Title
The role of eugenol and ferulic acid as the competitive inhibitors of transcriptional regulator RhlR in P. aeruginosa
11627/634211627/6342
Author
Escobar Muciño, Esmeralda
Abstract
"Search inhibitors of Quorum Sensing (QS) in Pseudomonas aeruginosa are challenging to find therapies due to the broad antibiotic resistance. Therefore, this study aimed to probe ten aromatic compounds as inhibitors of three transcriptional regulators of QS in P. aeruginosa. The methodology consisted in determining the Binding Gibbs Energy (BGE) with software Chimera (tool vina) and Mcule, comparing the averages by the Tukey method (p?0.05) to find inhibitors of QS. Subsequently, the LD50 in the mice model was evaluated by three QSAR models, and the in silico pharmacokinetic values were obtained from the ADME (the absorption distribution metabolism excretion) and PubChem databases. Found three potential inhibitors of RhlR with the lower BGE values in the range -6.70±0.21 to -7.43±0.35 kcal/mol. On the other side, all compounds were acceptable for Lipinski's rule of fives and the in silico oral mice LD50 and ADME values. Concluding, the ferulic acid and eugenol showed the best total BGE values (-75.07±0.892 and -70.36±1.022 kcal/mol), proposing them as a new therapy against the virulence of P. aeruginosa. Finally, the in silico studies have demonstrated are reproducible and valuable for putative QS inhibitors predicting and obtaining new studies derivatives from the results obtained in the present study. • The key benefits of this methodology are:
Use free, licensed, flexible, and efficient software for in silico molecular docking.
• Validation and comparison of BGE employing two molecular docking software in three different proteins.
• Use classical molecular dynamics to define the stability and the total BGE of interaction protein-ligand and find the best inhibitor of a protein for proposing them as a possible therapy against the virulence of specific pathogens."
Publication date
2022Publication type
articleDOI
https://doi.org/10.1016/j.mex.2022.101771Knowledge area
CIENCIAS TECNOLÓGICASCollections
Publisher
ElsevierKeywords
Molecular dockingQuorum sensing inhibitors
Validation Validation of software
Molecular dynamic
Therapy
virulence
Gram-negative bacteria