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  4. Interactions of Oleanolic Acid, Apigenin, Rutin, Resveratrol and Ferulic Acid with Phosphatidylcholine Lipid Membranes - A Spectroscopic and Machine Learning Study
 
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Interactions of Oleanolic Acid, Apigenin, Rutin, Resveratrol and Ferulic Acid with Phosphatidylcholine Lipid Membranes - A Spectroscopic and Machine Learning Study

Type
Journal article
Language
English
Date issued
2023
Author
Dwiecki, Krzysztof 
Przybył, Krzysztof 
Dezor, Dobrawa
Bąkowska, Ewa 
Rocha, Silvia M.
Faculty
Wydział Nauk o Żywności i Żywieniu
Journal
Applied Sciences (Switzerland)
ISSN
2076-3417
DOI
10.3390/app13169362
Web address
https://www.mdpi.com/2076-3417/13/16/9362
Volume
13
Number
16
Pages from-to
art. 9362
Abstract (EN)
Biologically active compounds present in the diet can interact with biological membranes (such as cell membranes), changing their properties. Their mutual interactions can influence their respective activities. In this study, we analyzed the interactions of oleanolic acid and phenolic compounds such as apigenin, rutin, resveratrol and ferulic acid with phosphatidylcholine membranes. Spectroscopic methods (fluorescence spectroscopy, dynamic light scattering) and machine learning were applied. The results of structural studies were compared with the antioxidant activity of the investigated substances in lipid membranes. In liposomes loaded with oleanolic acid, the pro-oxidant activity of resveratrol arises from changes in membrane structure, leading to an increased exposure of its hydrophilic region to external radicals. A similar mechanism may be involved in the pro-oxidant action of oleanolic acid. By contrast, apigenin, rutin and ferulic acid are present at the membrane surface. Their presence in this region protects the bilayer from radicals generated in the aqueous phase. Lower antioxidant activity observed in the case of ferulic aid is probably related to weaker interactions of this compound with the membrane, compared to the investigated flavonoids. Appropriate machine learning models for predicting oleanolic acid and phenolic compounds have been developed for the future application of intelligent predictive systems to optimizing manufacturing processes involving liposomes. The most effective regression model turned out to be the MLP 1:1-100-50-50-6:1, identifying resveratrol with a determination index of 0.83.
Keywords (EN)
  • oleanolic acid

  • flavonoid

  • resveratrol

  • phenolic compounds

  • antioxidant activity

  • lipid membranes

  • liposomes

  • machine learning

  • regression

  • multilayer perceptron

License
cc-bycc-by CC-BY - Attribution
Open access date
August 18, 2023
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