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Research article
Inhibition of Microbial Quorum Sensing Mediated Virulence Factors by Pestalotiopsis sydowiana
1Department of Microbiology, School of Life Sciences, Pondicherry University, Puducherry 605014, India 2Department of Biotechnology, School of Life Sciences, Pondicherry University, Puducherry 605014, India 3Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India 4Department of Chemical Engineering, Konkuk University, Seoul 05029, Republic of Korea 5Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Tejaswini Hills, Periya (P.O), Kasaragod, Kerala 671320, India
J. Microbiol. Biotechnol. 2020; 30(4): 571-582
Published April 28, 2020 https://doi.org/10.4014/jmb.1907.07030
Copyright © The Korean Society for Microbiology and Biotechnology.
Abstract
Keywords
Graphical Abstract

Introduction
Quorum sensing (QS) regulates the infectious diseases in bacteria [1]. It operates through the signaling molecules, that is, autoinducers. The QS system in bacteria coordinates and influences the expression of genes responsible for the secretion of various virulence factors and biofilm formation, which lead to pathogenicity. Inhibition of QS-mediated gene expression can help control bacterial infection and biofilm development without affecting their growth pattern [2, 3]. Due to this unique feature, the bacteria develop less resistance to QSIs compared to antibiotics [4]. In recent years, various QS inhibitors of chemical and biological origin have been reported [5-8].
Bioactive compounds from diverse organisms are gaining immense attention as QSIs [1, 15-24]. The present study aims to discover novel QSIs from the marine fungus against the biofilm-forming ability of
Materials and Methods
Microbial Strains, Culture Media, and Conditions
Fungi from dry wood samples were isolated on an agar plate and grown in 2% malt extract medium at 28 ± 2°C for 21 days. For the extraction of crude metabolites, the fungal isolates were cultivated in malt extract broth at same incubation conditions as aforementioned.
Collection of Samples, Isolation of Fungi, and Preparation of Crude Extract
Different dry wood samples were collected from the coast near the village of Muthupet, Cuddalore District, Tamil Nadu, India. Isolation of fungal species was executed by applying single spore isolation technique on malt extract agar. Morphologically distinct colonies of fungi were isolated and stored at −80°C with 25% glycerol. The selected fungal isolates were cultured for crude extract. Briefly, the fungi were subcultured in malt extract broth for 24 days and incubated at static conditions at 28 ± 2°C by adding 2% of inoculum in the culture medium. The cell-free supernatant of the culture broth was collected after centrifugation at 10,000 ×
Screening of Fungal Isolates for Their Violacein Inhibition Activity
Inhibition of violacein production in
Identification of Fungal Isolates
The fungal isolate presenting good anti-QS activity was identified by amplifying ITS region using ITS1 (5’ TCCGTAGGTGAACCTGCGG 3’) as forward primer and ITS4 (5’ TCCTCCGCTTATTGATATGC 3’) as reverse primer (Macrogen Inc., Seoul, South Korea). The nucleotide sequence result was equated with the DNA sequence in NCBI GenBank (https://blast.ncbi.nlm.nih.gov/Blast.cgi) to determine the closely related species. The ITS gene sequence of fungal isolate (PPR) was deposited to the NCBI GenBank database. Phylogeny was inferred using the neighbor-joining method in MEGA 5.04 software after aligning the sequences with CLUSTAL_W, and bootstrap analysis was carried out with 1000 replications [27].
Determination of Minimum Inhibitory Concentration (MIC) and Growth Curve Analysis
MIC of the fungal crude extract was determined using the microdilution method in order to study the effect of subinhibitory concentration (Sub-MIC) on QS-regulated virulence factors of the test bacterium,
Growth curve analysis was performed to determine the effect of sub-MIC of fungal crude extract on the growth of the test pathogen,
Violacein Inhibition Assay
The potential of the fungal extract in suppressing the violacein synthesis in
Pyocyanin Production
Quantitative determination of the effect of fungal extract on pyocyanin synthesis in
Azocasein-Degrading Proteolytic Activity
The effect of fungal extract on protease synthesis in
Elastase and Chitinase Assay
Elastolytic activity was determined by Elastin-Congo red (ECR) method [32]. Supernatant (0.1 ml) obtained from the overnight grown
Chitinase assay was performed by adopting the method described previously with slight modifications [33]. The culture supernatant obtained from the overnight grown
Staphylolytic Activity
Staphylolytic assay was performed to determine the effect of fungal extract on the LasA protease behavior of supernatant obtained for
Swimming and Swarming Motility Assay
Swimming and swarming motility was determined as described elsewhere [35]. Briefly, on the medium (1% tryptone, 0.5% NaCl, and 0.3% agar) for swimming and for swarming (1% peptone, 0.5% NaCl, 0.5% D-fructose, and 0.6% agar) amended with or without the fungal extract, was point inoculated with the test bacterium and incubated at 37°C for 24 h. After the incubation period, the plates were compared with the control (treated with 10% DMSO).
Effect of Fungal Extract Against the Biofilm of P. aeruginosa PAO1
The effect of fungal extract on biofilm development in
Exopolysaccharide (EPS) Production
EPS production by the test bacterium was qualitatively determined using Congo red agar (CRA) plate method [37]. The test bacterium,
Rhamnolipid Quantification
The effect of fungal extract on rhamnolipid production by
Alginate Production
The effect of fungal extract on synthesis of alginate by
Microscopic Analysis
The effect of fungal extract on the biofilm development in
Gas Chromatography-Mass Spectrometry (GC-MS) Analysis
The metabolites present in the crude extract were determined using GC-MS analysis. The GC model Clarus 680 with an ion-trap mass spectrometer model Clarus 600 (EI), equipped with Elite-5MS column having specifications of 30 m in length and 0.25 mm in thickness of the film, was employed for this experiment. The compounds were detected using an electron ionization system, which uses higher energy electrons (70 eV). Helium gas was applied as a carrier gas with a constant run of 1 ml/min. The temperature at the initial stage was set as 260°C and programmed with an increasing rate of 10°C per min during the chromatographic run. Next, 1 μl of fungal extract diluted in ethyl acetate was injected. By using GC-MS NIST (2008), the bioactive compounds present in the fungal extract were identified [40].
