Structure-Based Virtual Screening: Identification of Novel Quorum-Sensing Inhibitors to Interfere with the Formation of Pseudomonas aeruginosa Biofilm

authors:

avatar Majid Jafari-Sabet 1 , * , avatar Ali Baratian 2 , 3

Department of Pharmacology, School of Medicine, Iran university of Medical Sciences, Tehran, Iran
AJA University of Medical Sciences, Tehran, Iran
Department of Medicinal Chemistry, School of Pharmacy, Mashhad university of Medical Sciences, Mashhad, Iran

how to cite: Jafari-Sabet M, Baratian A. Structure-Based Virtual Screening: Identification of Novel Quorum-Sensing Inhibitors to Interfere with the Formation of Pseudomonas aeruginosa Biofilm. J Arch Mil Med. 2017;5(1):e13227. https://doi.org/10.5812/jamm.45046.

Abstract

Background:

Drug-resistant Pseudomonas aeruginosa (P. aeruginosa) is among the most important opportunistic human pathogens that may infect military personnel during war by generating a broad range of virulence factors, the expression rates of which are firmly arranged by cell density-dependent cell-to-cell signaling called quorum sensing (QS).

Objectives:

This study aimed at identifying putative inhibitors of LasR by structure-based virtual screening on ZINC database, testing prospective candidates on pqsE with computer aided inhibition studies followed by structure analysis, and examining the extension of specific drugs with potential anti-virulence properties for the treatment of infections induced by drug-resistant P. aeruginosa.

Methods:

Structure-based virtual screening in ZINC database was used through Autodock Vina in order to assess putative inhibitors of LasR. Prospective candidates’ inhibitory efficiency on pqsE was examined by means of computer aided inhibition studies followed by structure analysis.

Results:

Twenty possible quorum sensing inhibitors were introduced that could be used in different conditions to inhibit quorum sensing and thus reduce bacterial resistance and pathogenicity. A software was also designed to provide graphical user interface to vina and to automate the process of virtual screening.

Conclusions:

This study provided a perspective for development of specific drugs with potential anti virulence properties in military medicine for the treatment of infections induced by drug-resistant P. aeruginosa

1. Background

Pseudomonas aeruginosa (P. aeruginosa), rod-shaped gram-negative bacteria, can cause acute infections in humans (1). These bacteria are multidrug resistant pathogens recognized for their ubiquity, their intrinsically advanced antibiotic resistance mechanisms and association with serious infections in hospitalized patients, such as ventilator-associated pneumonia and various sepsis syndromes (1-3).

Pseudomonas aeruginosa produces a broad spectrum of virulence factors, the expression levels of which are firmly adjusted (4). The key to this adjustment is quorum sensing (QS), a ubiquitous cell density-dependent cell-to-cell communication system (4-6).In P. aeruginosa, similar to other bacteria, QS controls formation of biofilm, virulence factors secretion and DNA exchange (7-9). It has been shown that the growth of biofilm is the main bacterial property and plays a critical role in infections (10, 11).

On the other hand, numerous infections require the formation of bacterial biofilms, which are communities of bacterial that proliferate and fix on surfaces and are hidden by exopolymers (12).

It must be noted that after formation, it is difficult to eradicate the biofilm and this becomes a principle of secondary infection (4, 13).

Furthermore, bacteria hidden in biofilms are more resistant against antibiotics. Therefore, in this condition, treatment of infections often fails (14, 15).

Gram-negative bacteria, such as P. aeruginosa, produce and release N-acyl Homoserine Lactones (AHLs) by QS. Suitable concentrations of AHLs then bind to specific receptors and make dimers or polymers of the activated receptor-AHL complex which, in turn, acts as transcriptional modifiers of target genes in the QS region (16, 17).

Hence, the expression of virulence genes and induction of biofilm formation, through a cascade of regulatory events, is coordinated by AHLs (4, 18). Therefore, the QS system plays a crucial role in organizing infections and enhancing resistance to antibiotics (6, 15).

