title: Computer-based QSARs for predicting mixture toxicity of benzene and its derivatives.
abstract: During the past decades, the Quantitative structure-activity relationships (QSARs) have been proven to be reliable tools when little or no empirical data are available in medicinal chemistry, biochemistry, toxicology, and environmental sciences. However, only few studies that quantitatively predict mixtures toxicity have been reported. In this study, the QASR models for the binary mixtures toxicity of 12 benzene and its derivatives, including eight non-polar-narcotic compounds and four polar narcotic compounds were developed, without reference to exact toxicity mechanisms of single compounds. All parameters for the QSAR studies were defined on the basis of quantum mechanical calculations and these parameters were selected by the stepwise procedure. The results of this study provided a simple means of predicting the binary mixtures toxicity from the chemical structure.
authors.affiliation: College of Resources and Environment Science, Wuhan University, Wuhan 430072, PR China.
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.forename: Pei-Jiang
authors.initials: PJ
authors.lastname: Zhou
authors.forename: Feng
authors.initials: F
authors.lastname: Yang
authors.forename: Zhen-Dong
authors.initials: ZD
authors.lastname: Wang
mesh_terms: D001554:Benzene / Q000633:toxicity*; D001555:Benzene Derivatives / Q000633:toxicity*; D003198:Computer Simulation; D004338:Drug Combinations; D009294:Narcotics / Q000633:toxicity; D010776:Photobacterium / Q000187:drug effects*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D001555:Benzene Derivatives; D004338:Drug Combinations; D009294:Narcotics; D001554:Benzene