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 (R²_{independent 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.

While exaptation is most impressive when links between very dissimilar contexts are established, it can be even more pervasive when the previously unestablished connection seems surprisingly obvious in retrospect. We herein established such a connection between two major research fields previously advancing in parallel: osmolytes and deep eutectic solvents. Osmolytes are small molecules produced in cells as a response to external stimuli. Based on their individual interaction with macromolecules, single osmolytes are currently categorized as “kosmotropes” (stabilizing proteins) and “chaotropes” (destabilizing them). However, with two or more osmolytes, synergistic effects were also observed on top of cumulative ones. All current attempts to explain these synergistic effects have been studying osmolyte–osmolyte interactions in aqueous solutions, but none has been generally applicable so far, indicating that a new model “beyond kosmotropes and chaotropes” is needed to understand the function of osmolytes. We have gathered enough evidence to formulate a hypothesis of such a new model. First, inspired by patterns frequently observed in nature, five major stabilizing osmolytes (kosmotropes) prominent across kingdoms (trimethylamine N-oxide, sarcosine, glycerophosphorylcholine, dimethylsulfoniopropionate and ectoine) were for the first time employed to form novel two- and three-component DESs with all known natural perturbants/chaotropes (urea, guanidine hydrochloride and arginine). Going beyond the current three-component barrier, we mimicked the exact composition of multi-osmolyte cocktails widely observed in nature and we here report the rapid and consistent formation of deep eutectic systems of unprecedented complexity and the tunable potential of these new systems to stabilize a template protein. Based on these observations, we postulate that, in vivo, osmolytes form deep eutectic systems featuring new, emergent and synergistic properties which govern their interaction with macromolecules. We believe that such bio-inspired, osmolyte-based DESs can be a remarkable new tool to study complex natural systems in higher granularity and to engineer their microenvironment towards efficient and sustainable processes at scale.

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 used in a great number of biocatalytic reactions, as analytical biosensors, and in test kits for diagnostic and analytical purposes. This coenzyme is unstable in aqueous solutions, meaning that the minimization of its degradation during storage, assays, and enzyme-catalysed oxidoreductive reactions is of high importance. Herein, we report on the stabilisation of NAD (NAD⁺ as oxidised, and NADH as its reduced form) by deep eutectic solvents (DES), an emerging class of solvents that offer numerous remarkable advantages such as high tunability, and capability to stabilise a wide range of commercially important compounds of natural origin. Preliminary DES screening revealed that out of 7 candidates, choline chloride:urea (ChCl:U) shows the best ability to stabilise both NAD forms. Computational analysis (quantum chemical calculations and molecular dynamics simulations) provided a deeper insight into possible mechanisms behind the observed stabilisation, by identifying geometries and the solvation structure of NAD coenzymes in these solvents, and analysing their possible degradation pathways. Finally, prolonged NAD stability (up to 50 days) in ChCl:U is detected and the system is further confirmed as a stable working NAD solution in a model enzymatic assay.

Broccoli is rich in biologically active compounds, especially polyphenols and glucosinolates, known for their health benefits. Traditional extraction methods have limitations, leading to a shift towards using natural deep eutectic solvents (NADESs) to create high-quality extracts with enhanced biological activity. This study focuses on preparing broccoli extracts in NADES, enriched with polyphenols and glucosinolates, without additional purification steps. Using the COSMOtherm software, the solubility of polyphenols and glucosinolates in NADESs was predicted, and five biocompatible betaine-based NADESs were prepared with glucose (B:Glc_1:1 and B:Glc_5:2), sucrose (B:Suc), glycerol (B:Gly), and malic acid (B:MA) as hydrogen bond donors. The resulting extracts were assessed for total polyphenol and glucosinolate content, along with antioxidant capacity, using the ORAC assay. The results demonstrated that NADES extracts contained higher polyphenol content and exhibited enhanced antioxidant effects compared to the reference ethanol extract, with B:Glc_1:1 extract showing the highest performance among all the extracts tested. On the other hand, the extract based on B:MA exhibited nearly six times higher total glucosinolate content compared to the ethanol extract. Additionally, polyphenols and glucosinolates were generally more stable in NADES extracts than in the reference solvent. Finally, the B:Glc_1:1 extract, identified as optimal in terms of polyphenol and glucosinolate content and stability, exhibited mild stimulation of HaCaT cells growth and facilitated the wound-healing process. Through green chemistry parameter calculations, we demonstrated that the extraction of broccoli bioactives using B:Glc_1:1 can be considered sustainable, underscoring the potential of NADESs for producing ready-to-use plant extracts.

The most important and commonly used process for biodiesel synthesis is transesterification. The main by-product of biodiesel synthesis by transesterification is glycerol, which must be removed from the final product. Recently, deep eutectic solvent (DES) assisted extraction has been shown to be an effective and sustainable method for biodiesel purification. In this study, biodiesel was produced by lipase-catalysed transesterification from sunflower oil and methanol. A total of 12 different eutectic solvents were prepared and their physical properties were determined. Mathematical models were used to define which physical and chemical properties of DES and to what extent affect the efficiency of extraction of glycerol from the biodiesel. After initial screening, cholinium-based DES with ethylene glycol as hydrogen bond donor was selected and used for optimization of extraction process conditions performed in a microsystem. To determine the optimal process conditions (temperature, biodiesel:DES volume ratio, residence time), the experimental three-level-three-factor Box-Behnken experimental design was used. In the end, a combination of a mathematical model and experimental results was used to estimate how many micro-extractors are necessary for the complete removal of glycerol.

Probiotic lactic acid bacteria are widely recognized for their health-promoting effects. However, the use of live microorganisms may pose safety concerns and stability limitations. Consequently, postbiotics, defined as inactivated microbial cells and/or their components, have emerged as a promising alternative. This study integrates genome-guided evaluation of probiotic potential, experimental validation of in silico predictions and process optimization for the production of inactivated Lactiplantibacillus plantarum DM1 and KK1 cells as postbiotics. Genome mining identified genes and gene clusters associated with metabolic versatility, antimicrobial activity, gastrointestinal stress tolerance, adhesion and prebiotic substrate utilization. Building on these findings, to generate postbiotics, the efficiency of thermal, enzymatic, mechanical and radiation-based inactivation methods was evaluated in bacterial suspensions prepared in three dairy by-product matrices: milk permeate, sweet whey and sour whey. Complete inactivation of both strain cells was achieved by thermal treatment (3 min pasteurization), γ-irradiation (3 kGy), and combined lysozyme–pasteurization treatment, whereas other treatments showed partial and matrix-dependent effects. Matrix composition significantly influenced treatment efficacy, suggesting a protective role of food components used. These findings highlight the importance of combining genome mining for potential probiotic strain characterization with robust, matrix-adapted inactivation strategies for the development of stable postbiotic formulations.