title: Interspecies quantitative structure-toxicity-toxicity (QSTTR) relationship modeling of ionic liquids. Toxicity of ionic liquids to V. fischeri, D. magna and S. vacuolatus.
abstract: Considering the increasing uses of ionic liquids (ILs) in various industrial processes and chemical engineering operations, a complete assessment of their hazardous profile is essential. In the absence of adequate experimental data, in silico modeling might be helpful in filling data gaps for the toxicity of ILs towards various ecological indicator organisms. Using the rationale of taxonomic relatedness, the development of predictive quantitative structure-toxicity-toxicity relationship (QSTTR) models allows predicting the toxicity of ILs to a particular species using available experimental toxicity data towards a different species. Such studies may employ, along with the available experimental toxicity data to a species, molecular structure features and physicochemical properties of chemicals as independent variables for prediction of the toxicity profile against another closely related species. A few such interspecies toxicity correlation models have been reported in the literature for diverse chemicals in general, but this approach has been rarely applied to the class of ionic liquids. The present study involves the use of IL toxicity data towards the bacteria Vibrio fischeri along with molecular structure derived information or computational descriptors like extended topochemical atom (ETA) indices, quantum topological molecular similarity (QTMS) descriptors and computed lipophilicity measure (logk0) for the interspecies exploration of the toxicity data towards green algae S. vacuolatus and crustacea Daphnia magna, separately. This modeling study has been performed in accordance with the OECD guidelines. Finally, predictions for a true external set have been performed to fill the data gap of toxicity towards daphnids and algae using the Vibrio toxicity data and molecular structure attributes.
authors.affiliation: Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.
authors.forename: Rudra Narayan
authors.initials: RN
authors.lastname: Das
authors.affiliation: Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India; Manchester Institute of Biotechnology, 131 Princess Street, Manchester M1 7DN, UK. Electronic address: kroy@pharma.jdvu.ac.in.
authors.forename: Kunal
authors.initials: K
authors.lastname: Roy
authors.affiliation: Manchester Institute of Biotechnology, 131 Princess Street, Manchester M1 7DN, UK. Electronic address: paul.popelier@manchester.ac.uk.
authors.forename: Paul L A
authors.initials: PL
authors.lastname: Popelier
mesh_terms: D048908:Aliivibrio fischeri / Q000187:drug effects*; D000818:Animals; D000460:Chlorophyta / Q000187:drug effects*; D003621:Daphnia / Q000187:drug effects*; D054750:Ecotoxicology; D004785:Environmental Pollutants / Q000737:chemistry / Q000633:toxicity*; D052578:Ionic Liquids / Q000737:chemistry / Q000633:toxicity*; D008962:Models, Theoretical; D021281:Quantitative Structure-Activity Relationship; D013045:Species Specificity
chemical_list: D004785:Environmental Pollutants; D052578:Ionic Liquids
keywords: Ecotoxicological assessment; Interspecies correlation; Ionic liquids; QSTTR; Toxicity data gap