Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches

Hung-Jin Huang,1,2 Olga A Kraevaya,3,4 Ilya I Voronov,4 Pavel A Troshin,3,4 Shan-hui Hsu1,2,5 1Institute of Polymer Science and Engineering, National Taiwan University, Taipei, Taiwan; 2Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli, Taiwan; 3Skolkovo Institut...

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Autores principales:	Huang HJ, Kraevaya OA, Voronov II, Troshin PA, Hsu S
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	water-soluble fullerene derivatives non-small cell lung cancer cytotoxicity machine learning qsar Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/5ee83b16a01d4c11908146d5c28abb1f
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spelling	oai:doaj.org-article:5ee83b16a01d4c11908146d5c28abb1f2021-12-02T09:56:20ZFullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches1178-2013https://doaj.org/article/5ee83b16a01d4c11908146d5c28abb1f2020-04-01T00:00:00Zhttps://www.dovepress.com/fullerene-derivatives-as-lung-cancer-cell-inhibitors-investigation-of--peer-reviewed-article-IJNhttps://doaj.org/toc/1178-2013Hung-Jin Huang,1,2 Olga A Kraevaya,3,4 Ilya I Voronov,4 Pavel A Troshin,3,4 Shan-hui Hsu1,2,5 1Institute of Polymer Science and Engineering, National Taiwan University, Taipei, Taiwan; 2Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli, Taiwan; 3Skolkovo Institute of Science and Technology, Moscow, Russian Federation; 4Institute for Problems of Chemical Physics of Russian Academy of Sciences, Chernogolovka, Russian Federation; 5Research and Development Center for Medical Devices, National Taiwan University, Taipei, TaiwanCorrespondence: Shan-hui HsuInstitute of Polymer Science and Engineering, National Taiwan University, No. 1, Sec. 4 Roosevelt Road, Taipei 10617, TaiwanTel +886-2-3366-5313Fax +886-2-3366-5237Email shhsu@ntu.edu.twPavel A TroshinInstitute for Problems of Chemical Physics of Russian Academy of Sciences, Chernogolovka 142432, Russian FederationTel +7 496522-1418Fax +7 496515-5420Email troshin2003@inbox.ruBackground: 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 r2 and leave-one-out cross-validation q2 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.Keywords: water-soluble fullerene derivatives, non-small cell lung cancer, cytotoxicity, machine learning, QSAR  Huang HJKraevaya OAVoronov IITroshin PAHsu SDove Medical Pressarticlewater-soluble fullerene derivativesnon-small cell lung cancercytotoxicitymachine learningqsarMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol Volume 15, Pp 2485-2499 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	water-soluble fullerene derivatives non-small cell lung cancer cytotoxicity machine learning qsar Medicine (General) R5-920
spellingShingle	water-soluble fullerene derivatives non-small cell lung cancer cytotoxicity machine learning qsar Medicine (General) R5-920 Huang HJ Kraevaya OA Voronov II Troshin PA Hsu S Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches
description	Hung-Jin Huang,1,2 Olga A Kraevaya,3,4 Ilya I Voronov,4 Pavel A Troshin,3,4 Shan-hui Hsu1,2,5 1Institute of Polymer Science and Engineering, National Taiwan University, Taipei, Taiwan; 2Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli, Taiwan; 3Skolkovo Institute of Science and Technology, Moscow, Russian Federation; 4Institute for Problems of Chemical Physics of Russian Academy of Sciences, Chernogolovka, Russian Federation; 5Research and Development Center for Medical Devices, National Taiwan University, Taipei, TaiwanCorrespondence: Shan-hui HsuInstitute of Polymer Science and Engineering, National Taiwan University, No. 1, Sec. 4 Roosevelt Road, Taipei 10617, TaiwanTel +886-2-3366-5313Fax +886-2-3366-5237Email shhsu@ntu.edu.twPavel A TroshinInstitute for Problems of Chemical Physics of Russian Academy of Sciences, Chernogolovka 142432, Russian FederationTel +7 496522-1418Fax +7 496515-5420Email troshin2003@inbox.ruBackground: 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 r2 and leave-one-out cross-validation q2 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.Keywords: water-soluble fullerene derivatives, non-small cell lung cancer, cytotoxicity, machine learning, QSAR
format	article
author	Huang HJ Kraevaya OA Voronov II Troshin PA Hsu S
author_facet	Huang HJ Kraevaya OA Voronov II Troshin PA Hsu S
author_sort	Huang HJ
title	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_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_sort	fullerene derivatives as lung cancer cell inhibitors: investigation of potential descriptors using qsar approaches
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/5ee83b16a01d4c11908146d5c28abb1f
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Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigation of Potential Descriptors Using QSAR Approaches

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