title: Ranking of aquatic toxicity of esters modelled by QSAR.
abstract: Alternative methods like predictions based on Quantitative Structure-Activity Relationships (QSARs) are now accepted to fill data gaps and define priority lists for more expensive and time consuming assessments. A heterogeneous data set of 74 esters was studied for their aquatic toxicity, and available experimental toxicity data on algae, Daphnia and fish were used to develop statistically validated QSAR models, obtained using multiple linear regression (MLR) by the OLS (Ordinary Least Squares) method and GA-VSS (Variable Subset Selection by Genetic Algorithms) to predict missing values. An ESter Aquatic Toxicity INdex (ESATIN) was then obtained by combining, by PCA, experimental and predicted toxicity data, from which model outliers and esters highly influential due to their structure had been eliminated. Finally this integrated aquatic toxicity index, defined by the PC1 score, was modelled using only a few theoretical molecular descriptors. This last QSAR model, statistically validated for its predictive power, could be proposed as a preliminary evaluative method for screening/prioritising esters according to their integrated aquatic toxicity, just starting from their molecular structure.
authors.affiliation: Department of Structural and Functional Biology, QSAR and Environmental Chemistry Research Unit, University of Insubria, via Dunant 3, 21100 Varese, Italy.
authors.forename: Ester
authors.initials: E
authors.lastname: Papa
authors.forename: Francesca
authors.initials: F
authors.lastname: Battaini
authors.forename: Paola
authors.initials: P
authors.lastname: Gramatica
mesh_terms: D004952:Esters / Q000737:chemistry / Q000633:toxicity; D016014:Linear Models; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D018675:Toxicity Tests / Q000379:methods*; D014874:Water Pollutants, Chemical / Q000633:toxicity*
chemical_list: D004952:Esters; D014874:Water Pollutants, Chemical