Nanosafety-data-reusability-34-datasets

Quasi-QSAR for predicting the cell viability of human lung and skin cells exposed to different metal oxide nanomaterials (2019)

Original Study Abstract

A quasi-QSAR model was developed to predict the cell viability of human lung (BEAS-2B) and skin (HaCaT) cells exposed to 21 types of metal oxide nanomaterials. A wide range of toxicity datasets obtained from the S2NANO (www.s2nano.org) database was used. The data of descriptors representing the physicochemical properties and experimental conditions were coded to quasi-SMILES. In particular, hierarchical cluster analysis (HCA) and min-max normalization method were respectively used in assigning alphanumeric codes for numerical descriptors (e.g., core size, hydrodynamic size, surface charge, and dose) and then quasi-QSAR model performances for both methods were compared. The quasi-QSAR models were developed using CORAL software (www.insilico.eu/coral). Quasi-QSAR model built using quasi-SMILES generated by means of HCA showed better performance than the min-max normalization method. The model showed satisfactory statistical results ( for the training dataset: 0.71–0.73; for the calibration dataset: 0.74–0.82; and for the validation dataset: 0.70–0.76).

Data Sample

No. PMID Material CoreSize HydrodynamicSize SurfaceCharge AssayMethod CellLine Dose CellViability(%) PChem score (Maximum score: 5)
1 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 0,4 100 4,75
2 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 0,8 100 4,75
3 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 1,6 100 4,75
4 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 3,2 100 4,75
5 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 6,3 93,5 4,75
6 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 12,5 66,3 4,75
7 22502734 Co3O4 10 222,7 24,6 ATP BEAS-2B 25 43,9 4,75

Data Summary

Group Count
# of Toxicity Endpoints 337
# of Nanomaterial types 21