Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches.
Journal:
Journal of molecular modeling
PMID:
37468720
Abstract
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. Targeting the AgrA of the Agr system serves as beneficial in holding the top position in the QS system cascade.