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In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically

Unlimited growth of cancer cells requires an extensive nutrient supply. To meet this demand, cancer cells drastically upregulate glucose uptake and metabolism compared to normal cells. This difference has made the blocking of glycolysis a fascinating strategy to treat this malignant disease. α-enola...

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Autores principales: Lung, Jrhau, Chen, Kuan-Liang, Hung, Chien-Hui, Chen, Chih-Cheng, Hung, Ming-Szu, Lin, Yu-Ching, Wu, Ching-Yuan, Lee, Kuan-Der, Shih, Neng-Yao, Tsai, Ying Huang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695255/
https://www.ncbi.nlm.nih.gov/pubmed/29180852
http://dx.doi.org/10.2147/DDDT.S149214
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author Lung, Jrhau
Chen, Kuan-Liang
Hung, Chien-Hui
Chen, Chih-Cheng
Hung, Ming-Szu
Lin, Yu-Ching
Wu, Ching-Yuan
Lee, Kuan-Der
Shih, Neng-Yao
Tsai, Ying Huang
author_facet Lung, Jrhau
Chen, Kuan-Liang
Hung, Chien-Hui
Chen, Chih-Cheng
Hung, Ming-Szu
Lin, Yu-Ching
Wu, Ching-Yuan
Lee, Kuan-Der
Shih, Neng-Yao
Tsai, Ying Huang
author_sort Lung, Jrhau
collection PubMed
description Unlimited growth of cancer cells requires an extensive nutrient supply. To meet this demand, cancer cells drastically upregulate glucose uptake and metabolism compared to normal cells. This difference has made the blocking of glycolysis a fascinating strategy to treat this malignant disease. α-enolase is not only one of the most upregulated glycolytic enzymes in cancer cells, but also associates with many cellular processes or conditions important to cancer cell survival, such as cell migration, invasion, and hypoxia. Targeting α-enolase could simultaneously disturb cancer cells in multiple ways and, therefore, is a good target for anticancer drug development. In the current study, more than 22 million chemical structures meeting the criteria of Lipinski’s rule of five from the ZINC database were docked to α-enolase by virtual screening. Twenty-four chemical structures with docking scores better than that of the enolase substrate, 2-phosphoglycerate, were further screened by the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties prediction. Four of them were classified as non-mutagenic, non-carcinogenic, and capable of oral administration where they showed steady interactions to α-enolase that were comparable, even superior, to the currently available inhibitors in molecular dynamics (MD) simulation. These compounds may be considered promising leads for further development of the α-enolase inhibitors and could help fight cancer metabolically.
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spelling pubmed-56952552017-11-27 In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically Lung, Jrhau Chen, Kuan-Liang Hung, Chien-Hui Chen, Chih-Cheng Hung, Ming-Szu Lin, Yu-Ching Wu, Ching-Yuan Lee, Kuan-Der Shih, Neng-Yao Tsai, Ying Huang Drug Des Devel Ther Original Research Unlimited growth of cancer cells requires an extensive nutrient supply. To meet this demand, cancer cells drastically upregulate glucose uptake and metabolism compared to normal cells. This difference has made the blocking of glycolysis a fascinating strategy to treat this malignant disease. α-enolase is not only one of the most upregulated glycolytic enzymes in cancer cells, but also associates with many cellular processes or conditions important to cancer cell survival, such as cell migration, invasion, and hypoxia. Targeting α-enolase could simultaneously disturb cancer cells in multiple ways and, therefore, is a good target for anticancer drug development. In the current study, more than 22 million chemical structures meeting the criteria of Lipinski’s rule of five from the ZINC database were docked to α-enolase by virtual screening. Twenty-four chemical structures with docking scores better than that of the enolase substrate, 2-phosphoglycerate, were further screened by the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties prediction. Four of them were classified as non-mutagenic, non-carcinogenic, and capable of oral administration where they showed steady interactions to α-enolase that were comparable, even superior, to the currently available inhibitors in molecular dynamics (MD) simulation. These compounds may be considered promising leads for further development of the α-enolase inhibitors and could help fight cancer metabolically. Dove Medical Press 2017-11-16 /pmc/articles/PMC5695255/ /pubmed/29180852 http://dx.doi.org/10.2147/DDDT.S149214 Text en © 2017 Lung et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Lung, Jrhau
Chen, Kuan-Liang
Hung, Chien-Hui
Chen, Chih-Cheng
Hung, Ming-Szu
Lin, Yu-Ching
Wu, Ching-Yuan
Lee, Kuan-Der
Shih, Neng-Yao
Tsai, Ying Huang
In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title_full In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title_fullStr In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title_full_unstemmed In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title_short In silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
title_sort in silico-based identification of human α-enolase inhibitors to block cancer cell growth metabolically
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695255/
https://www.ncbi.nlm.nih.gov/pubmed/29180852
http://dx.doi.org/10.2147/DDDT.S149214
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