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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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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 |
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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 |
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