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计算机辅助的机理结构-活性研究:应用于各类化学致癌物

Computer-assisted mechanistic structure-activity studies: application to diverse classes of chemical carcinogens.

作者信息

Loew G H, Poulsen M, Kirkjian E, Ferrell J, Sudhindra B S, Rebagliati M

出版信息

Environ Health Perspect. 1985 Sep;61:69-96. doi: 10.1289/ehp.856169.

DOI:10.1289/ehp.856169
PMID:3905382
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1568757/
Abstract

In the first part of this paper we have indicated how the techniques and capabilities of theoretical chemistry, together with experimental results, can be used in a mechanistic approach to structure-activity studies of toxicity. In the second part, we have illustrated how this computer-assisted approach has been used to identify and calculate causally related molecular indicators of relative carcinogenic activity in five classes of chemical carcinogens: polycyclic aromatic hydrocarbons and their methyl derivatives, aromatic amines, chloroethanes, chloroalkenes and dialkyl nitrosamines. In each class of chemicals studied, candidate molecular indicators have been identified that could be useful in predictive screening of unknown compounds. In addition, further insights into some mechanistic aspects of chemical carcinogenesis have been obtained. Finally, experiments have been suggested to both verify the usefulness of the indicators and test their mechanistic implications.

摘要

在本文的第一部分,我们已经指出理论化学的技术和能力,连同实验结果,如何能够用于一种机理方法来进行毒性的构效关系研究。在第二部分,我们已经阐明这种计算机辅助方法如何被用于识别和计算五类化学致癌物中相对致癌活性的因果相关分子指标:多环芳烃及其甲基衍生物、芳香胺、氯乙烷、氯烯烃和二烷基亚硝胺。在所研究的每一类化学物质中,已经识别出可能有助于对未知化合物进行预测性筛选的候选分子指标。此外,还获得了对化学致癌作用一些机理方面的进一步认识。最后,已经提出了实验以验证这些指标的有用性并检验其机理含义。

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Computer-assisted mechanistic structure-activity studies: application to diverse classes of chemical carcinogens.计算机辅助的机理结构-活性研究:应用于各类化学致癌物
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Computer-assisted structure-activity studies of chemical carcinogens. Aromatic amines.化学致癌物的计算机辅助构效关系研究。芳香胺类。
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Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.应用 CP ANN 方法对非同类化学物质进行致癌性定量和定性预测的定量和定性模型,以供监管用途。
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