Targeting Trefoil Factor Family 3 in Obstructive Airway Diseases: A Computational Approach to Novel Therapeutics.

Background: Airway remodeling, a hallmark of chronic obstructive pulmonary disease (COPD) and mustard lung disease, is influenced by the Trefoil Factor 3 (TFF3). This study sought to pinpoint a compound with minimal toxicity that can effectively suppress TFF3 expression and activity. Methods: We employed an integrative approach, combining gene expression analysis, molecular docking, and molecular dynamics simulations to identify potential TFF3 inhibitors. Gene expression analysis utilized Z-scores from the Library of Integrated Network-Based Cellular Signatures (LINCS) database to identify compounds altering TFF3 expression. Drug-like properties were assessed through Lipinski's "Rule of Five." Molecular docking was conducted with AutoDock Vina (version 1.1.2), and molecular dynamics simulations were performed using Groningen Machine for Chemical Simulations (GROMACS) version 5.1. Toxicity evaluation leveraged a Graph Convolutional Network (GCN). Statistical significance was set at P<0.05. Results: Eight of the compounds assessed significantly reduced TFF3 expression, with binding affinities (ΔG) ranging from -7 to -9.4 kcal/mol. Notably, genistein emerged as the frontrunner, showcasing potent TFF3 downregulation, minimal toxicity, and a robust inhibitory profile, as evidenced by molecular dynamics simulations. The significance of gene expression changes was indicated by Z-scores provided by the LINCS database rather than exact P values. Conclusion: Genistein holds promise as a therapeutic agent for TFF3-mediated conditions, including mustard lung disease. Its potential to address the current therapeutic gaps is evident, but its clinical utility necessitates further