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This project aims to investigate, at the molecular level, how three structurally distinct natural polyphenols (curcumin, quercetin and resveratrol) interact with model biological membranes and supramolecular systems. Despite belonging to different chemical classes, these polyphenols exhibit a broad spectrum of biological activities, including antioxidant, anti-inflammatory, anticancer and neuroprotective effects. However, their clinical application remains limited by poor bioavailability, mainly due to low aqueous solubility, limited intestinal absorption, chemical instability, and rapid metabolism. To overcome these limitations, several drug delivery strategies, such as liposomes, nanoparticles, and micelles, have been developed. Nevertheless, the rational design of these systems requires a detailed understanding of the molecular mechanisms governing the interactions of these bioactive compounds with biological membranes. This project proposes to study these interactions using biomimetic membrane models composed of phospholipids, such as DMPC (phosphatidylcholine), as well as mixed lipid systems designed to mimic the lipid composition of different cellular and organelle membranes. In parallel, the interactions of curcumin, quercetin, and resveratrol with supramolecular structures, including biomolecular condensates formed by proteins such as α-synuclein, will be investigated to elucidate their effects on protein aggregation and liquid–liquid phase separation (LLPS). The molecular interactions were characterized using complementary biophysical techniques, including differential scanning calorimetry (DSC), fluorescence spectroscopy, electron paramagnetic resonance (EPR), and fluorescence microscopy. The results are discussed and help build an overall picture of the molecular interactions between curcumin and biomembranes.
The authors acknowledge the financial support from the National Institute of Science and Technology in Innovative Research in Health Sciences – from Nanotechnology to Artificial Intelligence (INCT PICS) sponsored by CNPq (grant 408417/2024-2), CAPES (grant 88887.197686/2025-00), and FAPESP (grant 2025/26818-7). FAPESP also sponsored the project via grants 2023/04532-9.
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