Identification of potential anti-biofilm agents targeting LasR in Pseudomonas aeruginosa through machine learning-driven screening, molecular docking, and dynamics simulations.

ABSTRACT: Antimicrobial resistance (AMR) remains a major worldwide health concern, with biofilm-forming bacteria playing an important role in the persistence of chronic infections and the evasion of host immune responses. Pseudomonas aeruginosa, a common biofilm-forming bacteria, is notorious for causing a wide range of infections, particularly in immunocompromised people, and is highly resistant to standard treatment drugs. This work aims to find new anti-biofilm compounds that target the Pseudomonas aeruginosa LasR quorum-sensing system, which is an important regulator of biofilm development and pathogenicity. In this study machine learning-based virtual screening, molecular docking, and dynamics simulations were combined. Initially, a selection of 324 decoys and 116 known LasR inhibitors were sel

SUBMITTER: Almatroudi A 

PROVIDER: S-EPMC12749182 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature