NanoToxRadar: A Multitarget Nano-QSAR Model for Predicting the Cytotoxicity Values of Multicomponent Nanoparticles

Nanotechnological advances have led to the development
of nanoparticles
with complex structures. In this context, nano-QSAR models have been
developed to assess toxicity; however, the applicability domain (AD)
of such models is significantly restricted to specific types of nanoparticles
(i.e., bare metal oxides, coated metals, or carbon-based nanomaterials)
and target cell lines. Accordingly, NanoToxRadar, a web-based platform
for predicting the toxicity of multicomponent nanoparticles (MC-NPs)
toward various cell lines, was developed to extend the AD of the nano-QSAR
model. The size-dependent electron-configuration fingerprint was
used to represent the molecular structures of MC-NPs, and one-hot
encoded cell types were used to predict toxicities toward 110 cell
lines. The CatBoost regression model achieved good performance (R2Test = 0.877) and was deployed online (https://www.kitox.re.kr/nanotoxradar). The Web site takes the nanoparticle composition of the core as
well as the shell, dopant, coating material, and diameter as inputs
and predicts pIC50 values for 110 cell lines.