重金属对典型水生生物的定量构效关系研究

Quantitative structure-activity relationship (QSAR) has been a powerful tool to predict the effect of organic pollutants, but the relative research of metals, a challenge for toxicity prediction, is still lacking for the complexity of metal speciation. On the basis of existing research, this project herein is to establish a QSAR prediction model for toxicity of metals to model organisms, with respect to metal bioavailability revised by the characteristics of the external environment condition. The orthogonal experiments were performed to evaluate acute or chronic toxic effects of seven metals to 2-3 model organisms; then we estimated novel structure parameters by computational quantum chemistry method and synthesized physic-chemical properties of metal and the characteristics of water chemistry in our country; eventually, a QSAR prediction model for heavy metals were established based on the comprehensive physic-chemical properties of metals and external environmental characteristics in China. These findings will enrich the application of toxicity prediction of heavy metals and their risk assessments, provide a new technology to assess metal toxicity more accurately and efficiently, and become a beneficial supplement to traditional metal toxicology for developing preliminarily screen level toxicities for metals.

定量结构活性相关（QSAR）是有机污染物毒性预测研究的重要手段，但因其形态和生态效应的复杂性，国内外关于金属的QSAR研究不足，依然是国际金属毒性预测的难点和挑战。项目在前期研究进展的基础上，拟开展模式生物定量构效关系的模型预测与实验验证研究。以7种典型重金属为对象，采用批量正交试验对2-3种模式生物的急、慢性毒性进行评估；通过量子化学方法估算重金属结构新参数，构建我国基本水化学条件下耦合的QSAR毒性预测模型。最终，通过模式生物毒性测试对模型进行进一步校正，建立基于综合金属的理化性质和我国环境要素特征的金属毒性预测模型。成果将拓展QSAR在重金属毒性预测和风险评估中的应用研究，为更加准确、高效的金属毒性评价提供新技术，为传统金属毒理学研究提供有益补充。

本课题采用毒性测试、计算机建模和大数据分析相结合的手段，建立了金属理化性质与水生生物毒性之间的定量相关关系，进一步扩展QSAR技术在金属毒性和水生态基准预测中的应用。两方面工作包括：1.构建了海水环境中重金属急、慢性毒性和水质基准预测模型，为一些难以开展实验研究或珍稀水生生物的毒性数据获取和基准推导提供了新途径；2.构建海洋环境中重金属的结构-环境要素-毒性耦合QSAR预测模型，为各地不同水域 “量身定制”海水金属海洋基准，更好保护海洋生态系统。发表SCI论文4篇。两篇论文发表在一区刊物上（IF>6）。申请国际PCT专利1项，发明专利2项。项目支出与预算基本相符，经费结余0.1128万元。