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The aim of this work was to develop a simple and easy-to-apply model to predict the pH values of deep eutectic solvents (DESs) over a wide range of pH values that can be used in daily work. For this purpose, the pH values of 38 different DESs were measured (ranging from 0.36 to 9.31) and mathematically interpreted. To develop mathematical models, DESs were first numerically described using σ profiles generated with the COSMOtherm software. After the DESs’ description, the following models were used: (i) multiple linear regression (MLR), (ii) piecewise linear regression (PLR), and (iii) artificial neural networks (ANNs) to link the experimental values with the descriptors. Both PLR and ANN were found to be applicable to predict the pH values of DESs with a very high goodness of fit (R2independent validation > 0.8600). Due to the good mathematical correlation of the experimental and predicted values, the σ profile generated with COSMOtherm could be used as a DES molecular descriptor for the prediction of their pH values.

Tracking osmolyte patterns in biological contexts can help design novel multicomponent deep eutectic systems, which mimic the nuanced microenvironment of biomacromolecules operating within these biological contexts.

Nicotinamide adenine dinucleotide (NAD) coenzyme is a vital part of numerous enzymatic reactions that are involved in all major biological processes from energy metabolism to cell survival. Accordingly, it is...