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 Table of Contents  
ORIGINAL RESEARCH
Year : 2021  |  Volume : 13  |  Issue : 6  |  Page : 586-592

Pharmacophore-based screening of autoinducer-2 inhibitor in bacteria for prevention of oral biofilm formation: An exploratory study


1 Department of Orthodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Velappanchavadi, India
2 Saveetha Institute of Medical and Technical Sciences, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai, Tamil Nadu, India

Date of Submission09-Jul-2021
Date of Decision23-Sep-2021
Date of Acceptance29-Sep-2021
Date of Web Publication30-Nov-2021

Correspondence Address:
Dr. Shantha Sundari
Department of Orthodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Velappanchavadi, Chennai 600077, Tamil Nadu.
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JIOH.JIOH_168_21

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  Abstract 

Aim: The aim of this study was to predict the 3D structure of luxS of Fusobacterium nucleatum and identification of key residues by in silico homology modeling and molecular docking for inhibiting autoinducer-2 (AI-2), responsible for biofilm formation. Materials and Methods: The current study was to explore 3D structure of luxS protein along with its major residues that are directly responsible for the activity by homology modeling employing Discovery Studio V4.0. Further, a ligand-based pharmacophore was generated, employing the known ligands to control AI-2 producing enzymes and to ultimately regulate biofilm formation in the oral environment subjecting to key bioinformatics tools. Results: The multiple sequence alignment study showed 26 and 56% similarity in target and template sequences of luxS protein, respectively. Homology modeling indicated high structural similarity between the two luxS proteins (homocysteine and 4, 5-dihydroxy-2, 3 pentanedione) with a low root mean square value of 0.6 Å, in addition to leading to major mutations that are responsible for the production of AI-2. A pharmacophore model was generated as a template for virtual screening to explore potent luxS inhibitor. ZINC15 database was used for similarity search algorithms and screening against a generated pharmacophore model. During molecular docking, a molecule was structurally identified with a high libdock score and significant binding energy, in addition to establishing a regulatory mechanism with the receptor protein. Conclusions: This investigation paves way for the high throughput virtual screening to characterize luxS and associated proteins resulting in considerable minimization of time and funds before taking up biological confirmatory tests in the wet laboratories during exploration of possible inhibitors.

Keywords: Autoinducer-2, Biofilm, Discovery Studio, Homology Modeling, luxS Protein, Molecular Docking, Pharmacophore, Quorum Sensing


How to cite this article:
Sundari S, Rajagopal R, Vijayaragavan R. Pharmacophore-based screening of autoinducer-2 inhibitor in bacteria for prevention of oral biofilm formation: An exploratory study. J Int Oral Health 2021;13:586-92

How to cite this URL:
Sundari S, Rajagopal R, Vijayaragavan R. Pharmacophore-based screening of autoinducer-2 inhibitor in bacteria for prevention of oral biofilm formation: An exploratory study. J Int Oral Health [serial online] 2021 [cited 2022 Jan 27];13:586-92. Available from: https://www.jioh.org/text.asp?2021/13/6/586/331601


  Introduction Top


Quorum sensing (QS), is a mechanism of communication among organisms, through signal molecules, which can affect microbial attachment through biofilm formation.[1] Targeting the biofilm formation through QS inhibitors (QSIs), is therefore considered an ideal choice to control the bacterial infection.[2] The other methods proposed have been antibiotics with antimicrobial peptides[3] or bacteriophages[4],[5],[6],[7],[8] and peptidimimetics[9],[10] to name a few. One of the first natural QSIs isolated is bromated furanone from Delisea pulchra (a red alga of marine origin), a product used for the synthesis of many novel inhibitory molecules.[11]

Autoinducer-2 (AI-2), is a well-known QS molecule, that mediates many communication processes, especially inducing biofilm formation among various microbial communities.[12] AI-2 is suggested to be produced and received by the commensal bacteria at picomolar concentrations in a highly pathogenic population. Higher concentrations of AI-2, in turn, enhance the multiplication of pathogens and decrease the commensal bacterial population leading to matured subgingival plaque formation in periodontitis.[12] Chemically, AI-2 is formed through the natural reorganization of 4, 5-dihydroxy-2, 3-pentanedione (DPD), produced by the enzyme luxS.

LuxS gene, a QS molecule formed by various Gram-positive and Gram-negative bacteria is primarily responsible for AI-2 synthesis.[13] Two prime products of the luxS, namely, homocysteine and DPD possess imperative functions in central metabolism and QS, respectively. Because a diverse number of bacteria react well with AI-2, it has been projected as a universal signaling molecule,[14] although three types of autoinducers such as AI-1 (N-acyl homoserine lactones, AHLs), autoinducing peptide, and AI-2 have been reported so far.[15]

Both luxS and AI-2 are responsible for the crucial control of precise factors to global influences on transcription. Their possible mechanisms of modulating biofilm growth are cell motility, bacterial conjugation, and biofilm formation;[16] altered exopolysaccharide production;[17] and regulation of virulence.[18] Mutated luxS adversely impacts planktonic bacterial development and the disrupted growth has a phenomenal effect on biofilm formation.[19] The diverse effect of luxS and AI-2 on biofilm formation like an increase in Escherichia coli[20] and Streptococcus suis,[21] and a decrease in Staphylococcus aureus and Bacillus cereus.[22] It differs with organisms with respect to various factors[23],[24],[25] and mode of action.[26],[27] Studies reveal that Fusobacterium nucleatum acts as the chief coaggregation bridge connecting early colonizers and final pathogenic colonizers formed in dental biofilms.[28],[29] It has been hypothesized of producing AI-2 favoring biofilm development and coaggregation of periodontal pathogens.

