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Approach to Optimization of FRAP Methodology for Studies Based on Selected Monoterpenes

Terpenes, wide-spread secondary plant metabolites, constitute important parts of many natural compounds that hold various biological activities, including antioxidant, calming, antiviral, and analgesic activities. Due to their high volatility and low solubility in water, studies of compounds based o...

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Detalles Bibliográficos
Autor principal: Wojtunik-Kulesza, Karolina A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696166/
https://www.ncbi.nlm.nih.gov/pubmed/33198134
http://dx.doi.org/10.3390/molecules25225267
Descripción
Sumario:Terpenes, wide-spread secondary plant metabolites, constitute important parts of many natural compounds that hold various biological activities, including antioxidant, calming, antiviral, and analgesic activities. Due to their high volatility and low solubility in water, studies of compounds based on terpenes are difficult, and methodologies must be adjusted to their specific characteristics. Considering the significant influence of iron ions on dementia development, the activity of terpenes in reducing Fe(3+) represents an important area to be determined. Previously obtained results were unreliable because ferric-reducing antioxidant power (FRAP) methodology was not adjusted regarding studying terpenes. Taking this fact into account, the aim of this study was to optimize the method for monoterpene assessment. The study included three modifications, namely, (1) slightly adjusting the entire FRAP procedure, (2) replacing methanol with other solvents (heptane, butanone, or ethyl acetate), and (3) adding Tween 20. Additionally, a thin layer chromatography (TLC) -FRAP assay was performed. The obtained results revealed significant improvement in the reduction activity of selected terpenes (linalool, α-phellandrene, and α-terpinene) in studies with Tween 20, whereas replacing methanol with other solvents did not show the expected effects.