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Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods
Plant-based polyphenols (i.e., phytochemicals) have been used as treatments for human ailments for centuries. The mechanisms of action of these plant-derived compounds are now a major area of investigation. Thousands of phytochemicals have been isolated, and a large number of them have shown protect...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3365021/ https://www.ncbi.nlm.nih.gov/pubmed/22693608 http://dx.doi.org/10.1371/journal.pone.0038261 |
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author | Chen, Hanyong Yao, Ke Nadas, Janos Bode, Ann M. Malakhova, Margarita Oi, Naomi Li, Haitao Lubet, Ronald A. Dong, Zigang |
author_facet | Chen, Hanyong Yao, Ke Nadas, Janos Bode, Ann M. Malakhova, Margarita Oi, Naomi Li, Haitao Lubet, Ronald A. Dong, Zigang |
author_sort | Chen, Hanyong |
collection | PubMed |
description | Plant-based polyphenols (i.e., phytochemicals) have been used as treatments for human ailments for centuries. The mechanisms of action of these plant-derived compounds are now a major area of investigation. Thousands of phytochemicals have been isolated, and a large number of them have shown protective activities or effects in different disease models. Using conventional approaches to select the best single or group of best chemicals for studying the effectiveness in treating or preventing disease is extremely challenging. We have developed and used computational-based methodologies that provide efficient and inexpensive tools to gain further understanding of the anticancer and therapeutic effects exerted by phytochemicals. Computational methods involving virtual screening, shape and pharmacophore analysis and molecular docking have been used to select chemicals that target a particular protein or enzyme and to determine potential protein targets for well-characterized as well as for novel phytochemicals. |
format | Online Article Text |
id | pubmed-3365021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-33650212012-06-12 Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods Chen, Hanyong Yao, Ke Nadas, Janos Bode, Ann M. Malakhova, Margarita Oi, Naomi Li, Haitao Lubet, Ronald A. Dong, Zigang PLoS One Research Article Plant-based polyphenols (i.e., phytochemicals) have been used as treatments for human ailments for centuries. The mechanisms of action of these plant-derived compounds are now a major area of investigation. Thousands of phytochemicals have been isolated, and a large number of them have shown protective activities or effects in different disease models. Using conventional approaches to select the best single or group of best chemicals for studying the effectiveness in treating or preventing disease is extremely challenging. We have developed and used computational-based methodologies that provide efficient and inexpensive tools to gain further understanding of the anticancer and therapeutic effects exerted by phytochemicals. Computational methods involving virtual screening, shape and pharmacophore analysis and molecular docking have been used to select chemicals that target a particular protein or enzyme and to determine potential protein targets for well-characterized as well as for novel phytochemicals. Public Library of Science 2012-05-31 /pmc/articles/PMC3365021/ /pubmed/22693608 http://dx.doi.org/10.1371/journal.pone.0038261 Text en Chen et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Chen, Hanyong Yao, Ke Nadas, Janos Bode, Ann M. Malakhova, Margarita Oi, Naomi Li, Haitao Lubet, Ronald A. Dong, Zigang Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title | Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title_full | Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title_fullStr | Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title_full_unstemmed | Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title_short | Prediction of Molecular Targets of Cancer Preventing Flavonoid Compounds Using Computational Methods |
title_sort | prediction of molecular targets of cancer preventing flavonoid compounds using computational methods |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3365021/ https://www.ncbi.nlm.nih.gov/pubmed/22693608 http://dx.doi.org/10.1371/journal.pone.0038261 |
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