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.

中文翻译：

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从有机化合物的分子特性预测环境中有机化合物的命运：综述


对定量结构-活性关系（QSAR）进行了全面审查，允许根据分子特性预测环境中有机化合物的命运。所考虑的过程包括水的溶解、解离、挥发、土壤和沉积物上的滞留（主要是吸附和解吸）、降解​​（生物和非生物）以及植物的吸收。据报道，总共 790 个方程涉及 686 个结构分子描述符，可估计与这些过程相关的 90 个环境参数。发现了大量关于解离过程 (pKa)、水溶解或疏水行为（特别是通过 KOW 参数）、土壤吸附和生物降解的方程。观察到缺乏 QSAR 来估计解吸或转移到水中的潜力。在 686 个分子描述符中，发现 5 个在 790 个收集的方程和最通用的方程中占主导地位：四个量子化学描述符、最高占据分子轨道 (EHOMO) 的能量和最低未占据分子轨道的能量 ( ELUMO）、极化率（α）和偶极矩（μ），以及一种组成描述符，即分子量。请记住，属于不同类别（构成、拓扑、量子化学）的描述符的组合可以提高 QSAR 性能，因此应考虑使用这些描述符来开发新的 QSAR，以进一步预测环境参数。该综述还可以找到相关的 QSAR 方程来预测环境中多种化合物的命运。