Shin Hyun Kil, Kim Soojin, Yoon Seokjoo
Toxicoinformatics Group, Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea.
Molecular Toxicology Group, Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea.
NanoImpact. 2021 Jan;21:100298. doi: 10.1016/j.impact.2021.100298. Epub 2021 Feb 6.
Due to the lack of nano descriptors that can appropriately represent the wide chemical space of engineered nanomaterials (ENMs), applicability domain of nano-quantitative structure-activity relationship models are limited to certain types of ENMs, such as metal oxides, metals, carbon-based nanomaterials, or quantum dots. In this study, a size-dependent electron configuration fingerprint (SDEC FP) was introduced to estimate the quantity of electrons based on the core, doping, and coating materials of ENMs in different sizes. SDEC FP was used in prediction model development and nanostructure similarity analysis on datasets including metal and carbon-based nanomaterials with and without surface modifications. Cytotoxicity and zeta potential prediction models developed with SDEC FP achieved good prediction accuracies on test set. Nanostructure similarity analysis was performed through principal component analysis which showed that structural similarity between ENMs measured by SDEC FP was highly correlated with their properties.
由于缺乏能够恰当表征工程纳米材料（ENM）广泛化学空间的纳米描述符，纳米定量构效关系模型的适用范围仅限于某些类型的ENM，如金属氧化物、金属、碳基纳米材料或量子点。在本研究中，引入了尺寸依赖电子构型指纹（SDEC FP），以基于不同尺寸ENM的核心、掺杂和包覆材料来估计电子数量。SDEC FP被用于预测模型开发以及对包括有和没有表面修饰的金属和碳基纳米材料的数据集进行纳米结构相似性分析。用SDEC FP开发的细胞毒性和zeta电位预测模型在测试集上取得了良好的预测准确性。通过主成分分析进行了纳米结构相似性分析，结果表明，由SDEC FP测量的ENM之间的结构相似性与其性质高度相关。