Receptor Protein Retrieval, Modeling, and Validation
The ligand binding domain of LasR was retrieved from the Protein Data Bank (PDB) ID:2UV0. The three-dimensional (3D) structure of the RhlR receptor molecule was built from the protein sequence retrieved from UniPort database (ID: P54292.1) in the ROBETTA server for protein structure modeling. The overall stereo chemistry quality assessment of the generated model of the RhlR structure was validated in the RAMPAGE web server (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) [41]. The best RhlR 3D-model after validation was selected for the docking studies.
Molecular Docking
The docking studies were carried out in Schrodinger Maestro software version 11.5 (Schrodinger, LLC, New York, NY, 2018) in order to understand the interaction of fungal metabolites against two major QS receptor proteins, LasR and RhlR, using the natural ligands, 3-oxo-C12-HSL and C4-HSL as reference molecules, respectively. The LasR and RhlR ligand binding domain molecule protein preparation was carried out using the protein preparation wizard of Maestro suite with default settings. The grid files were generated individually using Glide, version 7.8, in the Maestro software. For LasR, the docking site was generated around its autoinducer (3-oxo-C12-HSL) interacting residues, and the grid for RhlR was defined vicinity of the active site residue Trp-68 of its natural autoinducer (C4-HSL) [42]. The known anti-QS molecules biacelein and furanone C30 were used as positive controls for the QS receptors LasR and RhlR, respectively. The 3D structure files of all fungal metabolites from GC-MS analysis were collected from the PubChem database and prepared in the LigPrep module of Maestro software version 11.5 with enabled Epik option where other settings were set as default. The prepared receptor grids and ligands were docked in Glide, version 7.8 in Maestro suite, with enabled Extra Precision mode [43]. LigPlot+ version 1.4.5 and Chimera version 1.6.2 were used for 2D and 3D analysis, respectively. Among the identified compounds, two compounds, cyclo(-Leu-Pro) (CLP) and 4-hydroxyphenyl acetamide (4-HPA), showed promising docking scores with the QS receptors similar to those of the natural ligands. Thus, these compounds were subjected to the molecular dynamics simulation analysis to investigate the conformational changes in the QS receptor proteins following interaction with the natural ligands or bioactive compounds.
Molecular Dynamics Simulation
The results of molecular docking did not reveal the conformational changes found globally among the receptor proteins after interaction with their respective natural ligands or bioactive compounds, since the docking scores of interaction between the receptor and the ligand were determined at a particular region at a specific time. Through the molecular dynamics simulation study, we were able to detect the unwanted modification in the topology of the protein. The complexes of QS receptor proteins with selected bioactive compounds were simulated using GROMOS force field in the GROMACS v5.1.2 software [44]. The system was equilibrated under NVT and NPT ensembles before a final MD run of 50,000 ps with a time step of 2 fs. Post-simulation binding free energy of the complex formed by QS receptor protein and its natural ligand or bioactive compound and the interaction energy values were estimated using the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) analysis [45].
Effect of Bioactive Compounds of P. sydowiana PPR Crude Extract on P. aeruginosa PAO1
Based on the in silico results, the bioactive compounds CLP and 4-HPA were observed to show promising anti-QS properties, which were further confirmed by evaluating the bioactive compounds for their anti-QS activity against
The sub-MIC values of CLP and 4-HPA (100 and 62.5 μg/ml) were tested for anti-QS potential by assessing pyocyanin, chitinase, elastase, and staphylolytic activities as well as motility inhibition and reduction in biofilm formation according to the protocols mentioned above.
Gene Expression Studies
The effect of fungal bioactive compounds on the virulence genes of
RT-PCR was performed in a total volume of 10 μl containing SYBR Green Master Mix (Thermo Scientific, USA) on a Roche Light Cycle 480 system using appropriate primers (Table S1). The PCR cycling conditions were as follows: initial denaturation at 95°C for 10 min followed by denaturation at 95°C for 30 sec, annealing for 15 sec as mentioned in Table S1 and extension at 72°C for 15 min. These conditions were maintained for 45 cycles and the final extension was performed at 72°C for 5 min [46]. All samples were analyzed in triplicates and normalized to
Statistical Analysis
All the experiments were conducted thrice, and the data of the assays were expressed as mean values with standard deviation.
Results
Isolation and Screening of the Anti-QS Potential of Fungi
Fungi with anti-QS potential were isolated from the dry wood samples collected from the marine environment. A total of 14 distinct colonies of fungi were obtained as pure cultures using the single-spore isolation technique. The crude extracts from 14 fungal isolates showed variable degree of inhibition on violacein and pyocyanin production by
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Table 1 . Preliminary screening of extract of different fungal isolates against QS systems in the biosensor strain and test pathogen.
Sample Code Zone of inhibition (mm) Chromobacterium violaceum Pseudomonas aeruginosa PAO1250 μg/ml 500 μg/ml 250 μg/ml 500 μg/ml PPR 19.33 ± 1.52 24.67 ± 1.15 14.33 ± 2.08 19.00 ± 1.00 MC1 16.30 ± 1.53 16.30 ± 1.53 11.70 ± 1.53 14.00 ± 2.00 PM6 12.33 ± 0.57 14.00 ± 2.64 11.67 ± 1.52 15.33 ± 1.15 De20 11.67 ± 0.57 12.67 ± 1.52 9.00 ± 0.57 12.67 ± 0.57 DM19 11.00 ± 1.00 14.67 ± 1.52 8.33 ± 0.57 12.00 ± 1.00 DM15 10.67 ± 0.57 9.33 ± 1.52 9.66 ± 1.52 10.33 ± 0.57 DM2 11.00 ± 1.00 12.33 ± 2.08 8.00 ± 0.00 10.33 ± 1.52 DM38 11.00 ± 1.00 9.33 ± 1.52 8.00 ± 0.00 8.66 ± 1.15 DE29 9.66 ± 1.52 13.33 ± 1.15 10.00 ± 1.00 12.00 ± 2.00 DM32a 9.00 ± 1.00 10.33 ± 1.15 8.33 ± 0.57 8.33 ± 0.57 DM25 8.66 ± 0.57 13.00 ± 1.00 9.00 ± 1.00 11.00 ± 1.00 DE27 8.33 ± 0.57 13.33 ± 1.15 8.66 ± 1.15 9.33 ± 1.15 DE09 8.33 ± 0.57 11.33 ± 1.52 8.00 ± 0.00 12.00 ± 0.00 DM33 8.33 ± 0.57 11.67 ± 1.52 8.00 ± 0.00 9.00 ± 1.00
Characterization of Fungal Isolate
The light and phase contrast microscopic observations of PPR isolate presented an appendage-bearing conidial anamorphic form. The partial ITS rRNA gene sequence revealed 99% similarity with
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Fig. 1.
