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Research Articles

The system of self-consistent models based on quasi-SMILES as a tool to predict the potential of nano-inhibitors of human lung carcinoma cell line A549 for different experimental conditions

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 306-313 | Received 23 Jun 2022, Accepted 11 Oct 2022, Published online: 06 Feb 2023

References

  • Alfaro-Moreno, E., et al., 2013. Particulate matter and nanoparticles toxicology. BioMed Research International, 2013, 642974.
  • Ahmadi, S., et al., 2021. The predictive model for band gap prediction of metal oxide nanoparticles based on quasi-SMILES. Structural Chemistry, 32 (5), 1893–1905.
  • Bunmahotama, W., Vijver, M.G., and Peijnenburg, W., 2022. Development of a quasi–quantitative structure–activity relationship model for prediction of the immobilization response of Daphnia magna exposed to metal-based nanomaterials. Environmental Toxicology and Chemistry, 41 (6), 1439–1450.
  • Kleandrova, V.V., et al., 2014. Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions. Environment International, 73, 288–294.
  • Lebre, F., et al., 2022. Nanosafety: an evolving concept to bring the safest possible nanomaterials to society and environment. Nanomaterials, 12 (11), 1810.
  • Mercader, A., Castro, E.A., and Toropov, A.A., 2000. QSPR modeling of the enthalpy of formation from elements by means of correlation weighting of local invariants of atomic orbital molecular graphs. Chemical Physics Letters, 330 (5–6), 612–623.
  • OECD. 2014. Organisation for economic co-operation and development. ecotoxicology and environmental fate of manufactured nanomaterials, series on the safety of manufactured nanomaterials, ENV/JM/MONO(2014)1, test no. 40. Paris, France: OECD.
  • OECD. 2020. Organisation for economic co-operation and development. Guidance document for the testing of dissolution and dispersion stability of nanomaterials and the use of the data for further environmental testing and assessment strategies. OECD guidelines for the testing of chemicals, ENV/JM/MONO(2020)9, test no. 318. Paris, France: OECD.
  • Panneerselvam, S. and Choi, S., 2014. Nanoinformatics: emerging databases and available tools. International Journal of Molecular Sciences, 15 (5), 7158–7182.
  • Polyakova, Y., Long, M.J., and Kyung, H.R., 2006. QSPR models for chromatographic retention of some azoles with physicochemical properties. Bulletin of the Korean Chemical Society, 27 (2), 211–218.
  • Shin, H.K., Kim, S., and Yoon, S., 2021. Use of size-dependent electron configuration fingerprint to develop general prediction models for nanomaterials. NanoImpact, 21, 100298.
  • Singh, A.V., et al., 2020. Artificial intelligence and machine learning in computational nanotoxicology: unlocking and empowering nanomedicine. Advanced Healthcare Materials, 9 (17), 1901862.
  • Toropov, A.A., et al., 2005. Simplified molecular input line entry system (SMILES) as an alternative for constructing quantitative structure–property relationships (QSPR). Indian Journal of Chemistry Section A, 44 (8), 1545–1552.
  • Toropov, A.A., et al., 2016. Towards predicting the solubility of CO2 and N2 in different polymers using a quasi-SMILES based QSPR approach. SAR and QSAR in Environmental Research, 27 (4), 293–301.
  • Toropov, A.A. and Toropova, A.P., 2015. Quasi-SMILES and nano-QFAR: united model for mutagenicity of fullerene and MWCNT under different conditions. Chemosphere, 139, 18–22.
  • Toropov, A.A. and Toropova, A.P., 2019. The Correlation Contradictions Index (CCI): building up reliable models of mutagenic potential of silver nanoparticles under different conditions using quasi-SMILES. Science of the Total Environment, 681, 102–109.
  • Toropov, A.A. and Toropova, A.P., 2021a. Quasi-SMILES as a basis for the development of models for the toxicity of ZnO nanoparticles. Science of the Total Environment, 772, 145532.
  • Toropov, A.A. and Toropova, A.P., 2021b. The system of self-consistent models for the uptake of nanoparticles in PaCa2 cancer cells. Nanotoxicology, 15 (7), 995–1004.
  • Toropov, A.A., et al., 2022. The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models. Toxicology Mechanisms and Methods, 32 (7), 549–557.
  • Toropov, A.A., Kjeldsen, F., and Toropova, A.P., 2022. Use of quasi-SMILES to build models based on quantitative results from experiments with nanomaterials. Chemosphere, 303 (Pt 2), 135086.
  • Toropova, A.P. and Toropov, A.A., 2017. The index of ideality of correlation: a criterion of predictability of QSAR models for skin permeability? Science of the Total Environment, 586, 466–472.
  • Toropova, A.P. and Toropov, A.A., 2021. The system of self-consistent of models: a new approach to build up and validation of predictive models of the octanol/water partition coefficient for gold nanoparticles. International Journal of Environmental Research, 15 (4), 709–722.
  • Toropova, A.P., et al., 2021. Application of quasi-SMILES to the model of gold-nanoparticles uptake in A549 cells. Computers in Biology and Medicine, 136, 104720.
  • Toropova, A.P., Toropov, A.A., and Benfenati, E., 2021. The self-organizing vector of atom-pairs proportions: use to develop models for melting points. Structural Chemistry, 32 (3), 967–971.
  • Toropova, A.P., et al., 2022. The system of self-consistent models for vapour pressure. Chemical Physics Letters, 790, 139354.
  • Toropova, A.P., Toropov, A.A., and Fjodorova, N., 2022. Quasi-SMILES for predicting toxicity of nano-mixtures to Daphnia magna. NanoImpact, 28, 100427.
  • Toropova, A.P. and Toropov, A.A., 2022. Nanomaterials: quasi-SMILES as a flexible basis for regulation and environmental risk assessment. Science of the Total Environment, 823, 153747.
  • Trinh, T.X., et al., 2018. Quasi-SMILES-based nano-quantitative structure–activity relationship model to predict the cytotoxicity of multiwalled carbon nanotubes to human lung cells. Chemical Research in Toxicology, 31 (3), 183–190.
  • Weininger, D., 1988. SMILES, a chemical language and information system: 1: introduction to methodology and encoding rules. Journal of Chemical Information and Modeling, 28 (1), 31–36.
  • Zielińska, A., et al., 2020. Nanotoxicology and nanosafety: safety-by-design and testing at a glance. International Journal of Environmental Research and Public Health, 17 (13), 4657.