Characterization and Interaction with Biomembrane Model of Benzo[k,l]xanthene Lignan Loaded Solid Lipid Nanoparticles

Abstract

Benzo[k,l]xanthene lignans are a group of rare natural products belonging to the class of polyphenols with promising biological activities and are studied as potential chemotherapeutic agents. The lipophilic character of a xanthene core makes these molecules difficult to be used in an aqueous medium, limiting their employment in studies for pharmaceutical applications. To overcome this problem, a drug-delivery system which is able to improve the stability and bioavailability of the compound can be used. In this study, a bioactive benzoxanthene lignan (BXL) has been included in SLN. Unloaded and BXL-loaded SLN have been prepared using the Phase Inversion Temperature method and characterized in terms of size, zeta potential, entrapment efficiency and stability. Differential scanning calorimetry was used to evaluate the thermotropic behavior and ability of SLN to act as carriers for BXL. A biomembrane model, represented by multilamellar vesicles, was used to simulate the interaction of the SLN with the cellular membrane. Unloaded and loaded SLN were incubated with the MLV, and their interactions were evaluated through variations in their calorimetric curves. The results obtained suggest that SLN could be used as a delivery system for BXL.

Assessment of Pharmaco-Technological Parameters of Solid Lipid Nanoparticles as Carriers for Sinapic Acid

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Synthesis of 14H-dibenzoxanthenes in green media using Sn(II)/nano silica as an efficient catalyst

“…Moreover, some uridine- and xanthene-based drugs are used for treatment of heart problems ( Dai et al, 2022 ). They also have antioxidant ( Liu et al, 2022 ) and antibacterial activities ( Marona et al, 2009 ) and can be employed in biomembranes ( Torrisi et al, 2022 ), dyes ( Cesaratto et al, 2019 ), and solar cells ( Maciejczyk et al, 2016 ). These structures have interesting deep-red and near-infrared adsorption potencies, which make them valuable candidates for cell imaging ( Niu et al, 2016 ).…”