Culture plate image of Branch distances represent the nucleotide substitution rate and scale bar represents the changes per nucleotide position.Pestalotiopsis sydowiana PPR and phylogenetic tree based on ITS rRNA sequences using neighbor-joining of the strainP. sydowiana PPR.
Effect of Crude Extract on P. aeruginosa PAO1 Growth
The MIC was calculated using concentrations of fungal extract from 3.90 to 4,000 μg/ml. The fungal extract did not exhibit bactericidal effect on
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Fig. 2.
(A) Minimum inhibitory concentration of Pestalotiopsis sydowiana PPR extract onPseudomonas aeruginosa PAO1; (B) Growth curve analysis ofP. aeruginosa PAO1 treated with 250 and 500 μg/ml concentrations of fungal crude extract; (C)Effect of crude extract on QS-regulated virulence factors ofPseudomonas aeruginosa PAO1; (D) Effect of sub-MIC concentration of crude extract on biofilm attributes ofP. aeruginosa PAO1.
Effect of Fungal Extract on Violacein Production and Virulence Traits of P. aeruginosa PAO1
Violacein synthesis in
The ability of fungal extract in reducing the QS-dependent virulence phenotypes of
Inhibition of Motility and Microscopic Observation of Biofilms
The effect of fungal extract in suppressing both swimming and swarming motility of
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Fig. 3.
Microscopic observation of antibiofilm activity of fungal extract Pestalotiopsis sydowiana PPR and its bioactive compounds at sub-MIC concentration againstPseudomonas aeruginosa PAO1.
Effect of Fungal Extract on Biofilm of P. aeruginosa PAO1
The crude extract of PPR exhibited significant inhibition of
Inhibition of EPS, Rhamnolipid, and Alginate Production
The qualitative detection of the EPS production performed using Congo red plates is presented in Fig. S1. The control plate with black-colored colonies of
The results of GC-MS analysis revealed the presence of different metabolites in the fungal extract (Table S2). The major bioactive compounds present in
Molecular Modeling of RhlR and Molecular Docking
The 3D structure of the RhlR receptor molecule was modeled from the protein sequence retrieved from UniPort database (ID: P54292.1) using the ROBETTA on-line web server for structure modeling. The overall stereo chemistry quality assessment of the modeled RhlR structure was performed in the RAMPAGE web server. The overall stereochemistry qualities of built 3D-model structures of RhlR were accessed based on the psi/phi Ramachandran plot and the result demonstrated 100% presence of the amino acid residues in the favored region.
Molecular docking conferred better information about the interaction of bioactive compounds with LasR and RhlR receptor proteins. Natural ligands such as 3-oxo-C12-HSL and C4-HSL were used as reference models in molecular docking analyses for ligand interacting domains of LasR and RhlR, respectively. The molecular docking studies of different bioactive compounds identified in the crude extract of
Molecular Dynamics Simulation
Molecular dynamics simulation studies were conducted to determine the conformational modification in LasR QS receptor protein in the presence of signaling molecules and bioactive compounds. The simulations were performed with four complexes, LasR-C12HSL, LasR-BCL, LasR-CLP, and LasR-4-HPA. Similarly, the complexes of these ligands with RhlR were also subjected to the simulation process. The simulations were run for 50,000 ps with the time step of 2 fs. The root-mean-square deviation (RMSD) profile was generated to analyze the interaction of QS receptor proteins with the signaling molecules and bioactive compounds throughout the simulation process. The RMSD values of the complexes formed by QS receptors with their respective natural ligands and bioactive compounds were within the range of 2Å, indicating accurate docking [45]. Overall, the complexes were highly stable and RMSD values were maintained below 0.4 nm. Individual analysis based on RMSD showed that the LasR-3-oxo-C12HSL, LasR-BCL, LasR-CLP, and LasR-4HPA complexes were stable after ~12,000 ps, ~14,000 ps, ~20,000 ps, and ~15,000 ps, respectively. The fluctuations observed after ~35,000 ps and ~10,000 ps as well as the stability were maintained till the end of the simulation (Fig. 4A). In the case of RhlR, RMSD values of all the complexes were maintained below 0.8 nm. Individual analysis showed that the complex RhlR-C4-HSL was stable between ~10,000 ps and 40,000 ps, whereas RhlR-F30 attained stability at ~20,000 ps, and fluctuation was observed after 40,000 ps. RhlR-CLP maintained its stability between ~10,000 ps and 40,000 ps, whereas RhlR-4HPA complex was highly stable from ~10,000 ps and maintained its stability till the end of the simulation (Fig. 4B). The binding energy for LasR complex formation was −122.316 kJ/mol for LasR-C12-HSL, −164.58 kJ/mol for LasR-Baicalein, −52.930 kJ/mol for LasR-CLP and −100.375 kJ/mol for LasR-4HPA. In case of RhlR complexes, the binding energy values were −51.274 kJ/mol for RhlR-C4HSL, −93.732 kJ/mol for RhlR-Furanone C-30, −35.813 kJ/mol for RhlR-CLP and −95.881 kJ/mol for RhlR-4HPA (Table 2).
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Table 2 . MM/PBSA analysis: LasR and RhlR QS circuit with binding energy and their constituents (kJ/mol).
Ligand ID Van der Waals energy (kJ/mol) Binding energy (kJ/mol) Electrostatic energy (kJ/mol) Polar salvation energy (kJ/mol) SASA energy (kJ/mol) LasR -171.224 -122.316 -53.143 119.778 -17.700 C12-HSL CLP -119.284 -52.930 -34.116 112.670 -12.179 4-HPA -157.057 -100.375 -122.486 193.563 -14.433 BCL -190.142 -164.580 -3.662 45.533 -16.303 RhlR -105.598 -51.274 -45.407 111.066 -11.321 C4-HSL Furanone C30 -122.381 -93.732 -12.116 50.993 -10.194 CLP -78.249 -35.813 -22.521 73.401 -8.499 4-HPA -109.390 -95.881 -63.915 88.025 -10.654
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Fig. 4.
