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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...

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Autores principales: Wang, Qiantao, Park, Jihyun, Devkota, Ashwini K., Cho, Eun Jeong, Dalby, Kevin N., Ren, Pengyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2014
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.
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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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