abstract
Artemisinin is a sesquiterpenoid lactone peroxide, known for its potent antimalarial activity that can be extracted from Artemisia annua L. This compound is only sparingly soluble in water, making its extraction using environmental-friendly and non-toxic aqueous solvents difficult. In the attempt to overcome this limitation, hydrotropes, which are a class of compounds that can assist in increasing the solubility of hydrophobic solutes in water, were investigated in this work. In particular, the hydrotropic capability of ionic liquids (ILs) on the aqueous solubility of artemisinin was studied. The effects of IL concentration and anion nature of 1-butyl-3-methylimidazolium-based ILs on the solubility of artemisinin at 303.2 K in water were evaluated. It is here shown the excellent capacity of ILs containing thiocyanate or dicyanamide anions to enhance the solubility of artemisinin in aqueous media, with a magnitude comparable to that obtained with the best organic solvents. Furthermore, solvatochromic parameters of the ILs aqueous solutions were also measured and combined with COSMO-RS and the cooperative hydrotropy model to establish relations between the artemisinin solubility enhancement and the solvent characteristics. The solubility enhancement of artemisinin is favored by the apolarity of the medium and the lower hydrogen-bond acceptor character of the hydrotrope. (C) 2021 Elsevier B.V. All rights reserved.
keywords
POLARITY; SOLVENT
subject category
Thermodynamics; Chemistry, Physical; Engineering, Chemical
authors
Sales, I; Abranches, DO; Costa, P; Sintra, TE; Ventura, SPM; Mattedi, S; Coutinho, JAP; Freire, MG; Pinho, SP
our authors
Dinis O. Abranches
Assistant Researcher
Isabela Sales
Research Fellowship
Mara Guadalupe Freire Martins
Coordinating Researcher
Simão Pedro de Almeida Pinho
Collaborator
Sónia Patrícia Marques Ventura
Assistant Professor
Tânia Ereira Sintra
Post-Doc FellowshipGroups
G4 - Renewable Materials and Circular Economy
G5 - Biomimetic, Biological and Living Materials
G6 - Virtual Materials and Artificial Intelligence
acknowledgements
This work was developed within the scope of the projects CICECO-Aveiro Institute of Materials, UIDB/50011/2020 & UIDP/50011/2020, CIMO-Mountain Research Center, UIDB/00690/2020, all financed by national funds through the FCT/MEC and when appropriate co-financed by FEDER under the PT2020 Partnership Agreement. Isabela Sales and Silvana Mattedi thanks the finantial support from CAPES and CNPq/Brazil (CAPES: Proc. 88881.189075/2018-01 and 88887.494428/2020-00. CNPq: Grant 303089/2019-9 and Proc.438036/2018-2).