Discovery and development of drugs that inhibit the QS system cause a major innovation in the eradication of antibiotic resistant bacteria (19, 20). It has been found that some QS Inhibitors (QSIs) like patulin, a mycotoxin produced by a variety of molds, make P. aeruginosa more susceptible to tobramycin, an aminoglycoside antibiotic (21-23).

It must not be forgotten that P. aeruginosa cell-to-cell signaling is not limited to AHLs. Two distinct, yet related QS circuits, have been identified in P. aeruginosa. Both of these systems are genetically similar in that they consist of genes encoding transcriptional activator proteins (lasR and rhlR) as well as genes responsible for the production of AHL signaling molecules (lasI and rhlI) (24, 25).

In the QS systems, the intercellular signals for the las and rhl are N-(3-oxododecanoyl)-L-homoserine lactone (3-oxo-C12-HSL) and N-(butanoyl)-L-homoserine lactone (C4-HSL) (26). It has been shown that these signals regulate hundreds of genes, indicating 4% to 12% of the P. aeruginosa genome (27, 28).

Furthermore, 3-oxo-C12-HSL and C4-HSL, 2 bacterial cell-to-cell signals, are essential for the production of various extracellular virulence factors and the development of a differentiated biofilm in P. aeruginosa (29, 30).

It has been reported that P. aeruginosa produces another signal molecule, 2-heptyl-3-hydroxy-4-quinolone, which has been determined as the pseudomonas quinolone signal (PQS), a unique cell-to-cell signal (30, 31). Furthermore, PQS was shown to control the expression of lasB, which encodes for LasB elastase, a major virulence factor (32, 33). Moreover, the P. aeruginosa las and rhl QS systems were interfering in the synthesis and bioactivity of PQS, respectively (31).

Transcriptome analysis studies have shown that PQS directly and indirectly activates 92 and 143 genes, respectively (34, 35).

For this purpose, PQS binds to and activates PqsR (a LysR-type transcriptional regulator), and subsequently induces the expression of the pqsABCDE operon (36, 37). The pqsABCD genes of this operon are required for PQS synthesis, yet, the function of the pqsE gene is not clear (38-41). It has been reported that the pqsE gene is required for the production of several PQS-controlled virulence factors (42). Furthermore, it has been suggested that the regulatory activity of PqsE is unrelated to PqsR and PQS, yet, related to the rhl QS system (31, 42).

2. Objectives

This study aimed at identifying putative inhibitors of LasR by structure-based virtual screening on ZINC database, testing prospective candidates on pqsE with computer aided inhibition studies followed by structure analysis, and to determine the extension of specific drugs with potential anti-virulence properties for the treatment of infections induced by drug-resistant P. aeruginosa.

3. Methods

AutoDock Vina is a program for molecular docking and virtual screening that uses a command line interface and only accepts 1 receptor and ligand in each run. As structural virtual screening is a repetition of docking cycles for thousands of ligands, these limitations make it a time consuming task. Therefore, a software was developed using Microsoft visual studio 2012 (Visual Basic) to automate virtual screening steps. The program was designed to accept the database and receptor files through graphical user interface and to extract and convert the database to single ligands and then to run the docking cycle for each ligand with the same receptor. The program was set to output a list of ligands sorted by descending affinity in conjugation with their respective docking energy (43).

Autodock Vina achieves an approximately 2 order of magnitude speed-up compared with AutoDock 4, a molecular docking software. In addition, it significantly improves the accuracy of the binding mode predictions, judging by the tests on the training set used in AutoDock 4 development. Furthermore, speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user (43, 44).

The ZINC database was downloaded from its website. The 3D structures of LasR (PDB ID: 2UV0) and pqsE (PDB ID: 2Q0J) were downloaded from RCSB protein data bank and were used as receptors. To reduce the time needed for screening and to eliminate further need for animal and human safety tests, the zinc database was filtered so that only Food and Drug Administration (FDA) approved compounds were taken into account. About 2300 compounds were then used for virtual screening and subsequent docking studies.

