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Computational Analysis of Artimisinin Derivatives on the Antitumor Activities
The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Singapore
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709249/ https://www.ncbi.nlm.nih.gov/pubmed/29094266 http://dx.doi.org/10.1007/s13659-017-0142-x |
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author | Liu, Hui Liu, Xingyong Zhang, Li |
author_facet | Liu, Hui Liu, Xingyong Zhang, Li |
author_sort | Liu, Hui |
collection | PubMed |
description | The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q(2) = 0.567, R(2) = 0.968, ONC = 5; q(2) = 0.547, R(2) = 0.980, ONC = 7; q(2) = 0.559, R(2) = 0.921, ONC = 7 and q(2) = 0.527, R(2) = 0.921, ONC = 6. The predictive ability of CoMSIA with r(2) = 0.991 is the best one compared with the other three approaches, such as CoMFA (r(2) = 0.787), topomer CoMFA (r(2) = 0.819) and HQSAR (r(2) = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities. |
format | Online Article Text |
id | pubmed-5709249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-57092492017-12-06 Computational Analysis of Artimisinin Derivatives on the Antitumor Activities Liu, Hui Liu, Xingyong Zhang, Li Nat Prod Bioprospect Original Article The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q(2) = 0.567, R(2) = 0.968, ONC = 5; q(2) = 0.547, R(2) = 0.980, ONC = 7; q(2) = 0.559, R(2) = 0.921, ONC = 7 and q(2) = 0.527, R(2) = 0.921, ONC = 6. The predictive ability of CoMSIA with r(2) = 0.991 is the best one compared with the other three approaches, such as CoMFA (r(2) = 0.787), topomer CoMFA (r(2) = 0.819) and HQSAR (r(2) = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities. Springer Singapore 2017-11-01 /pmc/articles/PMC5709249/ /pubmed/29094266 http://dx.doi.org/10.1007/s13659-017-0142-x Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Liu, Hui Liu, Xingyong Zhang, Li Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title | Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title_full | Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title_fullStr | Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title_full_unstemmed | Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title_short | Computational Analysis of Artimisinin Derivatives on the Antitumor Activities |
title_sort | computational analysis of artimisinin derivatives on the antitumor activities |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709249/ https://www.ncbi.nlm.nih.gov/pubmed/29094266 http://dx.doi.org/10.1007/s13659-017-0142-x |
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