Doctoral Degree Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Department and Graduate Institute of Veterinary Medicine, School of Veterinary Medicine, National Taiwan University, Taipei, 106, Taiwan.
Regul Toxicol Pharmacol. 2021 Feb;119:104815. doi: 10.1016/j.yrtph.2020.104815. Epub 2020 Nov 4.
Preservatives play a vital role in cosmetics by preventing microbiological contamination for keeping products safe to use. However, a few commonly used preservatives have been suggested to be neurotoxic. Cytotoxicity to neuronal cells is commonly used as the first-tier assay for assessing chemical-induced neurotoxicity. Given the time and resources required for chemical screening, computational methods are attractive alternatives over experimental approaches in prioritizing chemicals prior to further experimental evaluations. In this study, we developed a Quantitative Structure-Activity Relationships (QSAR) model for the identification of potential neurotoxicants. A set of 681 chemicals was utilized to construct a robust prediction model using oversampling and Random Forest algorithms. Within a defined applicability domain, the independent test on 452 chemicals showed a high accuracy of 87.7%. The application of the model to 157 preservatives identified 15 chemicals potentially toxic to neuronal cells. Three of them were further validated by in vitro experiments. The results suggested that further experiments are desirable for assessing the neurotoxicity of the identified preservatives with potential neuronal cytotoxicity.
防腐剂在化妆品中起着至关重要的作用，可防止微生物污染，确保产品安全使用。然而，有几种常用的防腐剂已被认为具有神经毒性。神经细胞的细胞毒性通常被用作评估化学诱导神经毒性的第一级测定。鉴于化学筛选所需的时间和资源，在进一步的实验评估之前，计算方法比实验方法更具吸引力，可用于优先考虑化学品。在这项研究中，我们开发了一种定量构效关系 (QSAR) 模型，用于识别潜在的神经毒物。使用过采样和随机森林算法，利用 681 种化学物质构建了一个稳健的预测模型。在定义的适用域内，对 452 种化学物质的独立测试显示出 87.7%的高准确性。将该模型应用于 157 种防腐剂，鉴定出 15 种可能对神经元细胞有毒的化学物质。其中三种化学物质通过体外实验进一步验证。结果表明，对于具有潜在神经细胞毒性的鉴定防腐剂的神经毒性，需要进一步进行实验评估。
