Probing the Environmental Toxicity of Deep Eutectic Solvents and Their Components: An In Silico Modeling Approach

Abstract

Because of the increasing demand of greener solvents, deep eutectic solvents (DES) have just emerged as low-cost alternative solvents for a broad range of applications. However, recent toxicity assay studies showed a non-negligible toxic behavior for these solvents and their components. Alternative in silico-based approaches such as the one proposed here, multitasking-Quantitative Structure Toxicity Relationships (mtk-QSTR), are increasingly used for risk assessment of chemicals to speed up policy decisions. This work reports a mtk-QSTR modeling of 572 DES and their components under multiple experimental conditions. To set up a reliable model from such data, we examined here the use of 0D–2D descriptors along with classification analysis, and the Box–Jenkins approach. This procedure led to a final mtk-QSTR model with high overall accuracy and predictivity (ca. 90%). The model highlights also the crucial role that polarizability, electronegativity, hydrogen-bond donor (HBD), and topological properties play into the DES toxicity. Furthermore, with the help of the derived mtk-QSTR model, 30 different HBD components were ranked on the basis of their toxic contributions to DES. More importantly, the proposed in silico modeling approach is shown to be a valuable tool to mine relevant STR information, therefore guiding the rational design of potentially safe DES.