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与皮肤致敏相关的肽反应性:将定量构效关系工具箱和TIMES与直接肽反应性测定法进行比较。

Peptide reactivity associated with skin sensitization: The QSAR Toolbox and TIMES compared to the DPRA.

作者信息

Urbisch D, Honarvar N, Kolle S N, Mehling A, Ramirez T, Teubner W, Landsiedel R

机构信息

BASF SE, Experimental Toxicology and Ecology, Ludwigshafen, Germany.

BASF Personal Care and Nutrition GmbH, Düsseldorf, Germany.

出版信息

Toxicol In Vitro. 2016 Aug;34:194-203. doi: 10.1016/j.tiv.2016.04.005. Epub 2016 Apr 14.

Abstract

The molecular initiating event (MIE) of skin sensitization is the binding of a hapten to dermal proteins. This can be assessed using the in chemico direct peptide reactivity assay (DPRA) or in silico tools such as the QSAR Toolbox and TIMES SS. In this study, the suitability of these methods was analyzed by comparing their results to in vivo sensitization data of LLNA and human studies. Compared to human data, 84% of non-sensitizers and sensitizers yielded consistent results in the DPRA. In silico tools resulted in 'no alert' for 83%-100% of the non-sensitizers, but alerted only 55%-61% of the sensitizers. The inclusion of biotic and abiotic transformation simulations yielded more alerts for sensitizers, but simultaneously dropped the number of non-alerted non-sensitizers. In contrast to the DPRA, in silico tools were more consistent with results of the LLNA than human data. Interestingly, the new "DPRA profilers" (QSAR Toolbox) provided unsatisfactory results. Additionally, the results were combined in the '2 out of 3' prediction model with in vitro data derived from LuSens and h-CLAT. Using DPRA results, the model identified 90% of human sensitizers and non-sensitizers; using in silico results (including abiotic and biotic activations) instead of DPRA results led to a comparable high predictivity.

摘要

皮肤致敏的分子起始事件(MIE)是半抗原与皮肤蛋白质的结合。这可以使用化学直接肽反应性测定法(DPRA)或诸如QSAR Toolbox和TIMES SS等计算机工具进行评估。在本研究中,通过将这些方法的结果与LLNA体内致敏数据和人体研究结果进行比较,分析了这些方法的适用性。与人体数据相比,84%的非致敏剂和致敏剂在DPRA中产生了一致的结果。计算机工具对83%-100%的非致敏剂给出了“无警示”结果,但仅对55%-61%的致敏剂发出了警示。纳入生物和非生物转化模拟对致敏剂产生了更多警示,但同时未发出警示的非致敏剂数量减少。与DPRA不同,计算机工具与LLNA的结果比与人体数据更一致。有趣的是,新的“DPRA分析器”(QSAR Toolbox)给出的结果不尽人意。此外,这些结果与来自LuSens和h-CLAT的体外数据一起纳入了“三选二”预测模型。使用DPRA结果,该模型识别出了90%的人体致敏剂和非致敏剂;使用计算机结果(包括非生物和生物激活)而非DPRA结果也产生了相当高的预测性。

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