First screening was performed on LasR. Autodock tools were used to prepare the receptor by adding partial Kollman charges and missing polar hydrogen. The region of interest to be used by Autodock vina was defined as the center of the ligand already present in the crystal structure; the ligand and other unnecessary molecules were removed before commencement of the docking process. The size of the grid was set to 17, 17, and 23 angstroms in x, y, and z directions. Each compound was subjected to 10 runs of Vina with exhaustiveness value set to 8 and selection of LasR as the receptor. The same set of ligands was then docked into pqsE, following the same procedure. The size of the docking grid was set to 17 in all 3 dimensions. Ligands were sorted based on descending affinity to each receptor, and top 50 substrates were selected giving the same weight to LasR and pqsE binding affinity.

Ligands were finally inspected by the ViewerLite program for placement accuracy and formation of proper hydrogen bonds and van der Waals interactions.

4. Results

Top structures and their affinity to the 2 receptors are detailed in Table 1 and Figure 1. The data analysis showed that these compounds are very similar in structure. These inhibitors can mainly be categorized in 2 major groups, steroids and some subfamilies of non-steroidal anti-inflammatory drugs (NSAIDs). It can be inferred that having 2 polar groups with a distance similar to oxygen to oxygen distance between 3- and 17-hydroxyl groups of estradiol is required for proper interaction with the active site. These 2 groups are required for interaction with Tyr 47 and Ser 129 in LasR. For PqsE, they interact with Ser 273 and His 71. These interactions are depicted in Figure 2B and 2C. It seems that although the presence of these 2 groups is essential for proper binding, the distance is somewhat flexible, and ligands without fused rings with variation in distance also bind with lower affinity.

Structure of the Top Compounds
A, Pranoprofen; B, Estradiol; C, 19-Norandrostendione; D, Estrone; E, Triptane; F, Estradiol Benzoate; G, Carprofen; H, Catechin; I, Anisindione; J, Estriol; K, Phenindione; L, Labetelol; M, Flubiprofen; N, Nordihydroguaiaretic acid; O, Ketorolac; P, Sulfasalazine; Q, Cianidanol; R, Lenalidomide; S, Ketoprofen; T, Fluroperidol.
A, Shows a Surface Added to an Overlay of 5 Top Inhibitors of lasR in the Active site of the Protein; B, Shows Amino Acids Surrounding Ligands and Making Hydrogen Bonds with the Top 5 LasR Inhibitors; C and D Show pqsE and its 5 Top Inhibtors as Top
A, Shows a Surface Added to an Overlay of 5 Top Inhibitors of lasR in the Active site of the Protein; B, Shows Amino Acids Surrounding Ligands and Making Hydrogen Bonds with the Top 5 LasR Inhibitors; C and D Show pqsE and its 5 Top Inhibtors as Top
Table 1.

Top Compoundsa

Structure NameLasRpqsE
Docking energy
Pranoprofen-9.3-10.4
Estradiol-8.8-10.4
19-Norandrostendione-10-10.2
Estrone-9.3-10.3
Triptane-9-10.3
Estradiol Benzoate-8.7-12.8
Carprofen-9.8-9.6
Catechin-8.1-10.3
Anisindione-10.2-8.1
Estriol-10.0-8.6
Phenindione-9.7-9.0
Labetalol-10.2-8.0
Flurbiprofen-9.7-9.1
Nordihydroguaiaretic acid-8.0-10.1
Ketorolac-9.7-8.5
Sulfasalazine-10.5-7.5
Cianidanol-10.3-7.6
Lenalidomide-9.6-8.6
Ketoprofen-9.5-9.4
Fluroperidol-11.3-7.3

Figure 2A and 2D show the 2 proteins with surfaced ligands inside. It can be observed that due to smaller size of pqsE’s active site, compounds with higher affinity to the mentioned protein have smaller sizes in comparison to LasR inhibitors. Figure 3 demonstrates the difference between compounds with more affinity to pqsE or LasR. The LasR inhibitors are very similar to pqsE inhibitors on one end and on the other end it seems that having only an aromatic ring is sufficient for proper attachment. The mentioned ring forms aromatic interactions with phenol rings of Tyr 56 and Tyr 64. Having an electron substituted on this ring ameliorates binding affinity by facilitating formation of hydrogen bonds.

