IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Engenharia Química e Química |
Texto Completo: | https://periodicos.ufv.br/jcec/article/view/2483 |
Resumo: | AbstractIn silico study was carried on a dataset of 1,2,4-Triazole derivatives to investigate their activities behaviour on mycobacterium tuberculosis by utilizing Quantitative Structure-Activity Relationship (QSAR) technique. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the optimum descriptors and to generate the correlation QSAR model that relate their activities values against mycobacterium tuberculosis with the molecular structures of the inhibitors. The model was validated and was found to have squared correlation coefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 and Leave one out (LOO) cross validation coefficient (Qcv^2) value of 0.8231. The external validation set used for confirming the predictive power of the model has R2pred of 0.7482. Stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-mycobacterium tuberculosis activities |
id |
UFV-4_c1a66a764226a151b5d1ad35faa4ecfb |
---|---|
oai_identifier_str |
oai:ojs.periodicos.ufv.br:article/2483 |
network_acronym_str |
UFV-4 |
network_name_str |
Revista de Engenharia Química e Química |
repository_id_str |
|
spelling |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTSTuberculosis124-TriazoleQSARApplicability domainY-Randomization.AbstractIn silico study was carried on a dataset of 1,2,4-Triazole derivatives to investigate their activities behaviour on mycobacterium tuberculosis by utilizing Quantitative Structure-Activity Relationship (QSAR) technique. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the optimum descriptors and to generate the correlation QSAR model that relate their activities values against mycobacterium tuberculosis with the molecular structures of the inhibitors. The model was validated and was found to have squared correlation coefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 and Leave one out (LOO) cross validation coefficient (Qcv^2) value of 0.8231. The external validation set used for confirming the predictive power of the model has R2pred of 0.7482. Stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-mycobacterium tuberculosis activitiesUniversidade Federal de Viçosa - UFV2018-07-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/248310.18540/jcecvl4iss2pp0246-0254The Journal of Engineering and Exact Sciences; Vol. 4 No. 2 (2018); 0246-0254The Journal of Engineering and Exact Sciences; Vol. 4 Núm. 2 (2018); 0246-0254The Journal of Engineering and Exact Sciences; v. 4 n. 2 (2018); 0246-02542527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/2483/1039ADENIJI, SHOLA ELIJAHUba, SaniUzairu, Adamuinfo:eu-repo/semantics/openAccess2018-12-05T12:57:17Zoai:ojs.periodicos.ufv.br:article/2483Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2018-12-05T12:57:17Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false |
dc.title.none.fl_str_mv |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
title |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
spellingShingle |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS ADENIJI, SHOLA ELIJAH Tuberculosis 1 2 4-Triazole QSAR Applicability domain Y-Randomization. |
title_short |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
title_full |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
title_fullStr |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
title_full_unstemmed |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
title_sort |
IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS |
author |
ADENIJI, SHOLA ELIJAH |
author_facet |
ADENIJI, SHOLA ELIJAH Uba, Sani Uzairu, Adamu |
author_role |
author |
author2 |
Uba, Sani Uzairu, Adamu |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
ADENIJI, SHOLA ELIJAH Uba, Sani Uzairu, Adamu |
dc.subject.por.fl_str_mv |
Tuberculosis 1 2 4-Triazole QSAR Applicability domain Y-Randomization. |
topic |
Tuberculosis 1 2 4-Triazole QSAR Applicability domain Y-Randomization. |
description |
AbstractIn silico study was carried on a dataset of 1,2,4-Triazole derivatives to investigate their activities behaviour on mycobacterium tuberculosis by utilizing Quantitative Structure-Activity Relationship (QSAR) technique. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the optimum descriptors and to generate the correlation QSAR model that relate their activities values against mycobacterium tuberculosis with the molecular structures of the inhibitors. The model was validated and was found to have squared correlation coefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 and Leave one out (LOO) cross validation coefficient (Qcv^2) value of 0.8231. The external validation set used for confirming the predictive power of the model has R2pred of 0.7482. Stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-mycobacterium tuberculosis activities |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-04 |
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/2483 10.18540/jcecvl4iss2pp0246-0254 |
url |
https://periodicos.ufv.br/jcec/article/view/2483 |
identifier_str_mv |
10.18540/jcecvl4iss2pp0246-0254 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufv.br/jcec/article/view/2483/1039 |
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. 4 No. 2 (2018); 0246-0254 The Journal of Engineering and Exact Sciences; Vol. 4 Núm. 2 (2018); 0246-0254 The Journal of Engineering and Exact Sciences; v. 4 n. 2 (2018); 0246-0254 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_ |
1800211188197359616 |