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

Author:

Dwiecki Krzysztof1ORCID,Przybył Krzysztof2ORCID,Dezor Dobrawa1,Bąkowska Ewa1,Rocha Silvia M.3ORCID

Affiliation:

1. Department of Food Biochemistry and Analysis, Poznań University of Life Sciences, ul. Mazowiecka 48, 60-623 Poznan, Poland

2. Department of Dairy and Process Engineering, Faculty of Food Science and Nutrition, Poznań University of Life Sciences, ul. Wojska Polskiego 31, 60-624 Poznan, Poland

3. Department of Chemistry & LAQV-REQUIMTE, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

Abstract

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.

Funder

PT national funds

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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