Root-mean-square deviation (RMSD) analysis with time for cyclo(-Leu-Pro) (CLP), 4-Hydroxyphenylacetamide (4-HPA), baicalein, and furanone C-30 along with (A) LasR and (B) RhlR. (C ) Effect of bioactive compounds on the production of QS-regulated virulence factors, biofilm, and its determinants inP. aeruginosa PAO1. (D ) Relative expression levels of QS-related genes ofP. aeruginosa PAO1 exposed with bioactive compounds. Normalized with the reference genepr°C. The error bar symbolized the standard deviation of the three independent values.
Effect of Bioactive Compounds of P. sydowiana PPR on the Growth of P. aeruginosa PAO1
The MIC of CLP, 4-HPA, and BCL (positive control) against
Anti-QS Potential of Bioactive Compounds
Pyocyanin is an important virulence factor secreted by
Gene Expression Studies
The RT-PCR results revealed the mRNA expression levels of different QS-regulated virulence genes of
Discussion
QS is a regulatory process that allows a bacterial population to collectively express various virulence factors associated with pathogenesis including biofilm formation [47-50]. Targeting the QS circuits of bacteria has been found to be a promising strategy to combat bacterial infections as an alternative to conventional antibiotics [51]. This therapeutic strategy potentially inhibits the production of pathogenic phenotypes of the bacteria without provoking any adverse effect on their growth. The marine ecosystem appeared to be a promising source of diverse biological active compounds with pharmaceutical applications [52]. The metabolites of different marine-derived bacteria, actinomycetes, and fungi were reported as potential inhibitors of QS and its regulatory factors [53]. In the present study we examined the potential of the marine-derived fungi as a source of antipathogenic molecules.
Zhang
The present study also presented the effect of fungal extract on the production of rhamnolipids, EPS, and alginate, the major components of the biofilm [30, 56]. Molecular docking study revealed that the metabolite (cyclo(-Leu-Pro) of PPR isolate adapts in the structure of receptor protein in a likely fashion to the natural ligands and positive controls (Figs. S2 and S3). RMSD profile revealed that throughout the simulation, complexes of both the QS receptors with bioactive compounds were equally stable when compared with the LasR signaling molecule complex. Hnamte
Among the different metabolites of
As mentioned previously, QS plays a significant role in the pathogenicity of
In conclusion, the effect of metabolites from
Supplemental Materials
Acknowledgments
We sincerely acknowledge Dr. G. Muralitharan, Department of Microbiology, Bharathidasan University, Tiruchirappalli for providing the Confocal Laser Scanning Microscope facility. This research work was financially supported by start-up research grant from Department of Science and Technology-The Science & Engineering Research Board (SB/YS/LS-32/2014). V.V. Sarma would like to offer his sincere gratitude to the grant of the Ministry of Earth Sciences, Government of India, under Sanction order: MOES/36/OO1S/Extra/40/2014/PC-IV dt.14.1.2015). This research was supported by Brain Pool grant (NRF-2019H1D3A2A01060226) by the National Research Foundation of Korea for work at Konkuk University (VCK). This research was also supported by the Basic Science Research Program through the NRF funded by the Ministry of Science, ICT & Future Planning [2019R1F1A1063131 (IWK) and 2019R1C1C1009766 (SKSP)].
Conflict of Interest
The authors have no financial conflicts of interest to declare.
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Related articles in JMB

Article
Research article
J. Microbiol. Biotechnol. 2020; 30(4): 571-582
Published online April 28, 2020 https://doi.org/10.4014/jmb.1907.07030
Copyright © The Korean Society for Microbiology and Biotechnology.
Inhibition of Microbial Quorum Sensing Mediated Virulence Factors by Pestalotiopsis sydowiana
Paramanantham Parasuraman1, B Devadatha2, V. Venkateswara Sarma2, Sampathkumar Ranganathan3, Dinakara Rao Ampasala3, Dhanasekhar Reddy5, Ranjith Kumavath5, In-Won Kim4, Sanjay K. S. Patel4, Vipin Chandra Kalia4*, Jung-Kul Lee4*, and Busi Siddhardha1*
1Department of Microbiology, School of Life Sciences, Pondicherry University, Puducherry 605014, India 2Department of Biotechnology, School of Life Sciences, Pondicherry University, Puducherry 605014, India 3Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India 4Department of Chemical Engineering, Konkuk University, Seoul 05029, Republic of Korea 5Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Tejaswini Hills, Periya (P.O), Kasaragod, Kerala 671320, India
Abstract
Quorum sensing (QS)-mediated infections cause severe diseases in human beings. The control of infectious diseases by inhibiting QS using antipathogenic drugs is a promising approach as antibiotics are proving inefficient in treating these diseases. Marine fungal (Pestalotiopsis sydowiana PPR) extract was found to possess effective antipathogenic characteristics. The minimum inhibitory concentration (MIC) of the fungal extract against test pathogen Pseudomonas aeruginosa PAO1 was 1,000 μg/ml. Sub-MIC concentrations (250 and 500 μg/ml) of fungal extract reduced QSregulated virulence phenotypes such as the production of pyocyanin, chitinase, protease, elastase, and staphylolytic activity in P. aeruginosa PAO1 by 84.15%, 73.15%, 67.37%, 62.37%, and 33.65%, respectively. Moreover, it also reduced the production of exopolysaccharides (74.99%), rhamnolipids (68.01%), and alginate (54.98%), and inhibited the biofilm formation of the bacteria by 90.54%. In silico analysis revealed that the metabolite of P. sydowiana PPR binds to the bacterial QS receptor proteins (LasR and RhlR) similar to their respective natural signaling molecules. Cyclo(- Leu-Pro) (CLP) and 4-Hydroxyphenylacetamide (4-HPA) were identified as potent bioactive compounds among the metabolites of P. sydowiana PPR using in silico approaches. The MIC values of CLP and 4-HPA against P. aeruginosa PAO1 were determined as 250 and 125 μg/ml, respectively. All the antivirulence assays were conducted at sub-MIC concentrations of CLP (125 μg/ml) and 4-HPA (62.5 μg/ml), which resulted in marked reduction in all the investigated virulence factors. This was further supported by gene expression studies. The findings suggest that the metabolites of P. sydowiana PPR can be employed as promising QS inhibitors that target pathogenic bacteria.
