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QSAR TOXICITY PREDICTION METHOD FOR EVALUATING HEALTH EFFECT OF NANO-CRYSTALLINE METAL OXIDE

机译:纳米晶体金属氧化物健康效应的QSAR毒性预测方法

摘要

A QSAR toxicity prediction method for evaluating the health effects of nano-crystalline metal oxide relates to the field of toxic substance prediction in an environment. Specifically, the method comprises: predicting a toxicity endpoint of unknown metallic oxide according to a quantitative relationship between structural features and cytotoxicity effect of the nano-crystalline metal oxide; and is a method of building a nano-crystalline metal oxide prediction model by combining a physicochemical structure parameter and a special mechanism of toxication of the nano-crystalline metal oxide, and applying the nano-crystalline metal oxide prediction model to predict the unknown toxicity endpoint. Based on a functioning model and a mechanism of toxication of the nano-crystalline metal oxide, a nano-crystalline metal oxide prediction model can be built to predict an unknown toxicity value by means of the QSAR model method, so that the toxicity endpoint prediction of various compounds'lack of toxicity data can be completed quickly and simply with less dependency on experiment testing data.
机译:用于评估纳米晶体金属氧化物对健康的影响的QSAR毒性预测方法涉及环境中有毒物质预测领域。具体地,该方法包括:根据所述纳米晶体金属氧化物的结构特征与细胞毒性作用之间的定量关系,预测未知金属氧化物的毒性终点;并且是通过结合物理化学结构参数和纳米晶体金属氧化物中毒的特殊机理来构建纳米晶体金属氧化物预测模型的方法,并应用该纳米晶体金属氧化物预测模型来预测未知的毒性终点。基于纳米晶体金属氧化物的功能模型和中毒机理,可以通过QSAR模型方法建立纳米晶体金属氧化物的预测模型,以预测未知的毒性值,从而预测毒性终点。各种化合物缺乏毒性的数据可以快速,简单地完成,而对实验测试数据的依赖性较小。

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