QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES

Detalhes bibliográficos
Autor(a) principal: Isyaku, Yusuf
Data de Publicação: 2019
Outros Autores: Uzairu, Adamu, Uba, Sani
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/8348
Resumo: An insilico study was carried out on a series of thirty five (35) sulfonyl-containing compounds for their antifungal activities against Botrytis Cinerea fungi by the employment of Quantitative Structure-Activity Relationship (QSAR) techniques. Spartan 14 software was used to generate the molecular structure of the dataset which were then optimized using Density Function Techniques (DFT/B3LYP/6-31G*) quantum method found available in the software. PaDEL-Descriptor software was used to calculate the molecular descriptors. The calculated descriptors were then subjected to data-Pretreatment and later divided into training and test sets. The training set was used to generate the model while the test set was to validate the built model. The model was developed using Genetic Function Algorithm (GFA). Out of the four models developed, model 1 was selected as the optimum model with good statistical parameters; R2 = 0.954, R2adj =0.941, cross validation R2/ Q2cv = 0.888 and R2pred = 0.839. The model proposed was found to be stable, robust and showed a good internal and external validation. Other statistical analysis such as mean effect, variance inflation factor (VIF), Williams plot among others were also carried out for the applicability domain of the model.
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spelling QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDESQSAR 2-substituted Sulfonamides FungicidesAn insilico study was carried out on a series of thirty five (35) sulfonyl-containing compounds for their antifungal activities against Botrytis Cinerea fungi by the employment of Quantitative Structure-Activity Relationship (QSAR) techniques. Spartan 14 software was used to generate the molecular structure of the dataset which were then optimized using Density Function Techniques (DFT/B3LYP/6-31G*) quantum method found available in the software. PaDEL-Descriptor software was used to calculate the molecular descriptors. The calculated descriptors were then subjected to data-Pretreatment and later divided into training and test sets. The training set was used to generate the model while the test set was to validate the built model. The model was developed using Genetic Function Algorithm (GFA). Out of the four models developed, model 1 was selected as the optimum model with good statistical parameters; R2 = 0.954, R2adj =0.941, cross validation R2/ Q2cv = 0.888 and R2pred = 0.839. The model proposed was found to be stable, robust and showed a good internal and external validation. Other statistical analysis such as mean effect, variance inflation factor (VIF), Williams plot among others were also carried out for the applicability domain of the model.Universidade Federal de Viçosa - UFV2019-06-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/834810.18540/jcecvl5iss3pp0283-0290The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0283-0290The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0283-0290The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0283-02902527-1075reponame:The Journal of Engineering and Exact Sciencesinstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/8348/3509Isyaku, YusufUzairu, AdamuUba, Saniinfo:eu-repo/semantics/openAccess2019-08-14T20:37:03Zoai:ojs.periodicos.ufv.br:article/8348Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/oai2527-10752527-1075opendoar:2019-08-14T20:37:03The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
title QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
spellingShingle QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
Isyaku, Yusuf
QSAR 2-substituted Sulfonamides Fungicides
title_short QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
title_full QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
title_fullStr QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
title_full_unstemmed QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
title_sort QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES
author Isyaku, Yusuf
author_facet Isyaku, Yusuf
Uzairu, Adamu
Uba, Sani
author_role author
author2 Uzairu, Adamu
Uba, Sani
author2_role author
author
dc.contributor.author.fl_str_mv Isyaku, Yusuf
Uzairu, Adamu
Uba, Sani
dc.subject.por.fl_str_mv QSAR 2-substituted Sulfonamides Fungicides
topic QSAR 2-substituted Sulfonamides Fungicides
description An insilico study was carried out on a series of thirty five (35) sulfonyl-containing compounds for their antifungal activities against Botrytis Cinerea fungi by the employment of Quantitative Structure-Activity Relationship (QSAR) techniques. Spartan 14 software was used to generate the molecular structure of the dataset which were then optimized using Density Function Techniques (DFT/B3LYP/6-31G*) quantum method found available in the software. PaDEL-Descriptor software was used to calculate the molecular descriptors. The calculated descriptors were then subjected to data-Pretreatment and later divided into training and test sets. The training set was used to generate the model while the test set was to validate the built model. The model was developed using Genetic Function Algorithm (GFA). Out of the four models developed, model 1 was selected as the optimum model with good statistical parameters; R2 = 0.954, R2adj =0.941, cross validation R2/ Q2cv = 0.888 and R2pred = 0.839. The model proposed was found to be stable, robust and showed a good internal and external validation. Other statistical analysis such as mean effect, variance inflation factor (VIF), Williams plot among others were also carried out for the applicability domain of the model.
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/8348
10.18540/jcecvl5iss3pp0283-0290
url https://periodicos.ufv.br/jcec/article/view/8348
identifier_str_mv 10.18540/jcecvl5iss3pp0283-0290
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/8348/3509
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. 3 (2019); 0283-0290
The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0283-0290
The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0283-0290
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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