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Identification and Validation of Novel PERK Inhibitors
[Image: see text] PERK, as one of the principle unfolded protein response signal transducers, is believed to be associated with many human diseases, such as cancer and type-II diabetes. There has been increasing effort to discover potent PERK inhibitors due to its potential therapeutic interest. In...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038368/ https://www.ncbi.nlm.nih.gov/pubmed/24745945 http://dx.doi.org/10.1021/ci500114r |
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author | Wang, Qiantao Park, Jihyun Devkota, Ashwini K. Cho, Eun Jeong Dalby, Kevin N. Ren, Pengyu |
author_facet | Wang, Qiantao Park, Jihyun Devkota, Ashwini K. Cho, Eun Jeong Dalby, Kevin N. Ren, Pengyu |
author_sort | Wang, Qiantao |
collection | PubMed |
description | [Image: see text] PERK, as one of the principle unfolded protein response signal transducers, is believed to be associated with many human diseases, such as cancer and type-II diabetes. There has been increasing effort to discover potent PERK inhibitors due to its potential therapeutic interest. In this study, a computer-based virtual screening approach is employed to discover novel PERK inhibitors, followed by experimental validation. Using a focused library, we show that a consensus approach, combining pharmacophore modeling and docking, can be more cost-effective than using either approach alone. It is also demonstrated that the conformational flexibility near the active site is an important consideration in structure-based docking and can be addressed by using molecular dynamics. The consensus approach has further been applied to screen the ZINC lead-like database, resulting in the identification of 10 active compounds, two of which show IC(50) values that are less than 10 μM in a dose–response assay. |
format | Online Article Text |
id | pubmed-4038368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-40383682015-04-18 Identification and Validation of Novel PERK Inhibitors Wang, Qiantao Park, Jihyun Devkota, Ashwini K. Cho, Eun Jeong Dalby, Kevin N. Ren, Pengyu J Chem Inf Model [Image: see text] PERK, as one of the principle unfolded protein response signal transducers, is believed to be associated with many human diseases, such as cancer and type-II diabetes. There has been increasing effort to discover potent PERK inhibitors due to its potential therapeutic interest. In this study, a computer-based virtual screening approach is employed to discover novel PERK inhibitors, followed by experimental validation. Using a focused library, we show that a consensus approach, combining pharmacophore modeling and docking, can be more cost-effective than using either approach alone. It is also demonstrated that the conformational flexibility near the active site is an important consideration in structure-based docking and can be addressed by using molecular dynamics. The consensus approach has further been applied to screen the ZINC lead-like database, resulting in the identification of 10 active compounds, two of which show IC(50) values that are less than 10 μM in a dose–response assay. American Chemical Society 2014-04-18 2014-05-27 /pmc/articles/PMC4038368/ /pubmed/24745945 http://dx.doi.org/10.1021/ci500114r Text en Copyright © 2014 American Chemical Society |
spellingShingle | Wang, Qiantao Park, Jihyun Devkota, Ashwini K. Cho, Eun Jeong Dalby, Kevin N. Ren, Pengyu Identification and Validation of Novel PERK Inhibitors |
title | Identification and Validation of Novel PERK Inhibitors |
title_full | Identification and Validation of Novel PERK Inhibitors |
title_fullStr | Identification and Validation of Novel PERK Inhibitors |
title_full_unstemmed | Identification and Validation of Novel PERK Inhibitors |
title_short | Identification and Validation of Novel PERK Inhibitors |
title_sort | identification and validation of novel perk inhibitors |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038368/ https://www.ncbi.nlm.nih.gov/pubmed/24745945 http://dx.doi.org/10.1021/ci500114r |
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