Abstract
Seaweed-derived metabolites offer a rich source of bioactive compounds with therapeutic potential. In this study, 112 steroidal metabolites from Sargassum polycystum, Gracilaria fisheri, and Caulerpa lentillifera were computationally screened to identify candidates interacting with the glucocorticoid receptor (GR), a key molecule regulating inflammatory signaling. Among them, 11α-hydroxyprogesterone (SW052) from S. polycystum exhibited the favorable predicted GR binding affinity (-11.6 kcal/mol), comparable to hydrocortisone and medrysone. Molecular docking and 500 ns molecular dynamics simulations revealed a stable GR-SW052 complex stabilized by hydrophobic and van der Waals interactions with MET560, LEU563, LEU566, MET601, MET604, LEU608, LEU732, TYR735, and CYS736. Free energy analysis (MM/PBSA) supported favorable thermodynamic binding, and in silico ADMET evaluation predicted good oral absorption and low toxicity. In vitro assays showed that both SW052 and seaweed lipophilic extract were non-cytotoxic (>70 % cell viability) and significantly inhibited nitric oxide (NO) production in lipopolysaccharide-stimulated RAW 264.7 macrophages (IC(50) = 144.05 ± 8.06 and 108.24 ± 4.64 µg/mL, respectively). This study establishes an integrated computational-experimental framework for prioritizing seaweed-derived steroidal metabolites targeting the GR. Using this framework, SW052 was identified as a potential natural compound with stable predicted GR engagement, favorable in silico pharmacokinetic properties, and NO suppression, providing a structure-guided basis for further mechanism and in vivo validation.