QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Engenharia Química e Química |
DOI: | 10.18540/jcecvl5iss3pp0257-0270 |
Texto Completo: | https://periodicos.ufv.br/jcec/article/view/8019 |
Resumo: | QSAR modelling and docking studies on 45 thiazole analogues were carried out. The studied compounds in this research were optimized adopting DFT method at B3LYP function with a 6-31G* basis set. The QSAR models were generated in material studio by MLR analysis (GFA method). Based on its statistical fitness, the first model was selected and chosen as the studied model and assessed with R2 = 0.906134, R2 adj = 0.89049, Q2cv = 0.86149 and R2 pred = 0.82581. The ligand with the highest binding energy of -11.0 kcal/mol among the other ligands was ligand 13 as indicated by the molecular docking. The standard drug (acarbose) was also docked to the binding pocket of alfa-glucosidase with -9.5kcal/mole docking score. The most active compound was found to be better than standard drug. The outcome of this findings paved way for predicting novel ?-glucosidase inhibitors having improved potency toward the target enzyme. |
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Revista de Engenharia Química e Química |
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QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitorsQSARMolecular modellingdockingDiabetesQSAR modelling and docking studies on 45 thiazole analogues were carried out. The studied compounds in this research were optimized adopting DFT method at B3LYP function with a 6-31G* basis set. The QSAR models were generated in material studio by MLR analysis (GFA method). Based on its statistical fitness, the first model was selected and chosen as the studied model and assessed with R2 = 0.906134, R2 adj = 0.89049, Q2cv = 0.86149 and R2 pred = 0.82581. The ligand with the highest binding energy of -11.0 kcal/mol among the other ligands was ligand 13 as indicated by the molecular docking. The standard drug (acarbose) was also docked to the binding pocket of alfa-glucosidase with -9.5kcal/mole docking score. The most active compound was found to be better than standard drug. The outcome of this findings paved way for predicting novel ?-glucosidase inhibitors having improved potency toward the target enzyme.Universidade Federal de Viçosa - UFV2019-06-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/801910.18540/jcecvl5iss3pp0257-0270The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0257-0270The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0257-0270The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0257-02702527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/8019/3403Copyright (c) 2019 The Journal of Engineering and Exact Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessIbrahim, Muhammad TukurUzairu, AdamuShallangwa, Gideon AdamuUba, Sani2021-11-03T12:25:21Zoai:ojs.periodicos.ufv.br:article/8019Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2021-11-03T12:25:21Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false |
dc.title.none.fl_str_mv |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
title |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
spellingShingle |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors Ibrahim, Muhammad Tukur QSAR Molecular modelling docking Diabetes Ibrahim, Muhammad Tukur QSAR Molecular modelling docking Diabetes |
title_short |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
title_full |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
title_fullStr |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
title_full_unstemmed |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
title_sort |
QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors |
author |
Ibrahim, Muhammad Tukur |
author_facet |
Ibrahim, Muhammad Tukur Ibrahim, Muhammad Tukur Uzairu, Adamu Shallangwa, Gideon Adamu Uba, Sani Uzairu, Adamu Shallangwa, Gideon Adamu Uba, Sani |
author_role |
author |
author2 |
Uzairu, Adamu Shallangwa, Gideon Adamu Uba, Sani |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Ibrahim, Muhammad Tukur Uzairu, Adamu Shallangwa, Gideon Adamu Uba, Sani |
dc.subject.por.fl_str_mv |
QSAR Molecular modelling docking Diabetes |
topic |
QSAR Molecular modelling docking Diabetes |
description |
QSAR modelling and docking studies on 45 thiazole analogues were carried out. The studied compounds in this research were optimized adopting DFT method at B3LYP function with a 6-31G* basis set. The QSAR models were generated in material studio by MLR analysis (GFA method). Based on its statistical fitness, the first model was selected and chosen as the studied model and assessed with R2 = 0.906134, R2 adj = 0.89049, Q2cv = 0.86149 and R2 pred = 0.82581. The ligand with the highest binding energy of -11.0 kcal/mol among the other ligands was ligand 13 as indicated by the molecular docking. The standard drug (acarbose) was also docked to the binding pocket of alfa-glucosidase with -9.5kcal/mole docking score. The most active compound was found to be better than standard drug. The outcome of this findings paved way for predicting novel ?-glucosidase inhibitors having improved potency toward the target enzyme. |
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/8019 10.18540/jcecvl5iss3pp0257-0270 |
url |
https://periodicos.ufv.br/jcec/article/view/8019 |
identifier_str_mv |
10.18540/jcecvl5iss3pp0257-0270 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufv.br/jcec/article/view/8019/3403 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 The Journal of Engineering and Exact Sciences https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 The Journal of Engineering and Exact Sciences https://creativecommons.org/licenses/by/4.0 |
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); 0257-0270 The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0257-0270 The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0257-0270 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 |
_version_ |
1822180720601202688 |
dc.identifier.doi.none.fl_str_mv |
10.18540/jcecvl5iss3pp0257-0270 |