Structure-based drug design studies on a series of aldolase inhibitors
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Chemical Society (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000200005 |
Resumo: | Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl-glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r² = 0.95, non-cross-validated correlation coefficient, and q² = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set, and the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme. |
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Structure-based drug design studies on a series of aldolase inhibitorsAfrican trypanosomiasisdrugdesigninhibitorsQSARmolecular modelingHuman African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl-glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r² = 0.95, non-cross-validated correlation coefficient, and q² = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set, and the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.Sociedade Brasileira de Química2013-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000200005Journal of the Brazilian Chemical Society v.24 n.2 2013reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.5935/0103-5053.20130026info:eu-repo/semantics/openAccessFerreira,Leonardo G.Santos,Ricardo N. dosAndricopulo,Adriano D.eng2013-05-20T00:00:00Zoai:scielo:S0103-50532013000200005Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2013-05-20T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
Structure-based drug design studies on a series of aldolase inhibitors |
title |
Structure-based drug design studies on a series of aldolase inhibitors |
spellingShingle |
Structure-based drug design studies on a series of aldolase inhibitors Ferreira,Leonardo G. African trypanosomiasis drug design inhibitors QSAR molecular modeling |
title_short |
Structure-based drug design studies on a series of aldolase inhibitors |
title_full |
Structure-based drug design studies on a series of aldolase inhibitors |
title_fullStr |
Structure-based drug design studies on a series of aldolase inhibitors |
title_full_unstemmed |
Structure-based drug design studies on a series of aldolase inhibitors |
title_sort |
Structure-based drug design studies on a series of aldolase inhibitors |
author |
Ferreira,Leonardo G. |
author_facet |
Ferreira,Leonardo G. Santos,Ricardo N. dos Andricopulo,Adriano D. |
author_role |
author |
author2 |
Santos,Ricardo N. dos Andricopulo,Adriano D. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ferreira,Leonardo G. Santos,Ricardo N. dos Andricopulo,Adriano D. |
dc.subject.por.fl_str_mv |
African trypanosomiasis drug design inhibitors QSAR molecular modeling |
topic |
African trypanosomiasis drug design inhibitors QSAR molecular modeling |
description |
Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl-glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r² = 0.95, non-cross-validated correlation coefficient, and q² = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set, and the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-02-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000200005 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000200005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5935/0103-5053.20130026 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Journal of the Brazilian Chemical Society v.24 n.2 2013 reponame:Journal of the Brazilian Chemical Society (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Journal of the Brazilian Chemical Society (Online) |
collection |
Journal of the Brazilian Chemical Society (Online) |
repository.name.fl_str_mv |
Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
||office@jbcs.sbq.org.br |
_version_ |
1750318174460444672 |