Wei Jiajia, Tian Lei, Nie Fan, Shao Zhiguo, Wang Zhansheng, Xu Yu, He Mei
State Key Laboratory of Petroleum Pollution Control, CNPC Research Institute of Safety and Environmental Technology Co., Ltd, Beijing, 102206, China.
Hubei Key Laboratory of Petroleum Geochemistry and Environment (Yangtze University), Wuhan, 430100, China.
Heliyon. 2024 Feb 28;10(5):e26808. doi: 10.1016/j.heliyon.2024.e26808. eCollection 2024 Mar 15.
Quantitative structure-activity relationship (QSAR) is a cost-effective solution to directly and accurately estimating the environmental safety thresholds (ESTs) of pollutants in the ecological risk assessment due to the lack of toxicity data. In this study, QSAR models were developed for estimating the Predicted No-Effect Concentrations (PNECs) of petroleum hydrocarbons and their derivatives (PHDs) under dietary exposure, based on the quantified molecular descriptors and the obtained PNECs of 51 PHDs with given acute or chronic toxicity concentrations. Three high-reliable QSAR models were respectively developed for PHDs, aromatic hydrocarbons and their derivatives (AHDs), and alkanes, alkenes and their derivatives (ALKDs), with excellent fitting performance evidenced by high correlation coefficient (0.89-0.95) and low root mean square error (0.13-0.2 mg/kg), and high stability and predictive performance reflected by high internal and external verification coefficient (Q, 0.66-0.89; Q, 0.62-0.78; Q, 0.60-0.73). The investigated quantitative relationships between molecular structure and PNECs indicated that 18 autocorrelation descriptors, 3 information index descriptors, 4 barysz matrix descriptors, 6 burden modified eigenvalues descriptors, and 1 BCUT descriptor were important molecular descriptors affecting the PNECs of PHDs. The obtained results supported that PNECs of PHDs can be accurately estimated by the influencing molecular descriptors and the quantitative relationship from the developed QSAR models, that provided a new feasible solution for ESTs derivation in the ecological risk assessment.
由于缺乏毒性数据,定量构效关系(QSAR)是一种经济高效的解决方案,可直接准确地估计生态风险评估中污染物的环境安全阈值(EST)。在本研究中,基于定量分子描述符和51种具有给定急性或慢性毒性浓度的石油烃及其衍生物(PHD)的预测无效应浓度(PNEC),开发了QSAR模型,用于估计饮食暴露下石油烃及其衍生物的PNEC。分别为PHD、芳烃及其衍生物(AHD)以及烷烃、烯烃及其衍生物(ALKD)开发了三个高度可靠的QSAR模型,其具有优异的拟合性能,相关系数高(0.89 - 0.95)且均方根误差低(0.13 - 0.2 mg/kg),同时具有高稳定性和预测性能,内部和外部验证系数高(Q,0.66 - 0.89;Q,0.62 - 0.78;Q,0.60 - 0.73)。研究的分子结构与PNEC之间的定量关系表明,18个自相关描述符、3个信息指数描述符、4个巴里斯矩阵描述符、6个负担修正特征值描述符和1个BCUT描述符是影响PHD的PNEC的重要分子描述符。所得结果支持通过影响分子描述符和所开发的QSAR模型的定量关系可以准确估计PHD的PNEC,这为生态风险评估中的EST推导提供了一种新的可行解决方案。