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Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches
BACKGROUND: Nanotechnology-based strategies in the treatment of cancer have potential advantages because of the favorable delivery of nanoparticles into tumors through porous vasculature. MATERIALS AND METHODS: In the current study, we synthesized a series of water-soluble fullerene derivatives and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170710/ https://www.ncbi.nlm.nih.gov/pubmed/32368036 http://dx.doi.org/10.2147/IJN.S243463 |
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author | Huang, Hung-Jin Kraevaya, Olga A Voronov, Ilya I Troshin, Pavel A Hsu, Shan-hui |
author_facet | Huang, Hung-Jin Kraevaya, Olga A Voronov, Ilya I Troshin, Pavel A Hsu, Shan-hui |
author_sort | Huang, Hung-Jin |
collection | PubMed |
description | BACKGROUND: Nanotechnology-based strategies in the treatment of cancer have potential advantages because of the favorable delivery of nanoparticles into tumors through porous vasculature. MATERIALS AND METHODS: In the current study, we synthesized a series of water-soluble fullerene derivatives and observed their anti-tumor effects on human lung carcinoma A549 cell lines. The quantitative structure–activity relationship (QSAR) modeling was employed to investigate the relationship between anticancer effects and descriptors relevant to peculiarities of molecular structures of fullerene derivatives. RESULTS: In the QSAR regression model, the evaluation results revealed that the determination coefficient r(2) and leave-one-out cross-validation q(2) for the recommended QSAR model were 0.9966 and 0.9246, respectively, indicating the reliability of the results. The molecular modeling showed that the lack of chlorine atom and a lower number of aliphatic single bonds in saturated hydrocarbon chains may be positively correlated with the lung cancer cytotoxicity of fullerene derivatives. Synthesized water-soluble fullerene derivatives have potential functional groups to inhibit the proliferation of lung cancer cells. CONCLUSION: The guidelines obtained from the QSAR model might strongly facilitate the rational design of potential fullerene-based drug candidates for lung cancer therapy in the future. |
format | Online Article Text |
id | pubmed-7170710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-71707102020-05-04 Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches Huang, Hung-Jin Kraevaya, Olga A Voronov, Ilya I Troshin, Pavel A Hsu, Shan-hui Int J Nanomedicine Original Research BACKGROUND: Nanotechnology-based strategies in the treatment of cancer have potential advantages because of the favorable delivery of nanoparticles into tumors through porous vasculature. MATERIALS AND METHODS: In the current study, we synthesized a series of water-soluble fullerene derivatives and observed their anti-tumor effects on human lung carcinoma A549 cell lines. The quantitative structure–activity relationship (QSAR) modeling was employed to investigate the relationship between anticancer effects and descriptors relevant to peculiarities of molecular structures of fullerene derivatives. RESULTS: In the QSAR regression model, the evaluation results revealed that the determination coefficient r(2) and leave-one-out cross-validation q(2) for the recommended QSAR model were 0.9966 and 0.9246, respectively, indicating the reliability of the results. The molecular modeling showed that the lack of chlorine atom and a lower number of aliphatic single bonds in saturated hydrocarbon chains may be positively correlated with the lung cancer cytotoxicity of fullerene derivatives. Synthesized water-soluble fullerene derivatives have potential functional groups to inhibit the proliferation of lung cancer cells. CONCLUSION: The guidelines obtained from the QSAR model might strongly facilitate the rational design of potential fullerene-based drug candidates for lung cancer therapy in the future. Dove 2020-04-14 /pmc/articles/PMC7170710/ /pubmed/32368036 http://dx.doi.org/10.2147/IJN.S243463 Text en © 2020 Huang et al. http://creativecommons.org/licenses/by-nc/3.0/ 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. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Huang, Hung-Jin Kraevaya, Olga A Voronov, Ilya I Troshin, Pavel A Hsu, Shan-hui Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title | Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title_full | Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title_fullStr | Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title_full_unstemmed | Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title_short | Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches |
title_sort | fullerene derivatives as lung cancer cell inhibitors: investigation of potential descriptors using qsar approaches |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170710/ https://www.ncbi.nlm.nih.gov/pubmed/32368036 http://dx.doi.org/10.2147/IJN.S243463 |
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