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Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors
Aldose reductase (AR) plays an important role in the development of several long-term diabetic complications. Inhibition of AR activities is a strategy for controlling complications arising from chronic diabetes. Several AR inhibitors have been reported in the literature. Flavonoid type compounds ar...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4330605/ https://www.ncbi.nlm.nih.gov/pubmed/25709964 http://dx.doi.org/10.4103/2231-4040.150366 |
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author | Chandra De, Utpal Debnath, Tanusree Sen, Debanjan Debnath, Sudhan |
author_facet | Chandra De, Utpal Debnath, Tanusree Sen, Debanjan Debnath, Sudhan |
author_sort | Chandra De, Utpal |
collection | PubMed |
description | Aldose reductase (AR) plays an important role in the development of several long-term diabetic complications. Inhibition of AR activities is a strategy for controlling complications arising from chronic diabetes. Several AR inhibitors have been reported in the literature. Flavonoid type compounds are shown to have significant AR inhibition. The objective of this study was to perform a computational work to get an idea about structural insight of flavonoid type compounds for developing as well as for searching new flavonoid based AR inhibitors. The data-set comprising 68 flavones along with their pIC(50) values ranging from 0.44 to 4.59 have been collected from literature. Structure of all the flavonoids were drawn in Chembiodraw Ultra 11.0, converted into corresponding three-dimensional structure, saved as mole file and then imported to maestro project table. Imported ligands were prepared using LigPrep option of maestro 9.6 version. Three-dimensional quantitative structure-activity relationships and docking studies were performed with appropriate options of maestro 9.6 version installed in HP Z820 workstation with CentOS 6.3 (Linux). A model with partial least squares factor 5, standard deviation 0.2482, R(2) = 0.9502 and variance ratio of regression 122 has been found as the best statistical model. |
format | Online Article Text |
id | pubmed-4330605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-43306052015-02-23 Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors Chandra De, Utpal Debnath, Tanusree Sen, Debanjan Debnath, Sudhan J Adv Pharm Technol Res Original Article Aldose reductase (AR) plays an important role in the development of several long-term diabetic complications. Inhibition of AR activities is a strategy for controlling complications arising from chronic diabetes. Several AR inhibitors have been reported in the literature. Flavonoid type compounds are shown to have significant AR inhibition. The objective of this study was to perform a computational work to get an idea about structural insight of flavonoid type compounds for developing as well as for searching new flavonoid based AR inhibitors. The data-set comprising 68 flavones along with their pIC(50) values ranging from 0.44 to 4.59 have been collected from literature. Structure of all the flavonoids were drawn in Chembiodraw Ultra 11.0, converted into corresponding three-dimensional structure, saved as mole file and then imported to maestro project table. Imported ligands were prepared using LigPrep option of maestro 9.6 version. Three-dimensional quantitative structure-activity relationships and docking studies were performed with appropriate options of maestro 9.6 version installed in HP Z820 workstation with CentOS 6.3 (Linux). A model with partial least squares factor 5, standard deviation 0.2482, R(2) = 0.9502 and variance ratio of regression 122 has been found as the best statistical model. Medknow Publications & Media Pvt Ltd 2015 /pmc/articles/PMC4330605/ /pubmed/25709964 http://dx.doi.org/10.4103/2231-4040.150366 Text en Copyright: © Journal of Advanced Pharmaceutical Technology & Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Chandra De, Utpal Debnath, Tanusree Sen, Debanjan Debnath, Sudhan Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title | Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title_full | Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title_fullStr | Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title_full_unstemmed | Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title_short | Three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
title_sort | three-dimensional quantitative structure-activity relationships and docking studies of some structurally diverse flavonoids and design of new aldose reductase inhibitors |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4330605/ https://www.ncbi.nlm.nih.gov/pubmed/25709964 http://dx.doi.org/10.4103/2231-4040.150366 |
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