Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review

数量结构-活动关系 分子描述符 化学 轨道能级差 吸附 极化率 计算化学 环境化学 生物系统 溶解 分子 拓扑指数 解吸 化学物理 有机化学 立体化学 生物
作者
Laure Mamy,Dominique Patureau,Enrique Barriuso,Carole Bedos,Fabienne Bessac,Xavier Louchart,Fabrice Martin‐Laurent,Cécile Miège,Pierre Benoît
出处
期刊:Critical Reviews in Environmental Science and Technology [Taylor & Francis]
卷期号:45 (12): 1277-1377 被引量:154
标识
DOI:10.1080/10643389.2014.955627
摘要

A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment.
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