Computational solvation analysis of biomolecules in aqueous ionic liquid mixtures

Abstract

Based on their tunable properties, ionic liquids attracted significant interest to replace conventional, organic solvents in biomolecular applications. Following a Gartner cycle, the expectations on this new class of solvents dropped after the initial hype due to the high viscosity, hydrolysis, and toxicity problems as well as their high cost. Since not all possible combinations of cations and anions can be tested experimentally, fundamental knowledge on the interaction of the ionic liquid ions with water and with biomolecules is mandatory to optimize the solvation behavior, the biodegradability, and the costs of the ionic liquid. Here, we report on current computational approaches to characterize the impact of the ionic liquid ions on the structure and dynamics of the biomolecule and its solvation layer to explore the full potential of ionic liquids.

Exogenous Protein Delivery of Ionic Liquid-Mediated HMGB1 Coating on Titanium Implants

“…To account for polarizability and charge-transfer effects, the partial charges of the IonL atoms were scaled by 0.8 . It is reported that a 0.8 charge scaling factor can accurately capture experimental properties of imidazolium based IonLs such as their bulk density. − …”

Tuning Water Networks via Ionic Liquid/Water Mixtures

“…In addition to membranes, other potential applications of IL/water mixtures include use as solvents for chemical extraction, separation and catalysis [16,24,26,34,35], solvents for biomolecules and protein stabilizers [36][37][38][39][40], tunable solvents for biocatalysis [41][42][43][44] and solvents for tailoring coordination chemistry and exchange rates of lanthanides [45,46]. In all of these applications, it is essential to develop a fundamental understanding of how different ILs alter water nanostructure at various ion/water concentrations.…”

Pinning the conformation of a protein (CorA) in a solute matrix with selective binding

“…Different lattice sizes are used to make sure that the qualitative trends are independent of the sample size. The results presented here are based on data generated on a 350 3 sample which provides ample sampling at long-time scales without using excessive computer resources. Reduced units are used for temperature, time step, and spatial length scales in this simulation since our focus is on changes in physical quantities in response to changing the solute interaction strength (f) that affect the preferential binding.…”

“…For example, Duncan et al [2] have recently reported subdiffusion of proteins and lipids and effects of crowding on their sub-diffusive dynamics in general. Zeindlhofer and Schroeder [3] have reviewed the analysis of biomolecules in aqueous ionic liquid mixtures where they have pointed out that the viscosity of the imbedding matrix affect the structure of the protein. They have cautioned that such effects may be specific to individual protein and therefore should be tested before generalizing the main observation.…”