Left Column Shows the Compounds with Maximum Affinity to psqE, the Compounds in the Middle Are the Ones with Some Similar Affinity to Both Proteins, and the Right Column Contains Compounds with Higher Affinity to LasR
Left Column Shows the Compounds with Maximum Affinity to psqE, the Compounds in the Middle Are the Ones with Some Similar Affinity to Both Proteins, and the Right Column Contains Compounds with Higher Affinity to LasR

High similarity was seen between some of compounds listed in Table 1 and Figure 1 with tryptophan. Aromatic amino acids are known to be inhibitors of the pathway by regulating the first step of chorismate biosynthesis in the shikimate pathway (45). It can also be concluded from the data in Figure 3 that bigger compounds with a good degree of flexibility can fit the smaller active site of pqsE with partially degraded affinity.

5. Discussion

Pseudomonas aeruginosa is a multi-drug resistant pathogen known for its ubiquity, especially in war zone hospitals. It is well known that this opportunistic pathogen has intrinsically advanced antibiotic resistance mechanisms via coordinate gene expression and produces serious infections (1-3).

For these bacteria, quorum sensing (QS) plays an essential role for competitiveness in clinical or environmental sites (21). Bacterial QS system inhibition by QS Inhibitors (QSIs) may be applied in various fields such as medicine, food technology, and agriculture (4, 22).

Discovery and development of QSIs is attractive because these drugs reduce bacterial pathogenicity, via inhibition of QS and anti-biofilm effects, and so indirectly inhibit bacterial growth (13, 22). Furthermore, these drugs are not directly involved in the development of antibiotic resistance mechanisms (23).

For this reason, this study attempted to find novel targets with bacterial QS inhibition and anti-biofilm properties.

It is known that a broad range of P. aeruginosa virulence-related factors are regulated by QS LasR transcriptional regulator (30). Furthermore, although pqsE gene is not required for the synthesis of PQS, yet, is required for the production of many PQS-controlled virulence factors and for virulence in several models of infection. In other words, PqsE, as a regulator, can activate PQS-controlled genes without presence of PqsR and PQS (42).

Thus, it was concluded that dual inhibitors of LasR and pqsE would be of uttermost efficacy.

In this investigation, the above-mentioned pqseE was selected. On the other hand, the 3D structures of transcriptional regulators from P. aeruginosa involved in QS was elucidated (46, 47).

Because virtual screening is an integral part of many drug-discovery efforts and is widely used in pharmaceutical research, we applied this technique in a search for novel QSIs.

Considering that the currently available QSIs are inappropriate for human use, there is special interest in discovery of novel chemical agents. According to this, virtual screening approaches involve database filtering to exclude compounds containing toxic, reactive, or otherwise undesired groups (48).

In the present study, a database of 2300 compounds was screened because they were already FDA-approved for human use. Among the 20 introduced compounds, members of different drug groups can be found. The major sub group of the compounds is from the non-steroid anti-inflammatory drug group. It can be inferred that the active site of these proteins somewhat resembles COX. Steroids are also prominent among the suggested compounds. Thus, as a general guideline, bi-therapy of antibiotics and anti-inflammatory drugs of any type may reduce bacterial resistance in P. aeruginosa infections.

The software designed in this study provided a graphical user interface to Vina. It easily inputs required docking parameters using textboxes and buttons that reduce user training time in comparison to command-line interface of Vina. There is also no need for conversion of ligand files by the user. It detects ligand file formats and uses OpenBabel (49) to convert ligands to the PDB format. It provides Autodock vina for each ligand of a given dataset with parameters set in its GUI. After completing docking cycles, the software runs vina split to split docking results and analyzes the data. Finally it collects the best binding energy for each compound from the result files and displays and saves them in a text file in ascending order, assigning a rank number to each compound.

