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Deep eutectic solvents (DESs) have recently gained increased attention for their potential in biotechnological applications. DESs are binary mixtures often consisting of a hydrogen bond acceptor and a hydrogen bond donor, which allows for tailoring their properties for particular applications. If produced from sustainable resources, they can provide a greener alternative to many traditional organic solvents for usage in various applications (e.g., as reaction environment, crystallization agent, or storage medium). To navigate this large design space, it is crucial to comprehend the behavior of biomolecules (e.g., enzymes, proteins, cofactors, and DNA) in DESs and the impact of their individual components. Molecular dynamics (MD) simulations offer a powerful tool for understanding thermodynamic and transport processes at the atomic level and offer insights into their fundamental phenomena, which may not be accessible through experiments. While the experimental investigation of DESs for various biotechnological applications is well progressed, a thorough investigation of biomolecules in DESs via MD simulations has only gained popularity in recent years. Within this work, we aim to provide an overview of the current state of modeling biomolecules with MD simulations in DESs and discuss future directions with a focus for optimizing the molecular simulations and increasing our fundamental knowledge., Deutsche Forschungsgemeinschaft (DFG)

The origins of different computational artifacts that may occur in the calculation of one-dimensional potentials of mean force (PMF) via umbrella sampling molecular dynamics simulations and manifest as free energy offset between bulk solvent regions are investigated. By systematic studies, three distinct causes are elucidated: (i) an unfortunate choice of reference points for the umbrella distance restraint; (ii) a mis1t in probability distributions between bound and unbound umbrella windows in case of multiple binding modes; (iii) artifacts introduced by the free energy estimator. Starting with a fully symmetric model system consisting of methane binding to a cylindrical host, complexity is increased through the introduction of dipolar interactions between the host and the solvent, the host and the guest molecule or between all involved species, respectively. The manifestation of artifacts is illustrated and their origin and prevention is discussed. Finally, the consequences for the calculation of standard binding free enthalpies is illustrated using the complexation of primary alcohols with Alpha-cyclodextrin as an example., Baden-Württemberg, Ministerium für Wissenschaft, Forschung und Kunst, Deutsche Forschungsgemeinschaft (DFG)

For a knowledge-based design of enzyme catalysis in deep eutectic solvents (DESs), the influence of the DES properties (e.g., water activity and viscosity) and the impact of DESs and their individual components must be assessed. This paper investigates three different DESs: choline chloride-glycerol (ChCl-Gly), choline chloride-ethylene glycol (ChCl-EG), and ethyl ammonium chloride-glycerol (EACl-Gly). The specific activity and half-life time of horse liver alcohol dehydrogenase (HLADH) were experimentally determined in these DESs with water contents ranging from 0%-100%. HLADH showed limited activity in neat DESs, which was enhanced by adding water. Experiments with individual DES components of ChCl-Gly were carried out to clarify their individual influence. Glycerol acts as a strong stabilizer for the enzyme, whereas choline chloride's results are deleterious. To understand the experimental findings, molecular dynamics (MD) simulations were carried out to quantify the solvation layer and calculate the spatial distribution of the solvent molecules around HLADH. The experimental and the in silico approach suggests that designing novel DESs with higher glycerol loadings would result in improved media for biocatalysis. This is demonstrated by performing the reduction of cinnamaldehyde to cinnamyl alcohol-a relevant compound for the food industry and cosmetics-in ChCl-Gly (1 : 9 molar ratio), with 20 vol% water to decrease the viscosity. HLADH is highly active and stable under these new conditions, giving promising productivity (15.3 g L-1 d-1). This paper demonstrates that DESs can be designed to be both substrate-solubilizers and enzyme-compatible, opening new research lines for green chemistry and biocatalysis.

The use of oxidoreductases (EC1) in non-conventional reaction media has been increasingly explored. In particular, deep eutectic solvents (DESs) have emerged as a novel class of solvents. Herein, an in-depth study of bioreduction with an alcohol dehydrogenase (ADH) in the DES glyceline is presented. The activity and stability of ADH in mixtures of glyceline/water with varying water contents were measured. Furthermore, the thermodynamic water activity and viscosity of mixtures of glyceline/water have been determined. For a better understanding of the observations, molecular dynamics simulations were performed to quantify the molecular flexibility, hydration layer, and intraprotein hydrogen bonds of ADH. The behavior of the enzyme in DESs follows the classic dependence of water activity (aW) in non-conventional media. At low aW values (<0.2), ADH does not show any activity; at higher aW values, the activity was still lower than that in pure water due to the high viscosities of the DES. These findings could be further explained by increased enzyme flexibility with increasing water content.

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

Molecular-dynamics simulations are performed to understand the role of host-framework flexibility on the diffusion of methane molecules in the one-dimensional pores of AFI, LTL, and MTW-type zeolites. In particular, the impact of the choice of the host model is studied. Dynamically corrected Transition State Theory is used to provide insights into the diffusion mechanism on a molecular level. Free-energy barriers and dynamical correction factors can change significantly by introducing lattice flexibility. In order to understand the phenomenon of free-energy barriers reduction, we investigate the motion of the window atoms. The influence that host-framework flexibility exerts on gas diffusion in zeolites is, generally, a complex function of material, host model, and loading such that transferability of conclusions from one zeolite to the other is not guaranteed.

The influence of loading on the self-diffusion in an isolated single walled carbon nanotube is studied by molecular dynamics simulations. By simulating the carbon nanotube as a flexible framework we demonstrate that the flexibility has a crucial influence on self-diffusion at low loadings [1]. While simulating the nanotube as rigid a remarkable increase of the diffusion coefficient at low loadings is observed [2]. Molecular dynamics simulations of a fully flexible nanotube result in a far less pronounced increase, by a further reduction of the loading the diffusion becomes constant again. To incorporate the influence of the flexible walls in a simulation of a rigid nanotube, we have introduced a Lowe-Andersen thermostat which works on interface-fluid collisions [1]. The reproduction of the results of a flexible carbon nanotube by a rigid nanotube simulation is excellent. With this approach we simulate the loading dependent self-diffusion in carbon nanotubes. The influence of pore width and temperature on self-diffusion is studied. Furthermore, the influence of adsorption strength is investigated by comparing the self-diffusivities of different components. For small pores, in which the molecules cannot pass each other, single-file diffusion is observed under certain conditions.