From code to cure: computational identification of LasR inhibitors to combat quorum sensing in P. aeruginosa

Biofilm formation by Pseudomonas aeruginosa (PA) poses a significant challenge in clinical settings due to its contribution to chronic infections and antibiotic resistance. Quorum sensing (QS), particularly regulated by the LasR receptor, plays a crucial role in biofilm development and virulence. In this study, an integrative in silico approach was employed to identify the potential LasR inhibitors. Molecular docking predicted binding affinities of candidate molecules, followed by molecular dynamics simulations to assess complex stability in a dynamic system. Druggability analysis, quantum mechanical evaluation via density functional theory, and binding free energy calculations refined the selection, yielding six promising inhibitors. Among these, compounds 26529, 22498, and 25412 showed strong binding within the LasR-ligand-binding domain, engaging key residues such as Tyr56, Trp60, Asp73, and Ser129. Notably, compound 26529 formed an additional pi-cation interaction with Trp88, providing greater stabilization than typical hydrogen bonds and distinguishing it as the lead molecule. ADMET profiling further confirmed their favorable pharmacokinetic and toxicity properties, selecting the most drug-like candidates. The findings align with the previous reports targeting LasR to attenuate PA virulence and biofilm formation. However, experimental validation remains essential to confirm their therapeutic efficacy. Overall, this study highlights promising QS inhibitors as potential anti-virulence agents against PA.