A COSMO-RS descriptor (Sσ-profile) has been used in quantitative structure–activity relationship studies (QSARs) based on a neural network for the prediction of the toxicological effect of ionic liquids (ILs) on a leukemia rat cell line (LogEC50 IPC-81) for a wide variety of compounds including imidazolium, pyridinium, ammonium, phosphonium, pyrrolidinium and quinolinium ILs. Sσ-profile is a two-dimensional quantum-chemical parameter capable of characterising the electronic structure and molecular size of cations and anions. By using a COSMO-RS descriptor for a training set of 105 compounds (96 ILs and 9 closely related salts) with known biological activities (experimental LogEC50 IPC-81 values), a reliable neural network was designed for the systematic analysis of the influence of structural IL elements (cation side chain, head group, anion type and the presence of functional groups) on the cytotoxicity of ∼450 IL compounds. The Quantitative Structure–Activity Map (QSAM), a new concept developed here, was proposed as a valuable tool for (i) the molecular understanding of IL toxicity, by relating Log EC50 IPC-81 parameters to the electronic structure of compounds given by quantum-chemical calculations; and (ii) the sustainable design of IL products with low toxicity, by linking the chemical structure of counterions to the predictions of IL cytotoxicity in handy contour plots. As a principal contribution, quantum-chemical-based QSAM guides allow the analysis/quantification of the non-linear mixture effects of the toxicophores constituting the IL structures. Based on these favorable results, the QSAR model was applied to estimate IL cytotoxicities in order to screen commercially available compounds with comparatively low toxicities.
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