Cytotoxicity of quantum dots: Use of quasiSMILES in development of reliable models with index of ideality of correlation and the consensus modelling

The assessment of cytotoxicity of quantum dots is very essential for environmental and health risk analysis. In the present work we have modelled HeLa cell cytotoxicity of sixty one CdSe quantum dots with ZnS shell as a function of its experimental conditions and molecular construction using quasiSMILES representations. The index of ideality of correlation helps in the building of ten statistically significant models having good fitting ability with value of R-2 ranging from 0.8414 to 0.9609 for the training set. The split 5 model is rated as the best model with values of R-2, Q(F1)(2), Q(F2)(2) and Q(F3)(2) as 0.8964, 0.8267, 0.8264 and 0.8777 respectively for the calibration set. The extraction of features causing increase and decrease of cytotoxicity of quantum dots indicates importance of neutral surface charge, surface modified with protein, 72 h exposure time, combination of MTT assay with surface protein in decreasing the cytotoxicity. Amphiphilic polymer, polyol ligand with neutral charge, 0.5 - 0.6 nm quantum dot diameter with lipid ligand and unmodified positively charged surface are grouped in toxicity enhancer features. Further, consensus modelling using split 5 and 8 patterns enhances the prediction quality by increasing the R-val(2) to 0.9361 and 0.9656 respectively.

Automated summary

Assessing the cytotoxicity of CdSe quantum dots on HeLa cells is crucial for risk analysis, with the best model identified as split 5. Findings suggest that features such as neutral surface charge, 72-hour exposure time, and the combination of MTT assay with surface protein are important for reducing cytotoxicity, while amphiphilic polymers and polyol ligands with neutral charge enhance toxicity. Consensus modeling using split 5 and 8 patterns improves prediction quality by increasing R-val(2) to 0.9361 and 0.9656 respectively.