5.1. Conclusions

The present study provides new means of inhibiting bacterial resistance without relying on more potent bactericides or bacteriostatic compounds. The necessity to develop new anti-pathogenic drugs is critical, especially in the case of infections induced by P. aeruginosa, as it is a multidrug resistant pathogen and has intrinsically developed antibiotic resistance mechanisms by QS system and biofilm formation (50).

Therefore, compounds characterized in the present study prepare the potential for antibiotics to target infections that are insistently difficult to battle with the current antibiotics.

Acknowledgements

References

  • 1.

    Bjarnsholt T, Givskov M. The role of quorum sensing in the pathogenicity of the cunning aggressor Pseudomonas aeruginosa. Anal Bioanal Chem. 2007;387(2):409-14. [PubMed ID: 17019573]. https://doi.org/10.1007/s00216-006-0774-x.

  • 2.

    Frederiksen B, Koch C, Hoiby N. Antibiotic treatment of initial colonization with Pseudomonas aeruginosa postpones chronic infection and prevents deterioration of pulmonary function in cystic fibrosis. Pediatr Pulmonol. 1997;23(5):330-5. [PubMed ID: 9168506].

  • 3.

    Gjodsbol K, Christensen JJ, Karlsmark T, Jorgensen B, Klein BM, Krogfelt KA. Multiple bacterial species reside in chronic wounds: a longitudinal study. Int Wound J. 2006;3(3):225-31. [PubMed ID: 16984578]. https://doi.org/10.1111/j.1742-481X.2006.00159.x.

  • 4.

    Ding X, Yin B, Qian L, Zeng Z, Yang Z, Li H, et al. Screening for novel quorum-sensing inhibitors to interfere with the formation of Pseudomonas aeruginosa biofilm. J Med Microbiol. 2011;60(Pt 12):1827-34. [PubMed ID: 21852522]. https://doi.org/10.1099/jmm.0.024166-0.

  • 5.

    Rumbaugh KP, Griswold JA, Hamood AN. The role of quorum sensing in the in vivo virulence of Pseudomonas aeruginosa. Microbes Infect. 2000;2(14):1721-31. [PubMed ID: 11137045].

  • 6.

    Yufan C, Shiyin L, Zhibin L, Mingfa L, Jianuan Z, Lianhui Z. Quorum sensing and microbial drug resistance. Yi Chuan. 2016;38(10):881-93. [PubMed ID: 27806929]. https://doi.org/10.16288/j.yczz.16-141.

  • 7.

    Waters CM, Lu W, Rabinowitz JD, Bassler BL. Quorum sensing controls biofilm formation in Vibrio cholerae through modulation of cyclic di-GMP levels and repression of vpsT. J Bacteriol. 2008;190(7):2527-36. [PubMed ID: 18223081]. https://doi.org/10.1128/JB.01756-07.

  • 8.

    Mittal R, Aggarwal S, Sharma S, Chhibber S, Harjai K. Urinary tract infections caused by Pseudomonas aeruginosa: a minireview. J Infect Public Health. 2009;2(3):101-11. [PubMed ID: 20701869]. https://doi.org/10.1016/j.jiph.2009.08.003.

  • 9.

    Fuqua C, Winans SC. Localization of OccR-activated and TraR-activated promoters that express two ABC-type permeases and the traR gene of Ti plasmid pTiR10. Mol Microbiol. 1996;20(6):1199-210. [PubMed ID: 8809772].

  • 10.

    Costerton JW, Lewandowski Z, DeBeer D, Caldwell D, Korber D, James G. Biofilms, the customized microniche. J Bacteriol. 1994;176(8):2137-42. [PubMed ID: 8157581].

  • 11.

    Zhu H, Sun SJ. Inhibition of bacterial quorum sensing-regulated behaviors by Tremella fuciformis extract. Curr Microbiol. 2008;57(5):418-22. [PubMed ID: 18661179]. https://doi.org/10.1007/s00284-008-9215-8.

  • 12.

    Lewis K. Persister cells, dormancy and infectious disease. Nat Rev Microbiol. 2007;5(1):48-56. [PubMed ID: 17143318]. https://doi.org/10.1038/nrmicro1557.

