QSAR模型预测石化废水中芳香族物质对厌氧菌群的综合毒性
QSAR Modelling for Predicting Comprehensive Toxicity of Aromatic Substances to Anaerobic Microflora in Petrochemical Wastewater
-
摘要: 厌氧消化可有效降解芳香化合物,但其浓度对厌氧微生物活性影响显著,从而引起出水水质的波动。为预测芳香化合物对厌氧微生物的毒性作用,采用厌氧微生物毒理试验,以芳香化合物48 h半数效应浓度(48 h-EC50)值为样本,基于理化和量子化学结构描述符,利用多元逐步线性回归(multiple stepwise linear regression,MSLR)建立了芳香化合物对厌氧微生物抑制效应的定量构效关系(quantitative structure activity relationship,QSAR)模型。结果表明,芳香化合物对厌氧微生物的毒性影响与正辛醇/水分配系数(logKow)、摩尔折射率(MR)以及分子偶极矩(μ)有关,确定系数(R2)为0.928,三者对模型的贡献程度分别为51.30%、27.63%和21.07%。芳香化合物毒性与logKow和MR相关性显著(r2分别为0.8105和0.7128)。Abstract: The comprehensive toxicity of aromatic compounds during the anaerobic digestion of petrochemical wastewater was investigated by quantitative structure activity relationship (QSAR). The aromatic compounds from petrochemical wastewater stream were regarded to be significantly degraded through the active anaerobic microorganisms, though its high concentration caused the effect fluctuation of anaerobic digestion process on water quality of effluent. To understand the aromatic compound toxicity to anaerobic microorganisms, the toxicological method of anaerobic microorganisms was conducted by sampling 48 h median effect concentration (48 h-EC50) of aromatic compounds. Based on physicochemical and quantum chemical structure descriptors, the QSAR model about aromatic compounds was carried out by the multiple stepwise linear regression (MSLR). The inhibitions of aromatic compounds on the anaerobic microorganisms were predicted by the model with relating the parameters of the octanol water partition coefficient (logKow), the molar refractive index (MR) and the molecular dipole moment (μ). The results showed that R2 (coefficient of determination) was 0.928 and contributions of model parameters were 51.30%, 27.63% and 21.07% respectively. According to the acceptable criteria, the model indicated with high goodness-of-fit and robustness. Besides, the toxicity of aromatic compounds was correlated with logKow and MR significantly (r2 was 0.8105 and 0.7128 respectively).
-
Key words:
- aromatic compounds /
- anaerobic microorganism /
- comprehensive toxicity /
- QSAR /
- petrochemical wastewater
-
-
Hu J, Liu C Q, Zhang G P, et al. Distribution characteristics and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in the Liao River drainage basin, northeast China[J]. Environmental Monitoring and Assessment, 2016, 188(4):227 Johnson W, Idowu I, Francisco O, et al. Enumeration of the constitutional isomers of environmentally relevant substituted polycyclic aromatic compounds[J]. Chemosphere, 2018, 202:9-16 Fujita M, Lévêque J M, Komatsu N, et al. Sono-bromination of aromatic compounds based on the ultrasonic advanced oxidation processes[J]. Ultrasonics Sonochemistry, 2015, 27:247-251 Li Y J, Tabassum S, Yu Z J, et al. Effect of effluent recirculation rate on the performance of anaerobic bio-filter treating coal gasification wastewater under co-digestion conditions[J]. RSC Advances, 2016, 6(91):87926-87934 李雅秋, 王旗. 构建用于预测中药化学成分心脏毒性的定量构效关系模型[J]. 北京大学学报:医学版, 2017, 49(3):551-556 Li Y Q, Wang Q. Quantitative structure-activity relationship model for prediction of cardiotoxicity of chemical components in traditional Chinese medicines[J]. Journal of Peking University:Health Sciences, 2017, 49(3):551-556(in Chinese)
陈璋, 陶雪琴, 谢莹莹, 等. 土壤中多环芳烃微生物降解活性定量构效关系[J]. 科学技术与工程, 2017, 17(27):328-332 Chen Z, Tao X Q, Xie Y Y, et al. QSAR model for predicting biodegradation of PAHs in soils[J]. Science Technology and Engineering, 2017, 17(27):328-332(in Chinese)