Keywords: Pseudomonas aeruginosa, anti-quorum sensing, Pestalotiopsis sydowiana, anti-biofilm, in silico, gene expression
Introduction
Quorum sensing (QS) regulates the infectious diseases in bacteria [1]. It operates through the signaling molecules, that is, autoinducers. The QS system in bacteria coordinates and influences the expression of genes responsible for the secretion of various virulence factors and biofilm formation, which lead to pathogenicity. Inhibition of QS-mediated gene expression can help control bacterial infection and biofilm development without affecting their growth pattern [2, 3]. Due to this unique feature, the bacteria develop less resistance to QSIs compared to antibiotics [4]. In recent years, various QS inhibitors of chemical and biological origin have been reported [5-8].
Bioactive compounds from diverse organisms are gaining immense attention as QSIs [1, 15-24]. The present study aims to discover novel QSIs from the marine fungus against the biofilm-forming ability of
Materials and Methods
Microbial Strains, Culture Media, and Conditions
Fungi from dry wood samples were isolated on an agar plate and grown in 2% malt extract medium at 28 ± 2°C for 21 days. For the extraction of crude metabolites, the fungal isolates were cultivated in malt extract broth at same incubation conditions as aforementioned.
Collection of Samples, Isolation of Fungi, and Preparation of Crude Extract
Different dry wood samples were collected from the coast near the village of Muthupet, Cuddalore District, Tamil Nadu, India. Isolation of fungal species was executed by applying single spore isolation technique on malt extract agar. Morphologically distinct colonies of fungi were isolated and stored at −80°C with 25% glycerol. The selected fungal isolates were cultured for crude extract. Briefly, the fungi were subcultured in malt extract broth for 24 days and incubated at static conditions at 28 ± 2°C by adding 2% of inoculum in the culture medium. The cell-free supernatant of the culture broth was collected after centrifugation at 10,000 ×
Screening of Fungal Isolates for Their Violacein Inhibition Activity
Inhibition of violacein production in
Identification of Fungal Isolates
The fungal isolate presenting good anti-QS activity was identified by amplifying ITS region using ITS1 (5’ TCCGTAGGTGAACCTGCGG 3’) as forward primer and ITS4 (5’ TCCTCCGCTTATTGATATGC 3’) as reverse primer (Macrogen Inc., Seoul, South Korea). The nucleotide sequence result was equated with the DNA sequence in NCBI GenBank (https://blast.ncbi.nlm.nih.gov/Blast.cgi) to determine the closely related species. The ITS gene sequence of fungal isolate (PPR) was deposited to the NCBI GenBank database. Phylogeny was inferred using the neighbor-joining method in MEGA 5.04 software after aligning the sequences with CLUSTAL_W, and bootstrap analysis was carried out with 1000 replications [27].
Determination of Minimum Inhibitory Concentration (MIC) and Growth Curve Analysis
MIC of the fungal crude extract was determined using the microdilution method in order to study the effect of subinhibitory concentration (Sub-MIC) on QS-regulated virulence factors of the test bacterium,
Growth curve analysis was performed to determine the effect of sub-MIC of fungal crude extract on the growth of the test pathogen,
Violacein Inhibition Assay
The potential of the fungal extract in suppressing the violacein synthesis in
Pyocyanin Production
Quantitative determination of the effect of fungal extract on pyocyanin synthesis in
Azocasein-Degrading Proteolytic Activity
The effect of fungal extract on protease synthesis in
Elastase and Chitinase Assay
Elastolytic activity was determined by Elastin-Congo red (ECR) method [32]. Supernatant (0.1 ml) obtained from the overnight grown
Chitinase assay was performed by adopting the method described previously with slight modifications [33]. The culture supernatant obtained from the overnight grown
Staphylolytic Activity
Staphylolytic assay was performed to determine the effect of fungal extract on the LasA protease behavior of supernatant obtained for
Swimming and Swarming Motility Assay
Swimming and swarming motility was determined as described elsewhere [35]. Briefly, on the medium (1% tryptone, 0.5% NaCl, and 0.3% agar) for swimming and for swarming (1% peptone, 0.5% NaCl, 0.5% D-fructose, and 0.6% agar) amended with or without the fungal extract, was point inoculated with the test bacterium and incubated at 37°C for 24 h. After the incubation period, the plates were compared with the control (treated with 10% DMSO).
Effect of Fungal Extract Against the Biofilm of P. aeruginosa PAO1
The effect of fungal extract on biofilm development in
Exopolysaccharide (EPS) Production
EPS production by the test bacterium was qualitatively determined using Congo red agar (CRA) plate method [37]. The test bacterium,
Rhamnolipid Quantification
The effect of fungal extract on rhamnolipid production by
Alginate Production
The effect of fungal extract on synthesis of alginate by
Microscopic Analysis
The effect of fungal extract on the biofilm development in
Gas Chromatography-Mass Spectrometry (GC-MS) Analysis
The metabolites present in the crude extract were determined using GC-MS analysis. The GC model Clarus 680 with an ion-trap mass spectrometer model Clarus 600 (EI), equipped with Elite-5MS column having specifications of 30 m in length and 0.25 mm in thickness of the film, was employed for this experiment. The compounds were detected using an electron ionization system, which uses higher energy electrons (70 eV). Helium gas was applied as a carrier gas with a constant run of 1 ml/min. The temperature at the initial stage was set as 260°C and programmed with an increasing rate of 10°C per min during the chromatographic run. Next, 1 μl of fungal extract diluted in ethyl acetate was injected. By using GC-MS NIST (2008), the bioactive compounds present in the fungal extract were identified [40].
Receptor Protein Retrieval, Modeling, and Validation
The ligand binding domain of LasR was retrieved from the Protein Data Bank (PDB) ID:2UV0. The three-dimensional (3D) structure of the RhlR receptor molecule was built from the protein sequence retrieved from UniPort database (ID: P54292.1) in the ROBETTA server for protein structure modeling. The overall stereo chemistry quality assessment of the generated model of the RhlR structure was validated in the RAMPAGE web server (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) [41]. The best RhlR 3D-model after validation was selected for the docking studies.
