Computer-aided nanotoxicology: risk assessment of metal oxide nanoparticles via nano-QSAR
Computer-aided nanotoxicology: risk assessment of metal oxide nanoparticles via nano-QSAR
复制标题
计算机辅助纳米毒理学：通过纳米 QSAR 进行金属氧化物纳米粒子的风险评估
DOI：
10.1039/d0gc00933d
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发表时间：
2020-06-07
期刊：
影响因子：
9.8
通讯作者：
Wang, Qingsheng
中科院分区：
文献类型：
--
作者：
Cao, Jiakai;Pan, Yong;Wang, Qingsheng
由于纳米材料的应用已经扩展为治疗方法，在治疗过程中伴随纳米材料的细胞毒性引起了极大的关注。因此，有必要研究不同纳米材料的结构与细胞毒性之间的关系。为了避免逐个案例的测试，应开发将测试方法与非测试预测建模相结合的智能策略。定量构效关系（QSAR）是理解影响金属氧化物（MeOx）纳米颗粒（NPs）效力的性质和预测毒性反应的有前途的工具。在这项工作中，进行了实验和计算相结合的研究，以估计急性细胞毒性和开发预测模型的MeOx纳米颗粒。改进的SMILES为基础的最佳描述符被施加到描述的纳米结构特征的MeOx纳米粒子。在实验的基础上，考虑MeOx纳米颗粒粒径和zeta电位对细胞毒性的影响，建立了4种纳米定量构效关系模型，用于预测MeOx纳米颗粒对人肺腺癌（A549）细胞的半数致死浓度（LC50）。模型具有良好的预测性和鲁棒性。主要的纳米结构特征和机制负责的细胞毒性的MeOx纳米颗粒A549细胞通过模型解释与随后的实验上的活性氧物质（ROS）的MeOx纳米颗粒。所提出的模型可以可靠地预测和评估急性细胞毒性的新型纳米粒子单独从他们的纳米结构，并提供指导，优先设计，合成和制造的安全和绿色纳米材料的预期性能。
Since the application of nanomaterials has expanded as a therapeutic methodology, the cytotoxicity accompanying nanomaterials during the therapeutic process has attracted significant attention. Thus, it is necessary to investigate the relationship between the structure and cytotoxicity of different nanomaterials. To avoid case-by-case testing, intelligent strategies combining testing methods with non-testing predictive modelling should be developed. The quantitative structure–activity relationship (QSAR) is a promising tool in understanding the properties that affect the potency of metal oxide (MeOx) nanoparticles (NPs) and in predicting toxic responses. In this work, a combined experimental and computational study was performed to estimate the acute cytotoxicity and develop predictive models for MeOx NPs. Improved SMILES-based optimal descriptors were applied to describe the nanostructure characteristics of MeOx NPs. Based on the experimental test, four nano-QSAR models were established for predicting the median lethal concentration (LC50) of MeOx NPs to human lung adenocarcinoma (A549) cells by considering the influence of their particle size and zeta potential on cytotoxicity. The models showed satisfactory predictivity and robustness. The predominant nanostructure characteristics and the mechanism responsible for the cytotoxicity of MeOx NPs to A549 cells were identified through model interpretation with subsequent experiments on the reactive oxygen species (ROS) of MeOx NPs. The proposed models can reliably predict and assess the acute cytotoxicity of novel NPs solely from their nanostructures, and provide guidance for prioritising the design, synthesis, and manufacture of safer and green nanomaterials with expected properties.