title: Novel approach for predicting the joint effects based on the enzyme-catalyzed kinetics.
abstract: Organisms are exposed to mixtures of multiple contaminants and it is necessary to build prediction models for the joint effects, considering the high expense and the complexity of the traditional toxicity testing and the flood occurrence of environmental chemical pollutants. In this study, a new method for predicting the joint effects was developed and corresponding prediction models were constructed based on the kinetic models of enzyme-catalyzed reactions. While, we utilized Vibrio fischeri, Escherichia coli and Bacillus subtilis as model organisms and determined the chronic toxicity of the binary mixtures of sulfonamides (SAs) and sulfonamide potentiators (SAPs) (SA+SAP), the mixtures of two kinds of sulfonamides (SA+SA) and the binary mixtures of sulfonamide potentiators (SAPs) and tetracyclines (TCs) (SAP+TC) respectively. Finally, corresponding mixture toxicity data was utilized to fit and verify the prediction models for different joint effects.
authors.affiliation: State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
authors.forename: Min
authors.initials: M
authors.lastname: Zheng
authors.affiliation: State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
authors.forename: Zhifeng
authors.initials: Z
authors.lastname: Yao
authors.affiliation: State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Key Lab of Chemical Assessment and Substainability, Shanghai, China; Collaborative Innovation Center for Regional Environmental Quality, Beijing, China. Electronic address: lzhifen@tongji.edu.cn.
authors.forename: Zhifen
authors.initials: Z
authors.lastname: Lin
authors.affiliation: State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
authors.forename: Shuxia
authors.initials: S
authors.lastname: Fang
authors.affiliation: State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
authors.forename: Chunlei
authors.initials: C
authors.lastname: Song
authors.affiliation: Shanghai Key Lab of Chemical Assessment and Substainability, Shanghai, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
mesh_terms: D048908:Aliivibrio fischeri / Q000187:drug effects / Q000254:growth & development; D000900:Anti-Bacterial Agents / Q000633:toxicity*; D001412:Bacillus subtilis / Q000187:drug effects / Q000254:growth & development; D002384:Catalysis; D004347:Drug Interactions; D004785:Environmental Pollutants / Q000633:toxicity*; D004798:Enzymes / Q000378:metabolism; D004926:Escherichia coli / Q000187:drug effects / Q000254:growth & development; D007700:Kinetics; D008962:Models, Theoretical; D062105:Molecular Docking Simulation; D013449:Sulfonamides / Q000633:toxicity; D013754:Tetracyclines / Q000633:toxicity
chemical_list: D000900:Anti-Bacterial Agents; D004785:Environmental Pollutants; D004798:Enzymes; D013449:Sulfonamides; D013754:Tetracyclines
keywords: Antibiotics; Enzyme-catalyzed kinetics; Joint effects; Prediction approach