Molecular Docking
The docking studies were carried out in Schrodinger Maestro software version 11.5 (Schrodinger, LLC, New York, NY, 2018) in order to understand the interaction of fungal metabolites against two major QS receptor proteins, LasR and RhlR, using the natural ligands, 3-oxo-C12-HSL and C4-HSL as reference molecules, respectively. The LasR and RhlR ligand binding domain molecule protein preparation was carried out using the protein preparation wizard of Maestro suite with default settings. The grid files were generated individually using Glide, version 7.8, in the Maestro software. For LasR, the docking site was generated around its autoinducer (3-oxo-C12-HSL) interacting residues, and the grid for RhlR was defined vicinity of the active site residue Trp-68 of its natural autoinducer (C4-HSL) [42]. The known anti-QS molecules biacelein and furanone C30 were used as positive controls for the QS receptors LasR and RhlR, respectively. The 3D structure files of all fungal metabolites from GC-MS analysis were collected from the PubChem database and prepared in the LigPrep module of Maestro software version 11.5 with enabled Epik option where other settings were set as default. The prepared receptor grids and ligands were docked in Glide, version 7.8 in Maestro suite, with enabled Extra Precision mode [43]. LigPlot+ version 1.4.5 and Chimera version 1.6.2 were used for 2D and 3D analysis, respectively. Among the identified compounds, two compounds, cyclo(-Leu-Pro) (CLP) and 4-hydroxyphenyl acetamide (4-HPA), showed promising docking scores with the QS receptors similar to those of the natural ligands. Thus, these compounds were subjected to the molecular dynamics simulation analysis to investigate the conformational changes in the QS receptor proteins following interaction with the natural ligands or bioactive compounds.
Molecular Dynamics Simulation
The results of molecular docking did not reveal the conformational changes found globally among the receptor proteins after interaction with their respective natural ligands or bioactive compounds, since the docking scores of interaction between the receptor and the ligand were determined at a particular region at a specific time. Through the molecular dynamics simulation study, we were able to detect the unwanted modification in the topology of the protein. The complexes of QS receptor proteins with selected bioactive compounds were simulated using GROMOS force field in the GROMACS v5.1.2 software [44]. The system was equilibrated under NVT and NPT ensembles before a final MD run of 50,000 ps with a time step of 2 fs. Post-simulation binding free energy of the complex formed by QS receptor protein and its natural ligand or bioactive compound and the interaction energy values were estimated using the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) analysis [45].
Effect of Bioactive Compounds of P. sydowiana PPR Crude Extract on P. aeruginosa PAO1
Based on the in silico results, the bioactive compounds CLP and 4-HPA were observed to show promising anti-QS properties, which were further confirmed by evaluating the bioactive compounds for their anti-QS activity against
The sub-MIC values of CLP and 4-HPA (100 and 62.5 μg/ml) were tested for anti-QS potential by assessing pyocyanin, chitinase, elastase, and staphylolytic activities as well as motility inhibition and reduction in biofilm formation according to the protocols mentioned above.
Gene Expression Studies
The effect of fungal bioactive compounds on the virulence genes of
RT-PCR was performed in a total volume of 10 μl containing SYBR Green Master Mix (Thermo Scientific, USA) on a Roche Light Cycle 480 system using appropriate primers (Table S1). The PCR cycling conditions were as follows: initial denaturation at 95°C for 10 min followed by denaturation at 95°C for 30 sec, annealing for 15 sec as mentioned in Table S1 and extension at 72°C for 15 min. These conditions were maintained for 45 cycles and the final extension was performed at 72°C for 5 min [46]. All samples were analyzed in triplicates and normalized to
Statistical Analysis
All the experiments were conducted thrice, and the data of the assays were expressed as mean values with standard deviation.
Results
Isolation and Screening of the Anti-QS Potential of Fungi
Fungi with anti-QS potential were isolated from the dry wood samples collected from the marine environment. A total of 14 distinct colonies of fungi were obtained as pure cultures using the single-spore isolation technique. The crude extracts from 14 fungal isolates showed variable degree of inhibition on violacein and pyocyanin production by
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Table 1 . Preliminary screening of extract of different fungal isolates against QS systems in the biosensor strain and test pathogen..
Sample Code Zone of inhibition (mm) Chromobacterium violaceum Pseudomonas aeruginosa PAO1250 μg/ml 500 μg/ml 250 μg/ml 500 μg/ml PPR 19.33 ± 1.52 24.67 ± 1.15 14.33 ± 2.08 19.00 ± 1.00 MC1 16.30 ± 1.53 16.30 ± 1.53 11.70 ± 1.53 14.00 ± 2.00 PM6 12.33 ± 0.57 14.00 ± 2.64 11.67 ± 1.52 15.33 ± 1.15 De20 11.67 ± 0.57 12.67 ± 1.52 9.00 ± 0.57 12.67 ± 0.57 DM19 11.00 ± 1.00 14.67 ± 1.52 8.33 ± 0.57 12.00 ± 1.00 DM15 10.67 ± 0.57 9.33 ± 1.52 9.66 ± 1.52 10.33 ± 0.57 DM2 11.00 ± 1.00 12.33 ± 2.08 8.00 ± 0.00 10.33 ± 1.52 DM38 11.00 ± 1.00 9.33 ± 1.52 8.00 ± 0.00 8.66 ± 1.15 DE29 9.66 ± 1.52 13.33 ± 1.15 10.00 ± 1.00 12.00 ± 2.00 DM32a 9.00 ± 1.00 10.33 ± 1.15 8.33 ± 0.57 8.33 ± 0.57 DM25 8.66 ± 0.57 13.00 ± 1.00 9.00 ± 1.00 11.00 ± 1.00 DE27 8.33 ± 0.57 13.33 ± 1.15 8.66 ± 1.15 9.33 ± 1.15 DE09 8.33 ± 0.57 11.33 ± 1.52 8.00 ± 0.00 12.00 ± 0.00 DM33 8.33 ± 0.57 11.67 ± 1.52 8.00 ± 0.00 9.00 ± 1.00
Characterization of Fungal Isolate
The light and phase contrast microscopic observations of PPR isolate presented an appendage-bearing conidial anamorphic form. The partial ITS rRNA gene sequence revealed 99% similarity with
-
Figure 1.