  • 13.

    Jones SM, Dang TT, Martinuzzi R. Use of quorum sensing antagonists to deter the formation of crystalline Proteus mirabilis biofilms. Int J Antimicrob Agents. 2009;34(4):360-4. [PubMed ID: 19619987]. https://doi.org/10.1016/j.ijantimicag.2009.06.011.

  • 14.

    Donlan RM, Costerton JW. Biofilms: survival mechanisms of clinically relevant microorganisms. Clin Microbiol Rev. 2002;15(2):167-93. [PubMed ID: 11932229].

  • 15.

    Drenkard E. Antimicrobial resistance of Pseudomonas aeruginosa biofilms. Microbes Infect. 2003;5(13):1213-9. [PubMed ID: 14623017].

  • 16.

    Parsek MR, Greenberg EP. Acyl-homoserine lactone quorum sensing in gram-negative bacteria: a signaling mechanism involved in associations with higher organisms. Proc Natl Acad Sci U S A. 2000;97(16):8789-93. [PubMed ID: 10922036].

  • 17.

    Vannini A, Volpari C, Gargioli C, Muraglia E, Cortese R, De Francesco R, et al. The crystal structure of the quorum sensing protein TraR bound to its autoinducer and target DNA. EMBO J. 2002;21(17):4393-401. [PubMed ID: 12198141].

  • 18.

    Passador L, Cook JM, Gambello MJ, Rust L, Iglewski BH. Expression of Pseudomonas aeruginosa virulence genes requires cell-to-cell communication. Science. 1993;260(5111):1127-30. [PubMed ID: 8493556].

  • 19.

    Bergstrom CT, Lo M, Lipsitch M. Ecological theory suggests that antimicrobial cycling will not reduce antimicrobial resistance in hospitals. Proc Natl Acad Sci U S A. 2004;101(36):13285-90. [PubMed ID: 15308772]. https://doi.org/10.1073/pnas.0402298101.

  • 20.

    Boyen F, Eeckhaut V, Van Immerseel F, Pasmans F, Ducatelle R, Haesebrouck F. Quorum sensing in veterinary pathogens: mechanisms, clinical importance and future perspectives. Vet Microbiol. 2009;135(3-4):187-95. [PubMed ID: 19185433]. https://doi.org/10.1016/j.vetmic.2008.12.025.

  • 21.

    Hentzer M, Wu H, Andersen JB, Riedel K, Rasmussen TB, Bagge N, et al. Attenuation of Pseudomonas aeruginosa virulence by quorum sensing inhibitors. EMBO J. 2003;22(15):3803-15. [PubMed ID: 12881415]. https://doi.org/10.1093/emboj/cdg366.

  • 22.

    Rasmussen TB, Bjarnsholt T, Skindersoe ME, Hentzer M, Kristoffersen P, Kote M, et al. Screening for quorum-sensing inhibitors (QSI) by use of a novel genetic system, the QSI selector. J Bacteriol. 2005;187(5):1799-814. [PubMed ID: 15716452]. https://doi.org/10.1128/JB.187.5.1799-1814.2005.

  • 23.

    Rasmussen TB, Skindersoe ME, Bjarnsholt T, Phipps RK, Christensen KB, Jensen PO, et al. Identity and effects of quorum-sensing inhibitors produced by Penicillium species. Microbiology. 2005;151(Pt 5):1325-40. [PubMed ID: 15870443]. https://doi.org/10.1099/mic.0.27715-0.

  • 24.

    Ochsner UA, Reiser J. Autoinducer-mediated regulation of rhamnolipid biosurfactant synthesis in Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 1995;92(14):6424-8. [PubMed ID: 7604006].

  • 25.

    Winson MK, Camara M, Latifi A, Foglino M, Chhabra SR, Daykin M, et al. Multiple N-acyl-L-homoserine lactone signal molecules regulate production of virulence determinants and secondary metabolites in Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 1995;92(20):9427-31. [PubMed ID: 7568146].

  • 26.

