毒性杂质的预测研究策略

发布时间：2018-04-26 02:19

本文选题：药物 + 杂质　；参考：《中国新药杂志》2015年12期

【摘要】：对药物中杂质化合物的毒性预测研究方法包括警示结构、Ames试验、计算机辅助预测方法和斑马鱼快速评价方法等。具有警示结构的化合物主要有芳香族化合物、烷烃和环烷烃化合物及杂原子化合物等;具有基因毒性的化合物在Ames试验中会使鼠伤寒沙门氏细菌产生回复突变,从而有可见菌落产生;计算机辅助预测包括定量构效关系(Quantity Structure-Activity Relationship,QSAR)和数据库软件系统的使用,都是以化合物化学结构、分子结构参数和化合物的生物活性或效应之间关系为基础,通过QSAR模型或TOPKAT,TOXNET等毒理学数据库而预测杂质化合物的毒理学特性;斑马鱼模型有助于快速实现高通量和高内涵药物筛选。使用警示结构、Ames试验、计算机辅助预测及斑马鱼模型对杂质的毒性进行预测评估,可以节约药物研发成本,缩短研发周期,将会在药物研发领域发挥越来越重要的作用。
[Abstract]:The methods for predicting the toxicity of impurity compounds in drugs include the warning structure Ames test, the computer-aided prediction method and the rapid evaluation method of zebrafish, etc. Compounds with warning structures include mainly aromatic compounds, alkanes and cycloalkanes, and hetero-atomic compounds; compounds with genetic toxicity can cause the salmonella typhimurium to mutate in the Ames test. Thus visible colonies are produced; Computer-Aided Prediction includes quantitative structure-activity relationships (QSARs) and the use of database software systems based on the relationship between chemical structure of compounds, molecular structural parameters and biological activities or effects of compounds. The toxicological characteristics of impurity compounds were predicted by QSAR model or TOPKATT TOXNET, and zebrafish model was helpful for rapid screening of high-throughput and high-connotation drugs. The use of Ames test, computer-aided prediction and zebrafish model to predict the toxicity of impurities can save the cost of drug development, shorten the research and development cycle, and will play an increasingly important role in the field of drug development.
【作者单位】：河南大学药学院;天津药物研究院;天津中医药大学;
【基金】：国家“重大新药创制”科技重大专项(2009ZX09313-026)
【分类号】：R994.1

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