Quantitative Structure-Activity Relationship Models for Predicting Inflammatory Potential of Metal Oxide Nanoparticles

Environmental Health Perspectives
Yang HuangRuibin Li

Abstract

Although substantial concerns about the inflammatory effects of engineered nanomaterial (ENM) have been raised, experimentally assessing toxicity of various ENMs is challenging and time-consuming. Alternatively, quantitative structure-activity relationship (QSAR) models have been employed to assess nanosafety. However, no previous attempt has been made to predict the inflammatory potential of ENMs. By employing metal oxide nanoparticles (MeONPs) as a model ENM, we aimed to develop QSAR models for prediction of the inflammatory potential by their physicochemical properties. We built a comprehensive data set of 30 MeONPs to screen a proinflammatory cytokine interleukin (IL)-1 beta ( IL- 1 β ) release in THP-1 cell line. The in vitro hazard ranking was validated in mouse lungs by oropharyngeal instillation of six randomly selected MeONPs. We established QSAR models for prediction of MeONP-induced inflammatory potential via machine learning. The models were further validated against seven new MeONPs. Density functional theory (DFT) computations were exploited to decipher the key mechanisms driving inflammatory responses of MeONPs. Seventeen out of 30 MeONPs induced excess IL- 1 β production in THP-1 cells. In vivo disease out...Continue Reading

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Citations

Jul 15, 2020·Nature Communications·Shujuan XuRuibin Li
Dec 20, 2020·Journal of Controlled Release : Official Journal of the Controlled Release Society·Ali Shakeri-ZadehHadi Samadian

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Methods Mentioned

BETA
biopsy
ELISA
transmission electron microscopy
PMA
bronchoalveolar lavage

Software Mentioned

FindIt
Weka
DMol
Open Babel
Vienna Ab initio Simulation Package ( VASP
MOPAC
MeONP

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