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Validation of Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) approaches as alternatives to skin sensitization risk assessment
Journal of Toxicology and Environmental Health, Part A ( IF 2.3 ) Pub Date : 2021-08-01 , DOI: 10.1080/15287394.2021.1956660
Ji Yun Kim 1 , Kyu-Bong Kim 2 , Byung-Mu Lee 1
Affiliation  

ABSTRACT

The aim of this study was conducted to validate the physicochemical properties of a total of 362 chemicals [305 skin sensitizers (212 in the previous study + 93 additional new chemicals), 57 non-skin sensitizers (38 in the previous study + 19 additional new chemicals)] for skin sensitization risk assessment using quantitative structure-activity relationship (QSAR)/quantitative structure-property relationship (QSPR) approaches. The average melting point (MP), surface tension (ST), and density (DS) of the 305 skin sensitizers and 57 non-sensitizers were used to determine the cutoff values distinguishing positive and negative sensitization, and correlation coefficients were employed to derive effective 3-fold concentration (EC3 (%)) values. QSAR models were also utilized to assess skin sensitization. The sensitivity, specificity, and accuracy were 80, 15, and 70%, respectively, for the Toxtree QSAR model; 88, 46, and 81%, respectively, for Vega; and 56, 61, and 56%, respectively, for Danish EPA QSAR. Surprisingly, the sensitivity, specificity, and accuracy were 60, 80, and 64%, respectively, when MP, ST, and DS (MP+ST+DS) were used in this study. Further, MP+ST+DS exhibited a sensitivity of 77%, specificity 57%, and accuracy 73% when the derived EC3 values were classified into local lymph node assay (LLNA) skin sensitizer and non-sensitizer categories. Thus, MP, ST, and DS may prove useful in predicting EC3 values as not only an alternative approach to animal testing but also for skin sensitization risk assessment.



中文翻译:

验证定量结构-活性关系 (QSAR) 和定量结构-性质关系 (QSPR) 方法作为皮肤致敏风险评估的替代方法

摘要

本研究的目的是验证总共 362 种化学物质的理化特性 [305 种皮肤致敏物(先前研究中的 212 种 + 93 种额外的新化学物质)、57 种非皮肤致敏物(先前研究中的 38 种 + 19 种额外的新化学物质)化学品)] 使用定量构效关系(QSAR)/定量结构-性质关系(QSPR)方法进行皮肤致敏风险评估。305种皮肤致敏剂和57种非致敏剂的平均熔点(MP)、表面张力(ST)和密度(DS)被用来确定区分正负致敏的临界值,并通过相关系数得出有效的3 倍浓度 (EC3 (%)) 值。QSAR 模型也用于评估皮肤过敏。灵敏度、特异度和准确度均为 80,Toxtree QSAR 模型分别为 15% 和 70%;Vega 分别为 88、46 和 81%;丹麦 EPA QSAR 分别为 56%、61% 和 56%。令人惊讶的是,当本研究中使用 MP、ST 和 DS(MP+ST+DS)时,灵敏度、特异性和准确度分别为 60%、80% 和 64%。此外,当衍生的 EC3 值被分为局部淋巴结检测 (LLNA) 皮肤致敏物和非致敏物类别时,MP+ST+DS 表现出 77% 的敏感性、57% 的特异性和 73% 的准确度。因此,MP、ST 和 DS 可能被证明可用于预测 EC3 值,不仅可以作为动物试验的替代方法,还可以用于皮肤致敏风险评估。当本研究中使用 MP、ST 和 DS(MP+ST+DS)时,特异性和准确度分别为 60%、80% 和 64%。此外,当衍生的 EC3 值被分为局部淋巴结检测 (LLNA) 皮肤致敏物和非致敏物类别时,MP+ST+DS 表现出 77% 的敏感性、57% 的特异性和 73% 的准确度。因此,MP、ST 和 DS 可能被证明可用于预测 EC3 值,不仅可以作为动物试验的替代方法,还可以用于皮肤致敏风险评估。当本研究中使用 MP、ST 和 DS(MP+ST+DS)时,特异性和准确度分别为 60%、80% 和 64%。此外,当衍生的 EC3 值被分为局部淋巴结检测 (LLNA) 皮肤致敏物和非致敏物类别时,MP+ST+DS 表现出 77% 的敏感性、57% 的特异性和 73% 的准确度。因此,MP、ST 和 DS 可能被证明可用于预测 EC3 值,不仅可以作为动物试验的替代方法,还可以用于皮肤致敏风险评估。

更新日期:2021-09-27
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