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Assessing the Influence of Betaine-Based Natural Deep Eutectic Systems on Horseradish Peroxidase.

Nicolás F Gajardo-ParraLiane MenesesAna Rita C DuarteAlexandre PaivaChristoph Held
Published in: ACS sustainable chemistry & engineering (2022)
To validate the use of horseradish peroxidase (HRP) in natural deep eutectic systems (NADES), five different betaine-based NADES were characterized in terms of water content, water activity, density, and viscosity experimentally and by thermodynamic modeling. The results show that the NADES under study have a water activity of about 0.4 at 37 °C for water contents between 14 and 22 wt %. The densities of the studied NADES had values between 1.2 and 1.3 g . cm -3 at 20 °C. The density was modeled with a state-of-the-art equation of state; an excellent agreement with the experimental density data was achieved, allowing reasonable predictions for water activities. The system betaine:glycerol (1:2) was found to be the most viscous with a dynamic viscosity of ∼600 mPa . s at 40 °C, while all the other systems had viscosities <350 mPa . s at 40 °C. The impact of the NADES on the enzymatic activity, as well as on, conformational and thermal stability was assessed. The system betaine/sorbitol:water (1:1:3) showed the highest benefit for enzymatic activity, increasing it by two-folds. Moreover, upon NADES addition, thermal stability was increased followed by an increment in a-helix secondary structure content.
Keyphrases
  • hydrogen peroxide
  • machine learning
  • nitric oxide
  • deep learning
  • big data
  • aqueous solution