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在ChemScreen项目中对70983种REACH物质进行基因毒性致癌性、诱变性和发育毒性的定量构效关系筛选。

QSAR screening of 70,983 REACH substances for genotoxic carcinogenicity, mutagenicity and developmental toxicity in the ChemScreen project.

作者信息

Wedebye Eva B, Dybdahl Marianne, Nikolov Nikolai G, Jónsdóttir Svava Ó, Niemelä Jay R

机构信息

Division of Toxicology and Risk Assessment, National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, 2860 Søborg, Denmark.

Division of Toxicology and Risk Assessment, National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, 2860 Søborg, Denmark.

出版信息

Reprod Toxicol. 2015 Aug 1;55:64-72. doi: 10.1016/j.reprotox.2015.03.002. Epub 2015 Mar 19.

Abstract

The ChemScreen project aimed to develop a screening system for reproductive toxicity based on alternative methods. QSARs can, if adequate, contribute to the evaluation of chemical substances under REACH and may in some cases be applied instead of experimental testing to fill data gaps for information requirements. As no testing for reproductive effects should be performed in REACH on known genotoxic carcinogens or germ cell mutagens with appropriate risk management measures implemented, a QSAR pre-screen for 70,983 REACH substances was performed. Sixteen models and three decision algorithms were used to reach overall predictions of substances with potential effects with the following result: 6.5% genotoxic carcinogens, 16.3% mutagens, 11.5% developmental toxicants. These results are similar to findings in earlier QSAR and experimental studies of chemical inventories, and illustrate how QSAR predictions may be used to identify potential genotoxic carcinogens, mutagens and developmental toxicants by high-throughput virtual screening.

摘要

化学筛选项目旨在开发一种基于替代方法的生殖毒性筛选系统。如果适用,定量构效关系(QSARs)有助于在《化学品注册、评估、授权和限制法规》(REACH)下对化学物质进行评估,并且在某些情况下可以替代实验测试,以填补信息要求的数据空白。由于在实施了适当风险管理措施的情况下,REACH法规中不应对已知的遗传毒性致癌物或生殖细胞诱变剂进行生殖效应测试,因此对70983种REACH物质进行了QSAR预筛选。使用了16个模型和3种决策算法来对具有潜在影响的物质进行总体预测,结果如下:6.5%为遗传毒性致癌物,16.3%为诱变剂,11.5%为发育毒性物质。这些结果与早期对化学物质清单的QSAR和实验研究结果相似,并说明了如何通过高通量虚拟筛选利用QSAR预测来识别潜在的遗传毒性致癌物、诱变剂和发育毒性物质。

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