Alveolar epithelial barrier dysfunction contributes to lung edema and can lead to acute lung injury (ALI). The features include increased epithelial permeability, upregulation of inflammatory mediators and downregulation of junctional complex molecules; these changes are often induced by inflammation. tHGA is an acetophenone analogue with therapeutic potential in asthma. Its therapeutic potential in ALI is presently unknown. Herein, the effects of tHGA on epithelial barrier dysfunction were determined in TNF-α-induced human alveolar epithelial cells. The anti-inflammatory properties of tHGA were assessed by monocyte adhesion assay and analysis of MCP-1 and ICAM-1 expression. The epithelial barrier function was assessed by paracellular permeability and transepithelial electrical resistance (TEER) assays, and analysis of junctional complex molecules expression. To elucidate the mechanism of action, the effects of tHGA on the NF-κB and MAPK pathways were determined. Gene and protein expression were analyzed by RT-PCR and Western blotting or ELISA, respectively. tHGA suppressed leukocyte adhesion to TNF-α-induced epithelium and reduced MCP-1 and ICAM-1 gene expression and secretion. tHGA also increased TEER readings, reduced epithelial permeability and enhanced expression of junctional complex molecules (zona occludens-1, occludin and E-cadherin) in TNF-α-induced cells. Correspondingly, the NF-κB, ERK and p38 MAPK pathways were also inhibited by tHGA. These findings suggest that tHGA is able to preserve alveolar epithelial barrier function in response to acute inflammation, via its anti-inflammatory activity and stabilization of epithelial barrier integrity, mediated by NF-κB, ERK and p38 MAPK signaling.

Introduction: An important regulatory aspect of cancer progression is the interaction between p53 and MDM2, particularly in breast cancer, where the excessive presence of MDM2 hampers p53's tumour- suppressing function. Although many natural flavonoids are recognized for their influence on this pathway, they often exhibit suboptimal potency and pharmacokinetic properties. To discover flavonoid derivatives with stronger inhibitory effects on the p53–MDM2 interaction, this research integrates Density Functional Theory (DFT), molecular docking, and AI-enhanced de novo optimization. Materials and Methods: Validated molecular docking protocols were employed to evaluate 52 flavonoids from the Indonesian Natural Products Database against the p53–MDM2 complex, yielding a validation RMSD value of 0.4935 Å. AI-assisted molecular design was subsequently applied to the topperforming compounds to generate optimized derivatives with improved binding affinity and pharmacokinetic properties. Binding interactions were analyzed using conventional molecular visualization approaches. Drug-likeness, ADME, and toxicity profiles were predicted using SwissADME, ProTox-II, and ADMETlab 2.0. Density Functional Theory (DFT) calculations at the B3LYP/6-31G(d,p) level were performed to evaluate electronic properties and molecular stability. Furthermore, Molecular Dynamics (MD) simulations and MM-GBSA calculations were conducted to investigate the dynamic stability and binding free energy of the selected complexes. Results: Among the AI-optimized derivatives, Amentoflavone-1 demonstrated the strongest binding affinity (–5.60 kcal/mol), outperforming Resveratrol (–4.24 kcal/mol). Interaction profiling revealed that hydrophobic interactions and π–π stacking with key residues within the p53-MDM2 binding pocket were the primary stabilizing forces. ADME predictions indicated improved drug-likeness and absorption properties, while toxicity analyses suggested reduced mutagenicity and mitochondrial toxicity, though a moderate hepatotoxicity risk remained. DFT calculations demonstrated favourable HOMO– LUMO energy gaps and frontier molecular orbital characteristics associated with molecular stability and chemical reactivity. Molecular dynamics simulations over 100 ns showed that the p53-MDM2– Amentoflavone-1 complex maintained a stable conformation comparable to the native ligand, as evidenced by RMSD, RMSF, SASA, and radius-of-gyration analyses. In addition, MM-GBSA calculations revealed a binding free energy of –18.37 kcal/mol for Amentoflavone-1, confirming spontaneous and thermodynamically favourable binding to the p53-MDM2 complex. Discussion: The integration of AI-driven de novo design with conventional computational modelling successfully enhanced and clarified the pharmacological potential of flavonoid scaffolds. Amentoflavone- 1 exhibited favourable binding interactions consistent with known p53–MDM2 inhibition mechanisms, supported by stable molecular dynamics behaviour and thermodynamically favourable binding profiles. Improvements in ADME and toxicity parameters further suggest that AI-guided structural modification can effectively optimize flavonoid-based inhibitor candidates. Conclusion: Overall, AI-guided structural optimization improved the binding characteristics, molecular stability, and drug-likeness profile of Amentoflavone-1 relative to its parent compound. Although its binding affinity and MM-GBSA energy remained lower than those of the native ligand, Amentoflavone- 1 demonstrated stable interactions with the p53-MDM2 complex and should be considered a promising preliminary lead compound for further structural refinement and experimental validation.