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首页> 外文期刊>Environmental Science and Pollution Research >Discriminating Toxicant Classes by Mode of Action 1. (Eco)toxicity Profiles
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Discriminating Toxicant Classes by Mode of Action 1. (Eco)toxicity Profiles

机译:通过作用方式区分有毒物质类别1.(生态)毒性概况

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Background and Scope. Predictive toxicology, particularly quantitative structure-activity relationships (QSARs), require classification of chemicals by mode of action (MOA). MOA is, however, not a constant property of a compound but it varies between species and may change with concentration and duration of exposure. A battery of MOA-specific in-vitro and low-complexity assays, featuring biomolecular targets for major classes of environmental pollutants, provides characteristic responses for (1.) classification of chemicals by MOA, (2.) identification of (eco)toxicity profiles of chemicals, (3.) identification of chemicals with specific MO As, (4.) indication of most sensitive species, (5.) identification of chemicals that are outliers in QSARs and (6.) selection of appropriate QSARs for predictions. Methods. Chemicals covering nine distinct modes of toxic action (non-polar non-specific toxicants (n=14), polar non-specific toxicants (n=18), uncouplers of oxidative phosphorylation (n=25), inhibitors of photosynthesis (n=15), inhibitors of acetyl-cholinesterase (n=14), inhibitors of respiration (n=3), thiol-alky-lating agents (n=9), reactives (irritants) (n=8), estrogen receptor agonists (n=9)) were tested for cytotoxicity in the neutralred assay, oxygen consumption in isolated mitochondria, oxygen production in algae, inhibition of AChE, reaction with GSH and activity in the yeast estrogen receptor assay. Data on in-vivo aquatic toxicity (LC_(50), EC_(50)) towards fish, daphnids, algae and bacteria were collected from the literature for reasons of comparison and reference scaling. Results and Discussion. In the MOA-specific in-vitro test battery, most test chemicals are specifically active at low concentrations, though multiple effects do occur. Graphical and statistical evaluation of the individual classes versus MOA 1 (non-polar non-specific toxicants) identifies interactions related to predominant MOA. Discriminant analyses (DA) on subsets of the data revealed correct classifications between 70 percent (in-vivo data) and >90 percent (in-vitro data). Functional similarity of chemical substances is defined in terms of their (eco)toxicity profiles. Within each MOA class, the compounds share some properties related to the rate-limiting interactions, e.g., steric fit to the target site and/or reactivity with target biomolecules, revealing a specific pattern (fingerprint) of characteristic effects. Conclusion. The successful discrimination of toxicant classes by MOA is based on comprehensive characterization of test chemicals' properties related to interactions with target sites. The suite of aquatic in-vivo tests using fish, daphnids, algae and bacteria covers most acute effects, whilst long-term (latent) impacts are generally neglected. With the MOA-specific in-vitro test battery such distinctions are futile, because it focuses on isolated targets, i.e. it indicates the possible targets of a chemical regardless of the timescale of effects. The data analysis indicates that the in-vitro battery covers most effects in vivo and moreover provides additional aspects of the compounds' MOA. Recommendation and Perspective. Translating in-vitro effects to in-vivo toxicity requires combining physiological and chemical knowledge about underlying processes. Comparison of the specific in-vitro effects of a compound with the respective sensitivities of aquatic organisms indicates particularly sensitive species. Classifications of toxicants by MOA based on physico-chemical descriptors provides insight to interactions and directs to mechanistic QSARs.
机译:背景和范围。预测毒理学,尤其是定量构效关系(QSAR),需要通过作用方式(MOA)对化学物质进行分类。但是,MOA不是化合物的恒定特性,而是在物种之间变化,并且可能随浓度和暴露时间而变化。一系列MOA特定的体外和低复杂度测定法,具有针对主要类别环境污染物的生物分子靶标,可为(1.)通过MOA对化学物质分类,(2。)鉴定(生态)毒性特征提供特征响应(3.)鉴定具有特定MO As的化学物质,(4。)指示最敏感的物种,(5。)鉴定QSAR中离群值的化学物质,以及(6.)选择合适的QSAR进行预测。方法。化学品涵盖九种不同的毒性作用模式(非极性非特异性毒物(n = 14),极性非特异性毒物(n = 18),氧化磷酸化解偶联剂(n = 25),光合作用抑制剂(n = 15) ),乙酰胆碱酯酶抑制剂(n = 14),呼吸抑制剂(n = 3),硫醇烷基化剂(n = 9),反应物(刺激物)(n = 8),雌激素受体激动剂(n = 9))在中和试验中检测了细胞毒性,在分离的线粒体中消耗了氧气,在藻类中产生了氧气,抑制了AChE,与GSH的反应以及在酵母雌激素受体试验中的活性。由于比较和参考规模的原因,从文献中收集了对鱼类,蚤类,藻类和细菌的体内水生毒性数据(LC_(50),EC_(50))。结果与讨论。在MOA专用的体外测试电池中,大多数测试化学品在低浓度下都具有特定的活性,尽管会产生多种影响。相对于MOA 1(非极性非特异性毒物)对各个类别进行的图形和统计评估确定了与主要MOA相关的相互作用。数据子集的判别分析(DA)显示正确分类介于70%(体内数据)和> 90%(体外数据)之间。化学物质的功能相似性是根据其(生态)毒性特征定义的。在每个MOA类中,这些化合物共有一些与限速相互作用有关的特性,例如与目标位点的空间配合和/或与目标生物分子的反应性,从而揭示了特征作用的特定模式(指纹)。结论。 MOA对毒物类别的成功区分是基于对与目标部位相互作用相关的测试化学品性质的全面表征。使用鱼类,水蚤,藻类和细菌进行的一系列水生体内试验涵盖了大多数急性影响,而长期(潜在)影响通常被忽略。对于MOA专用的体外测试电池,这种区别是徒劳的,因为它着眼于孤立的目标,即无论作用时间长短,它都指示了化学物质的可能目标。数据分析表明,体外电池涵盖了体内大多数作用,而且还提供了化合物MOA的其他方面。建议和观点。将体外效应转化为体内毒性需要结合有关基础过程的生理和化学知识。化合物的特定体外作用与水生生物各自的敏感性的比较表明特别敏感的物种。 MOA根据理化描述符对有毒物质进行分类,从而提供了相互作用的见解,并指导了机械QSAR。

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