Culture plate image of Branch distances represent the nucleotide substitution rate and scale bar represents the changes per nucleotide position.Pestalotiopsis sydowiana PPR and phylogenetic tree based on ITS rRNA sequences using neighbor-joining of the strainP. sydowiana PPR.
Effect of Crude Extract on P. aeruginosa PAO1 Growth
The MIC was calculated using concentrations of fungal extract from 3.90 to 4,000 μg/ml. The fungal extract did not exhibit bactericidal effect on
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Figure 2.
(A) Minimum inhibitory concentration of Pestalotiopsis sydowiana PPR extract onPseudomonas aeruginosa PAO1; (B) Growth curve analysis ofP. aeruginosa PAO1 treated with 250 and 500 μg/ml concentrations of fungal crude extract; (C)Effect of crude extract on QS-regulated virulence factors ofPseudomonas aeruginosa PAO1; (D) Effect of sub-MIC concentration of crude extract on biofilm attributes ofP. aeruginosa PAO1.
Effect of Fungal Extract on Violacein Production and Virulence Traits of P. aeruginosa PAO1
Violacein synthesis in
The ability of fungal extract in reducing the QS-dependent virulence phenotypes of
Inhibition of Motility and Microscopic Observation of Biofilms
The effect of fungal extract in suppressing both swimming and swarming motility of
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Figure 3.
Microscopic observation of antibiofilm activity of fungal extract Pestalotiopsis sydowiana PPR and its bioactive compounds at sub-MIC concentration againstPseudomonas aeruginosa PAO1.
Effect of Fungal Extract on Biofilm of P. aeruginosa PAO1
The crude extract of PPR exhibited significant inhibition of
Inhibition of EPS, Rhamnolipid, and Alginate Production
The qualitative detection of the EPS production performed using Congo red plates is presented in Fig. S1. The control plate with black-colored colonies of
The results of GC-MS analysis revealed the presence of different metabolites in the fungal extract (Table S2). The major bioactive compounds present in
Molecular Modeling of RhlR and Molecular Docking
The 3D structure of the RhlR receptor molecule was modeled from the protein sequence retrieved from UniPort database (ID: P54292.1) using the ROBETTA on-line web server for structure modeling. The overall stereo chemistry quality assessment of the modeled RhlR structure was performed in the RAMPAGE web server. The overall stereochemistry qualities of built 3D-model structures of RhlR were accessed based on the psi/phi Ramachandran plot and the result demonstrated 100% presence of the amino acid residues in the favored region.
Molecular docking conferred better information about the interaction of bioactive compounds with LasR and RhlR receptor proteins. Natural ligands such as 3-oxo-C12-HSL and C4-HSL were used as reference models in molecular docking analyses for ligand interacting domains of LasR and RhlR, respectively. The molecular docking studies of different bioactive compounds identified in the crude extract of
Molecular Dynamics Simulation
Molecular dynamics simulation studies were conducted to determine the conformational modification in LasR QS receptor protein in the presence of signaling molecules and bioactive compounds. The simulations were performed with four complexes, LasR-C12HSL, LasR-BCL, LasR-CLP, and LasR-4-HPA. Similarly, the complexes of these ligands with RhlR were also subjected to the simulation process. The simulations were run for 50,000 ps with the time step of 2 fs. The root-mean-square deviation (RMSD) profile was generated to analyze the interaction of QS receptor proteins with the signaling molecules and bioactive compounds throughout the simulation process. The RMSD values of the complexes formed by QS receptors with their respective natural ligands and bioactive compounds were within the range of 2Å, indicating accurate docking [45]. Overall, the complexes were highly stable and RMSD values were maintained below 0.4 nm. Individual analysis based on RMSD showed that the LasR-3-oxo-C12HSL, LasR-BCL, LasR-CLP, and LasR-4HPA complexes were stable after ~12,000 ps, ~14,000 ps, ~20,000 ps, and ~15,000 ps, respectively. The fluctuations observed after ~35,000 ps and ~10,000 ps as well as the stability were maintained till the end of the simulation (Fig. 4A). In the case of RhlR, RMSD values of all the complexes were maintained below 0.8 nm. Individual analysis showed that the complex RhlR-C4-HSL was stable between ~10,000 ps and 40,000 ps, whereas RhlR-F30 attained stability at ~20,000 ps, and fluctuation was observed after 40,000 ps. RhlR-CLP maintained its stability between ~10,000 ps and 40,000 ps, whereas RhlR-4HPA complex was highly stable from ~10,000 ps and maintained its stability till the end of the simulation (Fig. 4B). The binding energy for LasR complex formation was −122.316 kJ/mol for LasR-C12-HSL, −164.58 kJ/mol for LasR-Baicalein, −52.930 kJ/mol for LasR-CLP and −100.375 kJ/mol for LasR-4HPA. In case of RhlR complexes, the binding energy values were −51.274 kJ/mol for RhlR-C4HSL, −93.732 kJ/mol for RhlR-Furanone C-30, −35.813 kJ/mol for RhlR-CLP and −95.881 kJ/mol for RhlR-4HPA (Table 2).
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Table 2 . MM/PBSA analysis: LasR and RhlR QS circuit with binding energy and their constituents (kJ/mol)..
Ligand ID Van der Waals energy (kJ/mol) Binding energy (kJ/mol) Electrostatic energy (kJ/mol) Polar salvation energy (kJ/mol) SASA energy (kJ/mol) LasR -171.224 -122.316 -53.143 119.778 -17.700 C12-HSL CLP -119.284 -52.930 -34.116 112.670 -12.179 4-HPA -157.057 -100.375 -122.486 193.563 -14.433 BCL -190.142 -164.580 -3.662 45.533 -16.303 RhlR -105.598 -51.274 -45.407 111.066 -11.321 C4-HSL Furanone C30 -122.381 -93.732 -12.116 50.993 -10.194 CLP -78.249 -35.813 -22.521 73.401 -8.499 4-HPA -109.390 -95.881 -63.915 88.025 -10.654
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Figure 4.
Root-mean-square deviation (RMSD) analysis with time for cyclo(-Leu-Pro) (CLP), 4-Hydroxyphenylacetamide (4-HPA), baicalein, and furanone C-30 along with (A) LasR and (B) RhlR. (C ) Effect of bioactive compounds on the production of QS-regulated virulence factors, biofilm, and its determinants inP. aeruginosa PAO1. (D ) Relative expression levels of QS-related genes ofP. aeruginosa PAO1 exposed with bioactive compounds. Normalized with the reference genepr°C. The error bar symbolized the standard deviation of the three independent values.
Effect of Bioactive Compounds of P. sydowiana PPR on the Growth of P. aeruginosa PAO1
The MIC of CLP, 4-HPA, and BCL (positive control) against
Anti-QS Potential of Bioactive Compounds
Pyocyanin is an important virulence factor secreted by
Gene Expression Studies
The RT-PCR results revealed the mRNA expression levels of different QS-regulated virulence genes of
Discussion
QS is a regulatory process that allows a bacterial population to collectively express various virulence factors associated with pathogenesis including biofilm formation [47-50]. Targeting the QS circuits of bacteria has been found to be a promising strategy to combat bacterial infections as an alternative to conventional antibiotics [51]. This therapeutic strategy potentially inhibits the production of pathogenic phenotypes of the bacteria without provoking any adverse effect on their growth. The marine ecosystem appeared to be a promising source of diverse biological active compounds with pharmaceutical applications [52]. The metabolites of different marine-derived bacteria, actinomycetes, and fungi were reported as potential inhibitors of QS and its regulatory factors [53]. In the present study we examined the potential of the marine-derived fungi as a source of antipathogenic molecules.
Zhang
The present study also presented the effect of fungal extract on the production of rhamnolipids, EPS, and alginate, the major components of the biofilm [30, 56]. Molecular docking study revealed that the metabolite (cyclo(-Leu-Pro) of PPR isolate adapts in the structure of receptor protein in a likely fashion to the natural ligands and positive controls (Figs. S2 and S3). RMSD profile revealed that throughout the simulation, complexes of both the QS receptors with bioactive compounds were equally stable when compared with the LasR signaling molecule complex. Hnamte
Among the different metabolites of
As mentioned previously, QS plays a significant role in the pathogenicity of
In conclusion, the effect of metabolites from
Supplemental Materials
Acknowledgments
We sincerely acknowledge Dr. G. Muralitharan, Department of Microbiology, Bharathidasan University, Tiruchirappalli for providing the Confocal Laser Scanning Microscope facility. This research work was financially supported by start-up research grant from Department of Science and Technology-The Science & Engineering Research Board (SB/YS/LS-32/2014). V.V. Sarma would like to offer his sincere gratitude to the grant of the Ministry of Earth Sciences, Government of India, under Sanction order: MOES/36/OO1S/Extra/40/2014/PC-IV dt.14.1.2015). This research was supported by Brain Pool grant (NRF-2019H1D3A2A01060226) by the National Research Foundation of Korea for work at Konkuk University (VCK). This research was also supported by the Basic Science Research Program through the NRF funded by the Ministry of Science, ICT & Future Planning [2019R1F1A1063131 (IWK) and 2019R1C1C1009766 (SKSP)].
Conflict of Interest
The authors have no financial conflicts of interest to declare.
Fig 1.

Fig 2.

Fig 3.

Fig 4.

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Table 1 . Preliminary screening of extract of different fungal isolates against QS systems in the biosensor strain and test pathogen..
Sample Code Zone of inhibition (mm) Chromobacterium violaceum Pseudomonas aeruginosa PAO1250 μg/ml 500 μg/ml 250 μg/ml 500 μg/ml PPR 19.33 ± 1.52 24.67 ± 1.15 14.33 ± 2.08 19.00 ± 1.00 MC1 16.30 ± 1.53 16.30 ± 1.53 11.70 ± 1.53 14.00 ± 2.00 PM6 12.33 ± 0.57 14.00 ± 2.64 11.67 ± 1.52 15.33 ± 1.15 De20 11.67 ± 0.57 12.67 ± 1.52 9.00 ± 0.57 12.67 ± 0.57 DM19 11.00 ± 1.00 14.67 ± 1.52 8.33 ± 0.57 12.00 ± 1.00 DM15 10.67 ± 0.57 9.33 ± 1.52 9.66 ± 1.52 10.33 ± 0.57 DM2 11.00 ± 1.00 12.33 ± 2.08 8.00 ± 0.00 10.33 ± 1.52 DM38 11.00 ± 1.00 9.33 ± 1.52 8.00 ± 0.00 8.66 ± 1.15 DE29 9.66 ± 1.52 13.33 ± 1.15 10.00 ± 1.00 12.00 ± 2.00 DM32a 9.00 ± 1.00 10.33 ± 1.15 8.33 ± 0.57 8.33 ± 0.57 DM25 8.66 ± 0.57 13.00 ± 1.00 9.00 ± 1.00 11.00 ± 1.00 DE27 8.33 ± 0.57 13.33 ± 1.15 8.66 ± 1.15 9.33 ± 1.15 DE09 8.33 ± 0.57 11.33 ± 1.52 8.00 ± 0.00 12.00 ± 0.00 DM33 8.33 ± 0.57 11.67 ± 1.52 8.00 ± 0.00 9.00 ± 1.00
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Table 2 . MM/PBSA analysis: LasR and RhlR QS circuit with binding energy and their constituents (kJ/mol)..
Ligand ID Van der Waals energy (kJ/mol) Binding energy (kJ/mol) Electrostatic energy (kJ/mol) Polar salvation energy (kJ/mol) SASA energy (kJ/mol) LasR -171.224 -122.316 -53.143 119.778 -17.700 C12-HSL CLP -119.284 -52.930 -34.116 112.670 -12.179 4-HPA -157.057 -100.375 -122.486 193.563 -14.433 BCL -190.142 -164.580 -3.662 45.533 -16.303 RhlR -105.598 -51.274 -45.407 111.066 -11.321 C4-HSL Furanone C30 -122.381 -93.732 -12.116 50.993 -10.194 CLP -78.249 -35.813 -22.521 73.401 -8.499 4-HPA -109.390 -95.881 -63.915 88.025 -10.654
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