Cargando…

Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity

BACKGROUND: Natural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and the...

Descripción completa

Detalles Bibliográficos
Autores principales: Guasch, Laura, Sala, Esther, Mulero, Miquel, Valls, Cristina, Salvadó, Maria Josepa, Pujadas, Gerard, Garcia-Vallvé, Santiago
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566095/
https://www.ncbi.nlm.nih.gov/pubmed/23405231
http://dx.doi.org/10.1371/journal.pone.0055889
_version_ 1782258528265699328
author Guasch, Laura
Sala, Esther
Mulero, Miquel
Valls, Cristina
Salvadó, Maria Josepa
Pujadas, Gerard
Garcia-Vallvé, Santiago
author_facet Guasch, Laura
Sala, Esther
Mulero, Miquel
Valls, Cristina
Salvadó, Maria Josepa
Pujadas, Gerard
Garcia-Vallvé, Santiago
author_sort Guasch, Laura
collection PubMed
description BACKGROUND: Natural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and their modes of action. METHODOLOGY/PRINCIPAL FINDINGS: From an initial set of 29,779 natural products that are annotated with their natural source and using a previously developed virtual screening procedure (carefully validated experimentally), we have predicted as potential peroxisome proliferators-activated receptor gamma (PPARγ) partial agonists 12 molecules from 11 extracts known to have antidiabetic activity. Six of these molecules are similar to molecules with described antidiabetic activity but whose mechanism of action is unknown. Therefore, it is plausible that these 12 molecules could be the bioactive molecules responsible, at least in part, for the antidiabetic activity of the extracts containing them. In addition, we have also identified as potential PPARγ partial agonists 10 molecules from 16 plants with undescribed antidiabetic activity but that are related (i.e., they are from the same genus) to plants with known antidiabetic properties. None of the 22 molecules that we predict as PPARγ partial agonists show chemical similarity with a group of 211 known PPARγ partial agonists obtained from the literature. CONCLUSIONS/SIGNIFICANCE: Our results provide a new hypothesis about the active molecules of natural extracts with antidiabetic properties and their mode of action. We also suggest plants with undescribed antidiabetic activity that may contain PPARγ partial agonists. These plants represent a new source of potential antidiabetic extracts. Consequently, our work opens the door to the discovery of new antidiabetic extracts and molecules that can be of use, for instance, in the design of new antidiabetic drugs or functional foods focused towards the prevention/treatment of type 2 Diabetes Mellitus.
format Online
Article
Text
id pubmed-3566095
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-35660952013-02-12 Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity Guasch, Laura Sala, Esther Mulero, Miquel Valls, Cristina Salvadó, Maria Josepa Pujadas, Gerard Garcia-Vallvé, Santiago PLoS One Research Article BACKGROUND: Natural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and their modes of action. METHODOLOGY/PRINCIPAL FINDINGS: From an initial set of 29,779 natural products that are annotated with their natural source and using a previously developed virtual screening procedure (carefully validated experimentally), we have predicted as potential peroxisome proliferators-activated receptor gamma (PPARγ) partial agonists 12 molecules from 11 extracts known to have antidiabetic activity. Six of these molecules are similar to molecules with described antidiabetic activity but whose mechanism of action is unknown. Therefore, it is plausible that these 12 molecules could be the bioactive molecules responsible, at least in part, for the antidiabetic activity of the extracts containing them. In addition, we have also identified as potential PPARγ partial agonists 10 molecules from 16 plants with undescribed antidiabetic activity but that are related (i.e., they are from the same genus) to plants with known antidiabetic properties. None of the 22 molecules that we predict as PPARγ partial agonists show chemical similarity with a group of 211 known PPARγ partial agonists obtained from the literature. CONCLUSIONS/SIGNIFICANCE: Our results provide a new hypothesis about the active molecules of natural extracts with antidiabetic properties and their mode of action. We also suggest plants with undescribed antidiabetic activity that may contain PPARγ partial agonists. These plants represent a new source of potential antidiabetic extracts. Consequently, our work opens the door to the discovery of new antidiabetic extracts and molecules that can be of use, for instance, in the design of new antidiabetic drugs or functional foods focused towards the prevention/treatment of type 2 Diabetes Mellitus. Public Library of Science 2013-02-06 /pmc/articles/PMC3566095/ /pubmed/23405231 http://dx.doi.org/10.1371/journal.pone.0055889 Text en © 2013 Guasch et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Guasch, Laura
Sala, Esther
Mulero, Miquel
Valls, Cristina
Salvadó, Maria Josepa
Pujadas, Gerard
Garcia-Vallvé, Santiago
Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title_full Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title_fullStr Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title_full_unstemmed Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title_short Identification of PPARgamma Partial Agonists of Natural Origin (II): In Silico Prediction in Natural Extracts with Known Antidiabetic Activity
title_sort identification of ppargamma partial agonists of natural origin (ii): in silico prediction in natural extracts with known antidiabetic activity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566095/
https://www.ncbi.nlm.nih.gov/pubmed/23405231
http://dx.doi.org/10.1371/journal.pone.0055889
work_keys_str_mv AT guaschlaura identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT salaesther identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT muleromiquel identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT vallscristina identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT salvadomariajosepa identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT pujadasgerard identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity
AT garciavallvesantiago identificationofppargammapartialagonistsofnaturaloriginiiinsilicopredictioninnaturalextractswithknownantidiabeticactivity