    Holden I, Swift I, Williams I. New signal molecules on the quorum-sensing block. Trends Microbiol. 2000;8(3):101-4. discussion 103-4. [PubMed ID: 10707058].

  • 27.

    Wagner VE, Bushnell D, Passador L, Brooks AI, Iglewski BH. Microarray analysis of Pseudomonas aeruginosa quorum-sensing regulons: effects of growth phase and environment. J Bacteriol. 2003;185(7):2080-95. [PubMed ID: 12644477].

  • 28.

    Schuster M, Lostroh CP, Ogi T, Greenberg EP. Identification, timing, and signal specificity of Pseudomonas aeruginosa quorum-controlled genes: a transcriptome analysis. J Bacteriol. 2003;185(7):2066-79. [PubMed ID: 12644476].

  • 29.

    Favre-Bonte S, Pache JC, Robert J, Blanc D, Pechere JC, van Delden C. Detection of Pseudomonas aeruginosa cell-to-cell signals in lung tissue of cystic fibrosis patients. Microb Pathog. 2002;32(3):143-7. [PubMed ID: 11855945]. https://doi.org/10.1006/mpat.2001.0487.

  • 30.

    Diggle SP, Winzer K, Chhabra SR, Worrall KE, Camara M, Williams P. The Pseudomonas aeruginosa quinolone signal molecule overcomes the cell density-dependency of the quorum sensing hierarchy, regulates rhl-dependent genes at the onset of stationary phase and can be produced in the absence of LasR. Mol Microbiol. 2003;50(1):29-43. [PubMed ID: 14507361].

  • 31.

    Pesci EC, Milbank JB, Pearson JP, McKnight S, Kende AS, Greenberg EP, et al. Quinolone signaling in the cell-to-cell communication system of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 1999;96(20):11229-34. [PubMed ID: 10500159].

  • 32.

    Yu H, He X, Xie W, Xiong J, Sheng H, Guo S, et al. Elastase LasB of Pseudomonas aeruginosa promotes biofilm formation partly through rhamnolipid-mediated regulation. Can J Microbiol. 2014;60(4):227-35. [PubMed ID: 24693981]. https://doi.org/10.1139/cjm-2013-0667.

  • 33.

    Diggle SP, Cornelis P, Williams P, Camara M. 4-quinolone signalling in Pseudomonas aeruginosa: old molecules, new perspectives. Int J Med Microbiol. 2006;296(2-3):83-91. [PubMed ID: 16483840]. https://doi.org/10.1016/j.ijmm.2006.01.038.

  • 34.

    Bredenbruch F, Geffers R, Nimtz M, Buer J, Haussler S. The Pseudomonas aeruginosa quinolone signal (PQS) has an iron-chelating activity. Environ Microbiol. 2006;8(8):1318-29. [PubMed ID: 16872396]. https://doi.org/10.1111/j.1462-2920.2006.01025.x.

  • 35.

    Deziel E, Gopalan S, Tampakaki AP, Lepine F, Padfield KE, Saucier M, et al. The contribution of MvfR to Pseudomonas aeruginosa pathogenesis and quorum sensing circuitry regulation: multiple quorum sensing-regulated genes are modulated without affecting lasRI, rhlRI or the production of N-acyl-L-homoserine lactones. Mol Microbiol. 2005;55(4):998-1014. [PubMed ID: 15686549]. https://doi.org/10.1111/j.1365-2958.2004.04448.x.

  • 36.

    Xiao G, Deziel E, He J, Lepine F, Lesic B, Castonguay MH, et al. MvfR, a key Pseudomonas aeruginosa pathogenicity LTTR-class regulatory protein, has dual ligands. Mol Microbiol. 2006;62(6):1689-99. [PubMed ID: 17083468]. https://doi.org/10.1111/j.1365-2958.2006.05462.x.

  • 37.

    Cugini C, Calfee MW, Farrow J3, Morales DK, Pesci EC, Hogan DA. Farnesol, a common sesquiterpene, inhibits PQS production in Pseudomonas aeruginosa. Mol Microbiol. 2007;65(4):896-906. [PubMed ID: 17640272]. https://doi.org/10.1111/j.1365-2958.2007.05840.x.

