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

Abstract

The different features of the impact of nanoparticles on cells, such as the structure of the core, presence/absence of doping, quality of surface, diameter, and dose, were used to define quasi-SMILES, a line of symbols encoded the above physicochemical features of the impact of nanoparticles. The correlation weight for each code in the quasi-SMILES has been calculated by the Monte Carlo method. The descriptor, which is the sum of the correlation weights, is the basis for a one-variable model of the biological activity of nano-inhibitors of human lung carcinoma cell line A549. The system of models obtained by the above scheme was checked on the self-consistence, i.e., reproducing the statistical quality of these models observed for different distributions of available nanomaterials into the training and validation sets. The computational experiments confirm the excellent potential of the approach as a tool to predict the impact of nanomaterials under different experimental conditions. In conclusion, our model is a self-consistent model system that provides a user to assess the reliability of the statistical quality of the used approach.

Keywords:

• Computational nano-toxicology
• human lung carcinoma cell line A549
• system of self-consistent models
• quasi-SMILES
• CORAL software

Author contributions

APT was involved in formal analysis, data collection, curation, investigation, methodology including statistics, software, visualization, writing of original draft, and revision. AAT was involved in conceptualization, data curation, formal analysis, investigation, methodology including statistics, software, writing of original draft, review, and editing. JM was involved in conceptualization, formal analysis, visualization, writing of original draft, review, and editing. EAM was involved in formal analysis, visualization, review, and editing. All authors revised it critically and finally approved the version to be submitted.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

The data used in this work and developed models are freely available Supplementary materials section.

Additional information

Funding

AAT and APT are grateful to the project LIFE-CONCERT (LIFE17 GIE/IT/000461) for their support. EAM was supported by European Union’s H2020 project Sinfonia (N.857253). JM was supported by SbDToolBox, NORTE-01-0145-FEDER-000047, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund.