Cytotoxicity estimation of ionic liquids based on their effective structural features

Cytotoxicity of a diverse set of 227 ionic liquids (taken from UFT/Merck Ionic Liquids Biological Effects Database) containing 94 imidazolium, 53 pyridinium, 23 pyrrolidinium, 22 ammonium, 15 piperidinium, 10 morpholinium, 5 phosphanium, and 5 quinolinium cations in combination with 25 different types of anions to Leukemia Rat Cell Line (IPC-81) was estimated from their structural parameters using quantitative structure – toxicity relationship “QSTR” methodology. Linear and nonlinear models were developed using genetic algorithm (GA), multiple linear regressions (MLR) and multilayer perceptron neural network (MLP NN) approaches. Robustness and reliability of the constructed models were evaluated through internal and external validation methods. Furthermore, chemical applicability domain was determined via leverage approach. In this work, it was revealed that the cationic moieties make the major contribution to cytotoxicity and the anionic parts play a secondary role in cytotoxicity of the ionic liquids studied here. Structural information represented in this work, can be used for a rational design of safer ILs.

► QSTR models are constructed on the basis of a large training set of 182 compounds. ► k-mean cluster algorithm shows a high capability for data set splitting. ► The anion effects are assessed considering more than 20 different types of anions.