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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...

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Detalles Bibliográficos
Autores principales: Huang, Hung-Jin, Kraevaya, Olga A, Voronov, Ilya I, Troshin, Pavel A, Hsu, Shan-hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
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
Descripción
Sumario: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.