Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches.

Context: Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expression of virulent genes, the quorum sensing (QS) mechanism is a major contributor to the development of these diseases. By hindering its QS network, an innovative approach to avoiding this bacterial infection is taken.

Inhibition of biofilm formation, quorum sensing and virulence factor production in Pseudomonas aeruginosa PAO1 by selected LasR inhibitors.

The quorum sensing network of Pseudomonas aeruginosa mediates the regulation of genes controlling biofilm formation and virulence factors. The rise of drug resistance to Pseudomonas aeruginosa infections has made quorum sensing-regulated biofilm formation in clinical settings a major issue. In the present study, LasR inhibitors identified in our previous study were evaluated for their antibiofilm and antiquorum sensing activities against P.

Combined machine learning and pharmacophore based virtual screening approaches to screen for antibiofilm inhibitors targeting LasR of .

, a virulent pathogen affects patients with cystic fibrosis and nosocomial infections. Quorum sensing (QS) mechanism plays a crucial role in causing these ailments by mediating biofilm formation and expressing virulent genes. A novel approach to circumvent this bacterial infection is by hindering its QS network.