New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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=S0103-50532016000901636 |
Resumo: | The peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that acts as a transcription factor, regulating glucose, lipid and inflammation signaling and it is exploited in type 2 diabetes treatment. However, the selective activation of this PPAR subtype has been linked to important adverse effects which can be mitigated through concomitant activation of PPARα and PPARδ. In this study, we proposed new PPARγ agonists using PharmaGist Server for pharmacophore prediction, the molecular docking was performed by GOLD (genetic optimization for ligand docking) v2.2, AutoDock 4.2 and AutoDock Vina 1.1 and QikProp v4.0 and Derek for absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment. One molecule showed high predicted affinity to PPARγ and favorable pharmacokinetic and toxicity properties. It was then evaluated against PPARα and PPARδ and showed greater affinity to these receptors than the controls. Therefore this molecule is a promising drug lead for the development of derivatives and for the treatment of metabolic syndrome with the benefits of a PPAR pan activation. |
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New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methodstype 2 diabetesPPAR pan agonistmolecular modelingADMET predictionThe peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that acts as a transcription factor, regulating glucose, lipid and inflammation signaling and it is exploited in type 2 diabetes treatment. However, the selective activation of this PPAR subtype has been linked to important adverse effects which can be mitigated through concomitant activation of PPARα and PPARδ. In this study, we proposed new PPARγ agonists using PharmaGist Server for pharmacophore prediction, the molecular docking was performed by GOLD (genetic optimization for ligand docking) v2.2, AutoDock 4.2 and AutoDock Vina 1.1 and QikProp v4.0 and Derek for absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment. One molecule showed high predicted affinity to PPARγ and favorable pharmacokinetic and toxicity properties. It was then evaluated against PPARα and PPARδ and showed greater affinity to these receptors than the controls. Therefore this molecule is a promising drug lead for the development of derivatives and for the treatment of metabolic syndrome with the benefits of a PPAR pan activation.Sociedade Brasileira de Química2016-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532016000901636Journal of the Brazilian Chemical Society v.27 n.9 2016reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.5935/0103-5053.20160043info:eu-repo/semantics/openAccessPadilha,Elias C.Serafim,Rodolfo B.Sarmiento,Deisy Y. R.Santos,César F.Santos,Cleydson B. R.Silva,Carlos H. T. P.eng2016-09-14T00:00:00Zoai:scielo:S0103-50532016000901636Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2016-09-14T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
title |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
spellingShingle |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods Padilha,Elias C. type 2 diabetes PPAR pan agonist molecular modeling ADMET prediction |
title_short |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
title_full |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
title_fullStr |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
title_full_unstemmed |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
title_sort |
New PPARα/γ/δ Optimal Activator Rationally Designed by Computational Methods |
author |
Padilha,Elias C. |
author_facet |
Padilha,Elias C. Serafim,Rodolfo B. Sarmiento,Deisy Y. R. Santos,César F. Santos,Cleydson B. R. Silva,Carlos H. T. P. |
author_role |
author |
author2 |
Serafim,Rodolfo B. Sarmiento,Deisy Y. R. Santos,César F. Santos,Cleydson B. R. Silva,Carlos H. T. P. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Padilha,Elias C. Serafim,Rodolfo B. Sarmiento,Deisy Y. R. Santos,César F. Santos,Cleydson B. R. Silva,Carlos H. T. P. |
dc.subject.por.fl_str_mv |
type 2 diabetes PPAR pan agonist molecular modeling ADMET prediction |
topic |
type 2 diabetes PPAR pan agonist molecular modeling ADMET prediction |
description |
The peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that acts as a transcription factor, regulating glucose, lipid and inflammation signaling and it is exploited in type 2 diabetes treatment. However, the selective activation of this PPAR subtype has been linked to important adverse effects which can be mitigated through concomitant activation of PPARα and PPARδ. In this study, we proposed new PPARγ agonists using PharmaGist Server for pharmacophore prediction, the molecular docking was performed by GOLD (genetic optimization for ligand docking) v2.2, AutoDock 4.2 and AutoDock Vina 1.1 and QikProp v4.0 and Derek for absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment. One molecule showed high predicted affinity to PPARγ and favorable pharmacokinetic and toxicity properties. It was then evaluated against PPARα and PPARδ and showed greater affinity to these receptors than the controls. Therefore this molecule is a promising drug lead for the development of derivatives and for the treatment of metabolic syndrome with the benefits of a PPAR pan activation. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-09-01 |
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=S0103-50532016000901636 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532016000901636 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5935/0103-5053.20160043 |
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.27 n.9 2016 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_ |
1750318178726051840 |