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Complexation of Cyclodextrins with Benzoic Acid in Water-Organic Solvents: A Solvation-Thermodynamic Approach.

Tatyana R UsachevaVitaly A VolynkinViktor T PanyushkinDmitry A LindtThi Lan PhamNguyen Thi Thu HaThi My Hanh LeDiana A AlisterDzhovidon N KabirovNatalya N KuranovaGeorge A GamovRoman A KushnirMarco BiondiConcetta GiancolaValentin A Sharnin
Published in: Molecules (Basel, Switzerland) (2021)
The aim of this research is to obtain new data about the complexation between β-cyclodextrin (β-CD) and benzoic acid (BA) as a model reaction of the complex formation of hydrophobic molecules with cyclodextrins (CDs) in various media. This research may help developing cyclodextrin-based pharmaceutical formulations through the choice of the appropriate solvent mixture that may be employed in the industrial application aiming to control the reactions/processes in liquid phase. In this paper, NMR results for the molecular complex formation between BA and β-CD ([BA⊂β-CD]) in D2O-DMSO-d6 and in D2O-EtOH have shown that the stability of the complex in the H2O-DMSO-d6 varies within the experimental error, while decreases in H2O-EtOH. Changes in the Gibbs energy of BA resolvation in water and water-dimethylsulfoxide mixtures have been obtained and have been used in the analysis of the reagent solvation contributions into the Gibbs energy changes of the [BA⊂β-CD] molecular complex formation. Quantum chemical calculations of the interaction energy between β-CD and BA as well as the structure of the [BA⊂β-CD] complex and the energy of β-CD and BA interaction in vacuum and in the medium of water, methanol and dimethylsulfoxide solvents are carried out. The stability of [BA⊂β-CD] complex in H2O-EtOH and H2O-DMSO solvents, obtained by different methods, are compared. The thermodynamic parameters of the [BA⊂β-CD] molecular complexation as well as the reagent solvation contributions in H2O-EtOH and H2O-DMSO mixtures were analyzed by the solvation-thermodynamic approach.
Keyphrases
  • ionic liquid
  • molecular dynamics
  • molecular dynamics simulations
  • magnetic resonance
  • machine learning
  • single molecule
  • big data
  • decision making
  • data analysis