INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE

Detalhes bibliográficos
Autor(a) principal: Abdullahi, Mustapha
Data de Publicação: 2019
Outros Autores: Shallangwa, Gideon A., Ali, Tijjani, Uzairu, Adamu
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/3850
Resumo: Insulin modeling was performed on 28 C14-urea tetrandrine compounds as inhibitors of leukemic (HEL) cell lines using Quantitative Structure-Activity Relationship (QSAR) method. The structure of the inhibitors was correctly drawn, then geometrically optimized at Density Functional Theory (DFT) level (DFT / B3LYP / 6-31G *) with Spartan 14 V1.1.4. Also, molecular descriptors of the inhibitors were calculated with PaDEL calculator, and the results were partitioned into training and test set after data pretreatment. The training set was used to generate a model by employing genetic function approximation in choosing best descriptors to form the model. The validation parameters of the model include; R ^ 2 (train) at 0.8067, LOF 0.037 r ^ 2 (QCV) to 0.6378 R ^ 2 (test) 0.7629 of the CRP ^ 2 and  the  0. 6990 Which have passed the acceptance criteria for a QSAR model worldwide. In addition, the model depicted four (4) descriptors, AATS4v, AATS5i, AATSC5i, and GATS5m with positive meanings signifying that increase in these descriptors will positively influence and increase the activity of the inhibitors. This study depicts a route in designing and synthesizing new C14-urea tetrandrine compounds with better inhibitory potentials.
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spelling INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINEQSARMean EffectValidationDescriptorsModelY-randomizationInsulin modeling was performed on 28 C14-urea tetrandrine compounds as inhibitors of leukemic (HEL) cell lines using Quantitative Structure-Activity Relationship (QSAR) method. The structure of the inhibitors was correctly drawn, then geometrically optimized at Density Functional Theory (DFT) level (DFT / B3LYP / 6-31G *) with Spartan 14 V1.1.4. Also, molecular descriptors of the inhibitors were calculated with PaDEL calculator, and the results were partitioned into training and test set after data pretreatment. The training set was used to generate a model by employing genetic function approximation in choosing best descriptors to form the model. The validation parameters of the model include; R ^ 2 (train) at 0.8067, LOF 0.037 r ^ 2 (QCV) to 0.6378 R ^ 2 (test) 0.7629 of the CRP ^ 2 and  the  0. 6990 Which have passed the acceptance criteria for a QSAR model worldwide. In addition, the model depicted four (4) descriptors, AATS4v, AATS5i, AATSC5i, and GATS5m with positive meanings signifying that increase in these descriptors will positively influence and increase the activity of the inhibitors. This study depicts a route in designing and synthesizing new C14-urea tetrandrine compounds with better inhibitory potentials.Universidade Federal de Viçosa - UFV2019-03-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/385010.18540/jcecvl5iss1pp0063-0078The Journal of Engineering and Exact Sciences; Vol. 5 No. 1 (2019); 0063-0078The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 1 (2019); 0063-0078The Journal of Engineering and Exact Sciences; v. 5 n. 1 (2019); 0063-00782527-1075reponame:The Journal of Engineering and Exact Sciencesinstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/3850/3254Abdullahi, MustaphaShallangwa, Gideon A.Ali, TijjaniUzairu, Adamuinfo:eu-repo/semantics/openAccess2019-04-12T14:38:21Zoai:ojs.periodicos.ufv.br:article/3850Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/oai2527-10752527-1075opendoar:2019-04-12T14:38:21The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
title INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
spellingShingle INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
Abdullahi, Mustapha
QSAR
Mean Effect
Validation
Descriptors
Model
Y-randomization
title_short INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
title_full INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
title_fullStr INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
title_full_unstemmed INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
title_sort INSILICO MODELLING ON SOME C14-UREA TETRANDRINE COMPOUNDS AS POTENT ANTI-CANCER AGAINST HUMAN ERYTHROLEUKEMIA (HEL) CELL LINE
author Abdullahi, Mustapha
author_facet Abdullahi, Mustapha
Shallangwa, Gideon A.
Ali, Tijjani
Uzairu, Adamu
author_role author
author2 Shallangwa, Gideon A.
Ali, Tijjani
Uzairu, Adamu
author2_role author
author
author
dc.contributor.author.fl_str_mv Abdullahi, Mustapha
Shallangwa, Gideon A.
Ali, Tijjani
Uzairu, Adamu
dc.subject.por.fl_str_mv QSAR
Mean Effect
Validation
Descriptors
Model
Y-randomization
topic QSAR
Mean Effect
Validation
Descriptors
Model
Y-randomization
description Insulin modeling was performed on 28 C14-urea tetrandrine compounds as inhibitors of leukemic (HEL) cell lines using Quantitative Structure-Activity Relationship (QSAR) method. The structure of the inhibitors was correctly drawn, then geometrically optimized at Density Functional Theory (DFT) level (DFT / B3LYP / 6-31G *) with Spartan 14 V1.1.4. Also, molecular descriptors of the inhibitors were calculated with PaDEL calculator, and the results were partitioned into training and test set after data pretreatment. The training set was used to generate a model by employing genetic function approximation in choosing best descriptors to form the model. The validation parameters of the model include; R ^ 2 (train) at 0.8067, LOF 0.037 r ^ 2 (QCV) to 0.6378 R ^ 2 (test) 0.7629 of the CRP ^ 2 and  the  0. 6990 Which have passed the acceptance criteria for a QSAR model worldwide. In addition, the model depicted four (4) descriptors, AATS4v, AATS5i, AATSC5i, and GATS5m with positive meanings signifying that increase in these descriptors will positively influence and increase the activity of the inhibitors. This study depicts a route in designing and synthesizing new C14-urea tetrandrine compounds with better inhibitory potentials.
publishDate 2019
dc.date.none.fl_str_mv 2019-03-08
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/3850
10.18540/jcecvl5iss1pp0063-0078
url https://periodicos.ufv.br/jcec/article/view/3850
identifier_str_mv 10.18540/jcecvl5iss1pp0063-0078
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/3850/3254
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. 1 (2019); 0063-0078
The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 1 (2019); 0063-0078
The Journal of Engineering and Exact Sciences; v. 5 n. 1 (2019); 0063-0078
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
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