INSILICO AND PHARMACEUTICAL CHARACTERIZATION OF PICEATANNOL IN LPS INDUCED DEPRESSION

Abstract

Depression is a prevalent neuropsychiatric disorder in which neuroinflammation, impaired neuroplasticity, and synaptic dysfunction contribute to disease progression. The present study investigated the antidepressant and neuroprotective potential of piceatannol and piceatannol-loaded PLGA nanoparticles (PN–PLGA NPs) in an LPS-induced depression model. In-silico ADMET and molecular docking analyses were performed to evaluate the pharmacokinetic properties and target interactions of piceatannol. PN–PLGA NPs were characterized for particle size, polydispersity index (PDI), zeta potential, encapsulation efficiency (EE%), and drug loading (DL%). Mice received piceatannol (20 mg/kg) or an equivalent PN–PLGA NP formulation for 14 days, followed by LPS (0.83 mg/kg, i.p.) challenge. BDNF and synaptophysin mRNA expression were evaluated using qRT-PCR. Piceatannol demonstrated favorable predicted pharmacokinetic characteristics and exhibited binding energies of −8.0 and −5.6 kcal/mol against D1 and D2 receptors, respectively. PN–PLGA NPs showed a particle size of 162.4 ± 4.7 nm, PDI of 0.148 ± 0.009, zeta potential of −24.3 ± 1.4 mV, EE% of 84.67 ± 2.31%, and DL% of 17.28 ± 0.58%. Both free piceatannol and PN–PLGA NPs improved BDNF and synaptophysin expression, with the nanoparticle formulation producing a greater restoration. Overall, these findings suggest that piceatannol possesses promising antidepressant and neuroprotective potential, while PLGA nanoencapsulation may enhance its therapeutic efficacy against inflammation-associated depression.