Interaction of quercetin with transcriptional regulator LasR of Pseudomonas aeruginosa: Mechanistic insights of the inhibition of virulence through quorum sensing

Grabski, Hovakim; Hunanyan, Lernik; Tiratsuyan, S. G.; Vardapetyan, Hrachik

doi:10.1101/239996

Cited by 8 publications

(13 citation statements)

References 46 publications

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“…Taxifolin is also a flavonoid, and it has been shown that it is not mutagenic less toxic than quercetin [11]. We show that taxifolin also has two binding modes, one with the LBD and the “bridge”, which includes amino acids from LBD and DBD, like quercetin [8, 9].…”

Section: Introductionmentioning

confidence: 76%

“…The methodology was inspired by our previous works [8, 9]. Molecular docking was performed using multiple docking programs: Autodock Vina [21], rDock [22], LeDock [23], FlexAid [24].…”

Section: Resultsmentioning

confidence: 99%

“…For the taxifolin without the hydroxyl group these 2 clusters amount 73.8% of all the docking poses. These two clusters correspond to ligand binding domain, which corresponds to the experimental binding site and the other is the “bridge” region [8, 9]. Then we extracted the “centroid” (representative structure) from each cluster of the docking simulations using equation 2 for molecular dynamics.…”

Section: Resultsmentioning

confidence: 99%

“…It should be noted that DQC interacts with many conserved amino acid residues, including Leu177 and Leu236. The native autoinducer [8] and quercetin [9] also interacts with Leu177 and Leu236, while DHO does not.…”

Section: Resultsmentioning

confidence: 99%

“…It appeared there could be a possible second binding site. In another work we show that quercetin has two binding modes: one with LBD and the other with the “bridge” [9]. It has been shown that the LBD is capable of having multiple ligands in the binding pocket [10], but yet flavonoids do not inhibit in the presence of 3OC12-HSL [1].…”

Section: Introductionmentioning

confidence: 99%

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Mechanistic insights of the attenuation of quorum-sensing-dependent virulence factors of Pseudomonas aeruginosa: Molecular modeling of the interaction of taxifolin with transcriptional regulator LasR

Grabski

Tiratsuyan

2018

Preprint

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Pseudomonas aeruginosa is one of the most dangerous superbugs and is responsible for both acute and chronic infection. Current therapies are not effective because of biofilms that increase antibiotic resistance. Bacterial virulence and biofilm formation are regulated through a system called quorum sensing, which includes transcriptional regulators LasR and RhIR. These regulators are activated by their own natural autoinducers. Targeting this system is a promising strategy to combat bacterial pathogenicity. Flavonoids are very well known for their antimicrobial activity and taxifolin is one of them. It is also known that flavonoids inhibit Pseudomonas aeruginosa biofilm formation, but the mechanism of action is unknown. In the present study, we tried to analyse the mode of interactions of LasR with taxifolin. We used a combination of molecular docking, molecular dynamics simulations and machine learning techniques, which includes principal component and cluster analysis to study the interaction of the LasR protein with taxifolin. We show that taxifolin has two binding modes. One binding mode is the interaction with ligand binding domain. The second mode is the interaction with the "bridge", which is a cryptic binding site. It involves conserved amino acid interactions from multiple domains. Biochemical studies show hydroxyl group of ring A in flavonoids is necessary for inhibition. In our model the hydroxyl group ensures the formation of many hydrogen bonds during the second binding mode. Microsecond simulations also show the stability of the formed complex. This study may offer insights on how taxifolin inhibits LasR and the quorum sensing circuitry.

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Section: Introductionmentioning

confidence: 76%

“…The methodology was inspired by our previous works [8, 9]. Molecular docking was performed using multiple docking programs: Autodock Vina [21], rDock [22], LeDock [23], FlexAid [24].…”

Section: Resultsmentioning

confidence: 99%