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

Abstract

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 [phone]Fax [phone]Email [email protected] A TroshinInstitute for Problems of Chemical Physics of Russian Academy of Sciences, Chernogolovka 142432, Russian FederationTel [phone]Fax [phone]Email [email protected]: 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  

Keywords

• water-soluble fullerene derivatives
• non-small cell lung cancer
• cytotoxicity
• machine learning
• qsar