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Identification of PPARγ ligands with One-dimensional Drug Profile Matching
INTRODUCTION: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Ad...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3770887/ https://www.ncbi.nlm.nih.gov/pubmed/24039401 http://dx.doi.org/10.2147/DDDT.S47173 |
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author | Kovács, Diána Simon, Zoltán Hári, Péter Málnási-Csizmadia, András Hegedűs, Csaba Drimba, László Németh, József Sári, Réka Szilvássy, Zoltán Peitl, Barna |
author_facet | Kovács, Diána Simon, Zoltán Hári, Péter Málnási-Csizmadia, András Hegedűs, Csaba Drimba, László Németh, József Sári, Réka Szilvássy, Zoltán Peitl, Barna |
author_sort | Kovács, Diána |
collection | PubMed |
description | INTRODUCTION: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Administration-approved generic drug database by means of the One-dimensional Drug Profile Matching (oDPM) method in order to find potential peroxisome proliferator-activated receptor gamma (PPARγ) agonists. The PPARγ action of the selected generics was also investigated by in vitro and in vivo experiments. MATERIALS AND METHODS: The in silico oDPM method was used to determine the binding potency of 1,255 generics to 149 proteins collected. In vitro PPARγ activation was determined by measuring fatty acid-binding protein 4/adipocyte protein gene expression in a Mono Mac 6 cell line. The in vivo insulin sensitizing effect of the selected compound (nitazoxanide; 50–200 mg/kg/day over 8 days; n = 8) was established in type 2 diabetic rats by hyperinsulinemic euglycemic glucose clamping. RESULTS: After examining the closest neighbors of each of the reference set’s members and counting their most abundant neighbors, ten generic drugs were selected with oDPM. Among them, four enhanced fatty acid-binding protein/adipocyte protein gene expression in the Mono Mac 6 cell line, but only bromfenac and nitazoxanide showed dose-dependent actions. Induction by nitazoxanide was higher than by bromfenac. Nitazoxanide lowered fasting blood glucose levels and improved insulin sensitivity in type 2 diabetic rats. CONCLUSION: We demonstrated that the oDPM method can predict previously unknown therapeutic effects of generic drugs. Nitazoxanide can be the prototype chemical structure of the new generation of insulin sensitizers. |
format | Online Article Text |
id | pubmed-3770887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-37708872013-09-13 Identification of PPARγ ligands with One-dimensional Drug Profile Matching Kovács, Diána Simon, Zoltán Hári, Péter Málnási-Csizmadia, András Hegedűs, Csaba Drimba, László Németh, József Sári, Réka Szilvássy, Zoltán Peitl, Barna Drug Des Devel Ther Original Research INTRODUCTION: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Administration-approved generic drug database by means of the One-dimensional Drug Profile Matching (oDPM) method in order to find potential peroxisome proliferator-activated receptor gamma (PPARγ) agonists. The PPARγ action of the selected generics was also investigated by in vitro and in vivo experiments. MATERIALS AND METHODS: The in silico oDPM method was used to determine the binding potency of 1,255 generics to 149 proteins collected. In vitro PPARγ activation was determined by measuring fatty acid-binding protein 4/adipocyte protein gene expression in a Mono Mac 6 cell line. The in vivo insulin sensitizing effect of the selected compound (nitazoxanide; 50–200 mg/kg/day over 8 days; n = 8) was established in type 2 diabetic rats by hyperinsulinemic euglycemic glucose clamping. RESULTS: After examining the closest neighbors of each of the reference set’s members and counting their most abundant neighbors, ten generic drugs were selected with oDPM. Among them, four enhanced fatty acid-binding protein/adipocyte protein gene expression in the Mono Mac 6 cell line, but only bromfenac and nitazoxanide showed dose-dependent actions. Induction by nitazoxanide was higher than by bromfenac. Nitazoxanide lowered fasting blood glucose levels and improved insulin sensitivity in type 2 diabetic rats. CONCLUSION: We demonstrated that the oDPM method can predict previously unknown therapeutic effects of generic drugs. Nitazoxanide can be the prototype chemical structure of the new generation of insulin sensitizers. Dove Medical Press 2013-09-02 /pmc/articles/PMC3770887/ /pubmed/24039401 http://dx.doi.org/10.2147/DDDT.S47173 Text en © 2013 Kovács et al. This work is published by Dove Medical Press Ltd, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Ltd, provided the work is properly attributed. |
spellingShingle | Original Research Kovács, Diána Simon, Zoltán Hári, Péter Málnási-Csizmadia, András Hegedűs, Csaba Drimba, László Németh, József Sári, Réka Szilvássy, Zoltán Peitl, Barna Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title | Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title_full | Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title_fullStr | Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title_full_unstemmed | Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title_short | Identification of PPARγ ligands with One-dimensional Drug Profile Matching |
title_sort | identification of pparγ ligands with one-dimensional drug profile matching |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3770887/ https://www.ncbi.nlm.nih.gov/pubmed/24039401 http://dx.doi.org/10.2147/DDDT.S47173 |
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