American Public Health Association American. Standard methods for the examination of water and wastewater[R]. American Public Health Association, American Water Works Association & Water Pollution Control Federation, 2005 王治军, 王伟. 热水解预处理改善污泥的厌氧消化性能[J]. 环境科学, 2005, 26(1):70-73 Wang Z J, Wang W. Enhancement of sewage sludge anaerobic digestibility by thermal hydrolysis pretreatment[J]. Environmental Science, 2005, 26(1):70-73(in Chinese)
李娟英, 高峰, 陈洁, 等. 酚类化合物对发光细菌的急性毒性和对ETS的抑制研究[J]. 上海海洋大学学报, 2010, 19(1):111-115 Li J Y, Gao F, Chen J, et al. Inhibition of phenol and its derivatives on dehydrogenase activity and luminescent bacteria biotoxicity[J]. Journal of Shanghai Ocean University, 2010, 19(1):111-115(in Chinese)
赵丽. 有毒难降解物质对活性污泥毒性的研究[D]. 石家庄:河北科技大学, 2014:31-32 Zhao L. Study on toxicity to activated sludge of toxic refractory material[D]. Shijiazhuang:Hebei University of Science and Technology, 2014:31 -32(in Chinese)
裴洪平, 许高金. 量子化学参数用于苯胺类化合物的QSAR毒性研究[J]. 浙江大学学报:理学版, 2003, 30(3):310-313 Pei H P, Xu G J. Quantum chemistry parameters in QSAR toxicity studies of anilines[J]. Journal of Zhejiang University:Sciences Edition, 2003, 30(3):310-313(in Chinese)
Gupta S, Basant N, Mohan D, et al. Modeling the reactivities of hydroxyl radical and ozone towards atmospheric organic chemicals using quantitative structure-reactivity relationship approaches[J]. Environmental Science and Pollution Research International, 2016, 23(14):14034-14046 Li C, Zheng S S, Li T T, et al. Quantitative structure-activity relationship models for predicting reaction rate constants of organic contaminants with hydrated electrons and their mechanistic pathways[J]. Water Research, 2019, 151:468-477 Xiao R Y, Ye T T, Wei Z S, et al. Quantitative structure-activity relationship (QSAR) for the oxidation of trace organic contaminants by sulfate radical[J]. Environmental Science & Technology, 2015, 49(22):13394-13402 Rahimi-Nasrabadi M, Akhoondi R, Pourmortazavi S M, et al. Predicting adsorption of aromatic compounds by carbon nanotubes based on quantitative structure property relationship principles[J]. Journal of Molecular Structure, 2015, 1099:510-515 陆伟峰, 杨殿海, 蔡碧婧. 定量构效模型预测苯系物对活性污泥的生物毒性[J]. 工业用水与废水, 2009, 40(3):33-37 Lu W F, Yang D H, Cai B J. Predicting bio-toxicity of benzene and its derivatives to activated sludge by QSARs model[J]. Industrial Water & Wastewater, 2009, 40(3):33-37(in Chinese)
曹森, 曾亚威, 李志明. 大环内酯化合物细胞毒性的定量构效关系研究[J]. 海峡药学, 2016, 28(10):19-23 Cao S, Zeng Y W, Li Z M. QSAR of macrolide compound cytotoxicity[J]. Strait Pharmaceutical Journal, 2016, 28(10):19-23(in Chinese)
Tropsha A, Gramatica P, Gombar V. The importance of being earnest:Validation is the absolute essential for successful application and interpretation of QSPR models[J]. QSAR & Combinatorial Science, 2003, 22(1):69-77 Su H R, Yu C Y, Zhou Y F, et al. Quantitative structure-activity relationship for the oxidation of aromatic organic contaminants in water by TAML/H2O2[J]. Water Research, 2018, 140:354-363 Velázquez-Libera J L, Rossino G, Navarro-Retamal C, et al. Docking, interaction fingerprint, and three-dimensional quantitative structure-activity relationship (3D-QSAR) of Sigma1 receptor ligands, analogs of the neuroprotective agent RC-33[J]. Frontiers in Chemistry, 2019, 7:496 李钦玲, 杨玉良, 张升书. 氯代有机化合物的结构与发光菌毒性的定量构效关系[J]. 河南师范大学学报:自然科学版, 2016, 44(3):79-84 Li Q L, Yang Y L, Zhang S S. QSAR between structure and the acute toxicity to Photobacterium phosphoreum of chlorinated organic compounds[J]. Journal of Henan Normal University:Natural Science Edition, 2016, 44(3):79-84(in Chinese)
-

计量
- 文章访问数: 2060
- HTML全文浏览数: 2060
- PDF下载数: 97
- 施引文献: 0