IN SILICO ELUCIDATION OF SOME QUINOLINE DERIVATIVES WITH POTENT ANTI-BREAST CANCER ACTIVITIES.
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | The Journal of Engineering and Exact Sciences |
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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oai:ojs.periodicos.ufv.br:article/8629 |
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UFV-6 |
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The Journal of Engineering and Exact Sciences |
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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:The Journal of Engineering and Exact Sciencesinstname: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/oai2527-10752527-1075opendoar:2021-02-23T20:11:47The Journal of Engineering and Exact Sciences - 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:The Journal of Engineering and Exact Sciences instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
The Journal of Engineering and Exact Sciences |
collection |
The Journal of Engineering and Exact Sciences |
repository.name.fl_str_mv |
The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV) |
repository.mail.fl_str_mv |
|
_version_ |
1808845245187620864 |