Determination of the effects of Chrysophanol on Pseudomonas aeruginosa Quorum sensing mechanism and biofilm formation via In vitro and In silico methods
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Abstract (EN)
Pseudomonas aeruginosa is an opportunistic pathogen that causes acute and chronic virulence associated infections. Developing antibiotic resistance mechanisms causes failure to treat P.aeruginosa infections. Consequently, new approaches are aimed at reducing virulence factors. In this study, the anti-QS effect of Chrysophanol using P. aeruginosa sensor strains, antibiofilm and antivirulence effect using wild type strain PAO1 were investigated in vitro. Molecular docking simulations were carried out with proteins involved in the QS signaling mechanism of P. aeruginosa. The structure of the RhlR receptor was obtained by homology modeling. Protein-ligand complexes with the lowest binding energy and containing the desired amino acid connections were subjected to long molecular dynamics simulations and MM-GBSA free energies were calculated. In the first dose of 135.8 µM of Chrysophanol, inhibition of lasB-gfp, rhlA-gfp and pqsA-gfp strains was 52.6%, 20.1% and 73.1%, respectively. The same dose of antibiofilm effect is 43.8% and the antivirulence feature is 96.4% in piyosiyanin, 88.3% in elastase and 52.3% in protease. Each protein has its endogenous agonist and the Penicillic acid molecule known for its QSI effect is used as a positive control. Our simulations indicated that the effectiveness of the molecule is successful and its stability is stable in QS systems. Considering in vitro inhibition, in silico and in vitro studies were found to be consistent with each other. It is thought that the antivirulence and QSI property of Chrysophanol is determined in vitro and detailed in silico calculations of each reseptors will contribute to the literature.
Author
Ayla Yıldız
Institution
How to Cite
Ayla Yıldız (Master Thesis). Determination of the effects of Chrysophanol on Pseudomonas aeruginosa Quorum sensing mechanism and biofilm formation via In vitro and In silico methods, 2020, Marmara University.
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