title_fullStr IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
title_full_unstemmed IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
title_sort IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
author Ovaku, Momohjimoh Idris
author_facet Ovaku, Momohjimoh Idris
Abech, Stephen Eyije
Shallangwa, Gideon Adamu
Uzairu, Adamu
author_role author
author2 Abech, Stephen Eyije
Shallangwa, Gideon Adamu
Uzairu, Adamu
author2_role author
author
author
dc.contributor.author.fl_str_mv Ovaku, Momohjimoh Idris
Abech, Stephen Eyije
Shallangwa, Gideon Adamu
Uzairu, Adamu
dc.subject.por.fl_str_mv Keywords
QSAR model
model validations
Breast cancer
quinoline derivatives.
topic Keywords
QSAR model
model validations
Breast cancer
quinoline derivatives.
description Abstract: The toxicity and high resistance to the commercially sold breast-cancer drugs have become more alarming and the demand to produce new and less toxic breast-cancer drugs arises. In silico studies was carried out on some quinoline derivatives to investigate their reported activities against breast cancer and thereby generate a model with a better activity against breast cancer. The chemical structures of the compounds were optimized using Spartan software at Density Functional Theory (DFT) level, utilizing the B3LYP/ 6-31G* basis set. Four QSAR models were generated using Multi-Linear Regression (MLR) and Genetic Function Approximation (GFA) method. Equation one was chosen as the best model based on the validation parameters. The validation parameters was found to be statistically signi?cant with square correlation coefficient (R2) of 0.9853, adjusted square correlation coef?cient ( ) of 0.9816, cross validation coefficient ( ) of 0.9727 and an external correlation coefficient square ( ) of 0.6649 was used to validate the model. The built model was a good and robust one for it passed the minimum requirement for generating a QSAR model.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-03
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/8629
10.18540/jcecvl6iss1pp0008-0014
url https://periodicos.ufv.br/jcec/article/view/8629
identifier_str_mv 10.18540/jcecvl6iss1pp0008-0014
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/8629/5227
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. 6 No. 1 (2020); 0008-0014
The Journal of Engineering and Exact Sciences; Vol. 6 Núm. 1 (2020); 0008-0014
The Journal of Engineering and Exact Sciences; v. 6 n. 1 (2020); 0008-0014
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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