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

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.