Suppr超能文献

受体介导的环境毒性现象的计算机模拟预测——在内分泌干扰中的应用

In silico prediction of receptor-mediated environmental toxic phenomena-application to endocrine disruption.

作者信息

Lill M A, Dobler M, Vedani A

机构信息

Biographics Laboratory 3R, Friedensgasse 35, 4056 Basel, Switzerland.

出版信息

SAR QSAR Environ Res. 2005 Feb-Apr;16(1-2):149-69. doi: 10.1080/10629360412331319826.

Abstract

It is an objective of our institution to establish a virtual laboratory allowing for a reliable in silico estimation of the harmful effects triggered by drugs, chemicals and their metabolites. In the recent past, we have developed the underlying technology (Multi-dimensional QSAR: Quasar and Raptor) and compiled a pilot system including the 3D models of three receptors known to mediate endocrine-disrupting effects (the aryl hydrocarbon receptor, the estrogen receptor and the androgen receptor, respectively) and validated them against 310 compounds (drugs, chemicals, toxins). Within this set up we could demonstrate that our concepts are able to both recognize toxic compounds substantially different from those used in the training set as well as to classify harmless compounds clearly as being non-toxic. This suggests that our approach can be used for the prediction of adverse effects of drug molecules and chemicals.

摘要

我们机构的目标是建立一个虚拟实验室,以便对药物、化学物质及其代谢产物引发的有害影响进行可靠的计算机模拟评估。最近,我们开发了基础技术(多维定量构效关系:Quasar和Raptor),并编制了一个试点系统,其中包括已知介导内分泌干扰效应的三种受体的三维模型(分别为芳烃受体、雌激素受体和雄激素受体),并针对310种化合物(药物、化学物质、毒素)对其进行了验证。在此设置下,我们能够证明我们的概念既能够识别与训练集中使用的化合物有很大不同的有毒化合物,也能够将无害化合物明确分类为无毒。这表明我们的方法可用于预测药物分子和化学物质的不良反应。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验