TY - JOUR
T1 - 纳米金属氧化物对人体细胞毒性效应的构效关系研究
AU - Cao, Hong Yin
AU - Yuan, Bei Lei
AU - Pan, Yong
AU - Shi, Hai Hua
N1 - Publisher Copyright:
© 2023 Science China Press. All rights reserved.
PY - 2023/1
Y1 - 2023/1
N2 - To establish an efficient structure-activity relationship model for cytotoxicity of metal oxide nanoparticles, the structure-activity relationships of toxic effects of twenty metal oxide nanoparticles on human normal lung epithelial cells (BEAS 2B) and keratinocytes (Hacat) were researched under different biological conditions. For the first time, eleven periodic table-based descriptors (quantitative descriptors) and six experimental condition parameters (qualitative descriptors) were combined to characterize the nanostructure characteristics of metal oxides. Three descriptors, namely metal electronegativity (χ), Hydro Size and Dose, were selected from the above descriptors by the support vector machine-feature recursive elimination (SVM RFE) method to form the optimal feature subset, which was used as input parameters of this study. On this basis, two nano-SAR prediction models were established by using support vector machine (SVM) and random forest (RF) modeling methods respectively. Both accuracy (ACC) of training sets in two models are more than 0. 9, both accuracies of the internal validation are more than 0. 7, and both accuracies of the external validation for the test sets are more than 0. 8. The model validation results show that the combination of periodic table-based descriptors and biological condition parameters can effectively characterize the molecular structure characteristics of metal oxide nanoparticles, and the two models established have good stability and strong prediction ability. The results of the model comparison show that the RF model is superior to the SVM model, and the performance of the RF model is superior to existing models reported in the literature. The results of model mechanism interpretation using the descriptor sensitivity analysis method show that the Hydro Size and electronegativity of metal oxide nanoparticles are the main structural factors affecting their toxicity to both human normal lung epithelial cells (BEAS 2B) and keratinocytes(Hacat), and the smaller the nanoparticle size is, the easier it is to enter the cells. As a scale of the ability of atoms to attract electrons in compounds, electronegativity mainly plays a role in inducing intracellular oxidative stress.
AB - To establish an efficient structure-activity relationship model for cytotoxicity of metal oxide nanoparticles, the structure-activity relationships of toxic effects of twenty metal oxide nanoparticles on human normal lung epithelial cells (BEAS 2B) and keratinocytes (Hacat) were researched under different biological conditions. For the first time, eleven periodic table-based descriptors (quantitative descriptors) and six experimental condition parameters (qualitative descriptors) were combined to characterize the nanostructure characteristics of metal oxides. Three descriptors, namely metal electronegativity (χ), Hydro Size and Dose, were selected from the above descriptors by the support vector machine-feature recursive elimination (SVM RFE) method to form the optimal feature subset, which was used as input parameters of this study. On this basis, two nano-SAR prediction models were established by using support vector machine (SVM) and random forest (RF) modeling methods respectively. Both accuracy (ACC) of training sets in two models are more than 0. 9, both accuracies of the internal validation are more than 0. 7, and both accuracies of the external validation for the test sets are more than 0. 8. The model validation results show that the combination of periodic table-based descriptors and biological condition parameters can effectively characterize the molecular structure characteristics of metal oxide nanoparticles, and the two models established have good stability and strong prediction ability. The results of the model comparison show that the RF model is superior to the SVM model, and the performance of the RF model is superior to existing models reported in the literature. The results of model mechanism interpretation using the descriptor sensitivity analysis method show that the Hydro Size and electronegativity of metal oxide nanoparticles are the main structural factors affecting their toxicity to both human normal lung epithelial cells (BEAS 2B) and keratinocytes(Hacat), and the smaller the nanoparticle size is, the easier it is to enter the cells. As a scale of the ability of atoms to attract electrons in compounds, electronegativity mainly plays a role in inducing intracellular oxidative stress.
KW - basic disciplines of environmental science and technology
KW - cytotoxicity
KW - metal oxide nanoparticles
KW - model
KW - periodic table-based descriptors
KW - random forest
KW - structure-activity relationship
UR - http://www.scopus.com/inward/record.url?scp=105000866161&partnerID=8YFLogxK
U2 - 10.13637/j.issn.1009-6094.2021.1795
DO - 10.13637/j.issn.1009-6094.2021.1795
M3 - 文章
AN - SCOPUS:105000866161
SN - 1009-6094
VL - 23
SP - 304
EP - 312
JO - Journal of Safety and Environment
JF - Journal of Safety and Environment
IS - 1
ER -