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...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0038261&type=printable |
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| author | Hanyong Chen Ke Yao Janos Nadas Ann M Bode Margarita Malakhova Naomi Oi Haitao Li Ronald A Lubet Zigang Dong |
| author_facet | Hanyong Chen Ke Yao Janos Nadas Ann M Bode Margarita Malakhova Naomi Oi Haitao Li Ronald A Lubet Zigang Dong |
| author_sort | Hanyong Chen |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-6b8767255c4f4de8a0f3d80118ce82dd |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-6b8767255c4f4de8a0f3d80118ce82dd2025-08-20T02:05:29ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0175e3826110.1371/journal.pone.0038261Prediction of molecular targets of cancer preventing flavonoid compounds using computational methods.Hanyong ChenKe YaoJanos NadasAnn M BodeMargarita MalakhovaNaomi OiHaitao LiRonald A LubetZigang DongPlant-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.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0038261&type=printable |
| spellingShingle | Hanyong Chen Ke Yao Janos Nadas Ann M Bode Margarita Malakhova Naomi Oi Haitao Li Ronald A Lubet Zigang Dong Prediction of molecular targets of cancer preventing flavonoid compounds using computational methods. PLoS ONE |
| 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 |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0038261&type=printable |
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