  • 38.

    Cao H, Krishnan G, Goumnerov B, Tsongalis J, Tompkins R, Rahme LG. A quorum sensing-associated virulence gene of Pseudomonas aeruginosa encodes a LysR-like transcription regulator with a unique self-regulatory mechanism. Proc Natl Acad Sci U S A. 2001;98(25):14613-8. [PubMed ID: 11724939]. https://doi.org/10.1073/pnas.251465298.

  • 39.

    Wade DS, Calfee MW, Rocha ER, Ling EA, Engstrom E, Coleman JP, et al. Regulation of Pseudomonas quinolone signal synthesis in Pseudomonas aeruginosa. J Bacteriol. 2005;187(13):4372-80. [PubMed ID: 15968046]. https://doi.org/10.1128/JB.187.13.4372-4380.2005.

  • 40.

    D'Argenio DA, Calfee MW, Rainey PB, Pesci EC. Autolysis and autoaggregation in Pseudomonas aeruginosa colony morphology mutants. J Bacteriol. 2002;184(23):6481-9. [PubMed ID: 12426335].

  • 41.

    Gallagher LA, McKnight SL, Kuznetsova MS, Pesci EC, Manoil C. Functions required for extracellular quinolone signaling by Pseudomonas aeruginosa. J Bacteriol. 2002;184(23):6472-80. [PubMed ID: 12426334].

  • 42.

    Farrow J3, Sund ZM, Ellison ML, Wade DS, Coleman JP, Pesci EC. PqsE functions independently of PqsR-Pseudomonas quinolone signal and enhances the rhl quorum-sensing system. J Bacteriol. 2008;190(21):7043-51. [PubMed ID: 18776012]. https://doi.org/10.1128/JB.00753-08.

  • 43.

    Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-61. [PubMed ID: 19499576]. https://doi.org/10.1002/jcc.21334.

  • 44.

    Jafari Sabet M, Baratian A, Habibi M, Hadizadeh F. Iran virtual screening (IranVscreen): An integrated virtual screening interface. J Arch Mil Med. 2015;3(3). https://doi.org/10.5812/jamm.30745.

  • 45.

    Herrmann KM. The shikimate pathway as an entry to aromatic secondary metabolism. Plant Physiol. 1995;107(1):7-12. [PubMed ID: 7870841].

  • 46.

    Zou Y, Nair SK. Synthesis and molecular modeling provide insight in to a Pseudomonas aeruginosa quorum sensing conundrum. Chem Biol. 2009;16:961-70.

  • 47.

    Yu S, Jensen V, Seeliger J, Feldmann I, Weber S, Schleicher E, et al. Structure elucidation and preliminary assessment of hydrolase activity of PqsE, the Pseudomonas quinolone signal (PQS) response protein. Biochemistry. 2009;48(43):10298-307. [PubMed ID: 19788310]. https://doi.org/10.1021/bi900123j.

  • 48.

    Zeng Z, Qian L, Cao L, Tan H, Huang Y, Xue X, et al. Virtual screening for novel quorum sensing inhibitors to eradicate biofilm formation of Pseudomonas aeruginosa. Appl Microbiol Biotechnol. 2008;79(1):119-26. [PubMed ID: 18330563]. https://doi.org/10.1007/s00253-008-1406-5.

  • 49.

    O'Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR. Open Babel: An open chemical toolbox. J Cheminform. 2011;3:33. [PubMed ID: 21982300]. https://doi.org/10.1186/1758-2946-3-33.

  • 50.

    Furci LM, Lopes P, Eakanunkul S, Zhong S, MacKerell AD Jr, Wilks A. Inhibition of the bacterial heme oxygenases from Pseudomonas aeruginosa and Neisseria meningitidis: novel antimicrobial targets. J Med Chem. 2007;50(16):3804-13. [PubMed ID: 17629261]. https://doi.org/10.1021/jm0700969.