Inhibition of QS or communication among oral bacteria would certainly slow down the rate of deterioration of oral health. Study on modulation of LuxS to inhibit QS is therefore absolutely necessary. There are no available reports depicting the structural model of protein luxS.[10] To pursue such studies, the current study is an in silico homology modeling to predict the 3D structure of luxS present in F. nucleatum and identification of key residues responsible for its activity on biofilm formation. The current study is thus, intended to unveil the contribution of AI-2 in the prevention of oral biofilm formation by screening the AI-2 inhibitor, namely, luxS in F. nucleatum.


  Materials and Methods Top


Setting and design

Discovery Studio v4.0 was used to carry out the computational modeling and docking studies carried out in the current work.

Homology modeling

The 3D structure of luxS protein from F. nucleatum is presently not available. The homology modeling module of Discovery Studio was used to generate the 3D structures of luxS protein. Crystal structure of luxS protein from Bacillus subtilis obtained through an extensive literature survey was used as a template for modeling. ClustalW was used to align the target and the template sequence, and to identify the variation. The generated 3D structures were aligned to the template using the superimposition module of Discovery Studio.

Pharmacophore generation

Pharmacophore modeling is one of the most frequently and widely used methods to discover novel conformers for various targets with utmost accuracy. Among the different methods of conformer generation in Discovery Studio, the BEST method algorithm was used to find the perfect merged feature pharmacophore resulting from the known library of inhibitors. Pharmacophore model was constructed using five compounds that have the potential to inhibit luxS protein were selected after an extensive literature survey. Pharmacophore was generated based on the merged pharmacophore featured of the selected inhibitors. All default parameters were used to generate the merged feature pharmacophore. This process ensures that the screened lead molecules possess the molecular features required for potential inhibition of the luxS protein. Discovery Studio was used to carry out ligand-based pharmacophore screening, in which the libraries of compounds were screened against the pharmacophore skeleton of the known inhibitors.

Virtual screening and docking

The library of ligands was obtained from ZINC 15 database. ZINC15, a freely available database for commercially marketed compounds, was used for in silico screening. ZINC15 comprises approximately 230 million commercial compounds which are ready-to-dock and available in 3D formats. Approximately 6,00,000 related compounds were also collected in this investigation by using similarity search algorithms. In addition, an extensive literature survey was carried out to identify potential lead compounds with luxS inhibitory activity. Libdock module of Discovery Studio was used for molecular docking. Preparation of protein was carried out using the protein preparation wizard module of Discovery Studio. Similarly, the Ligprep module was used for ligand preparation. Database of ligands for virtual screening was created for screening against the target of interest. Pharmacophore-based database searching was used to find potential hit compounds that could repress or trigger luxS activity. The Fast Flexible search method from Ligand Pharmacophore Mapping/Digital Studio was applied to retrieve hits that satisfy the chemical moiety requirements and spatially map with corresponding features in the pharmacophore query. Analysis, superimposition, and calculation of root mean square (RMS) of the model were also carried out using Discovery Studio v4.0.


  Results Top


Homology modeling of luxS protein

Multiple sequence alignment indicated 26% sequence identity and 56% similarity between the target and template sequence. As there are no structures of luxS protein available at present for F. nucleatum, homology modeling was carried out with a template of luxS protein from B. subtilis [Figure 1]. With this information, homology modeling results depicted a high structural similarity between the two luxS proteins, and an RMS value as low as 0.6 Å was observed [Figure 2]. Key mutations included Cys(41) -> Lys, Leu(140) ->Glu, Glu(95) -> Lys for which it contributes a major part during AI-2 signaling. Ligands interacting with these residues can as well inhibit the luxS protein for producing AI-2.
Figure 1: Multiple sequence alignment between luxS of Fusobacterium nucleatum with luxS from Bacillus subtilis

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Figure 2: Alignment between the target luxS protein (yellow) from Fusobactrium nucleatum with template luxS protein (green) from Bacillus subtilis showing RMS of 0.6 Å

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Pharmacophore model generation and high throughput screening

Extensive literature review was carried out to find a potent luxS inhibitor with proven activity for preventing the production of AI-2. Five compounds were obtained and were used to create a common feature pharmacophore model. The selected compounds include 2-(4-amino-5H–pyrrolo [3,2-d]pyrimidin-7-yl)-5-(hydroxymethyl) pyrrolidine-3,4-diol, 3-butyl-5-(dibromomethylene)-2(5H)-furanone, (2S)-2-amino-4-[(2R,3S)-2,3-dihydroxy-3-N-hydroxycarbamoyl-propylmercapto] butyric acid, N-(4-fluorophenyl) sulfonyl-N-methyl-4-propyl-benzenesulfonamide. This pharmacophore model depicts the key interactions which are essential for the inhibition of the target protein [Figure 3]. The generated pharmacophore model was further used as a template for virtual screening.
Figure 3: A common feature pharmacophore generated using the selected top compounds depicting hydrogen bond acceptors (green), hydrogen bond donors (purple), and ionizable groups (red)

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ZINC15, a freely available database for commercially marketed compounds was used for in silico screening. ZINC15 comprises approximately 230 million commercial compounds which are ready-to-dock, 3D formats. Approximately 6,00,000 related compounds were screened in this investigation by using similarity search algorithms. These compounds were prepared for further screening against the generated pharmacophore. It was observed that about 42 molecules were significantly mapped against the template pharmacophore with high fit scores. These molecules inherit the molecular features which are essential for inhibiting the luxS protein from producing AI-2. The top three structures obtained after screening were selected for docking against the target protein [Figure 4].
Figure 4: Alignment of top three hit molecules obtained after the virtual screening with the common pharmacophore features

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Molecular docking of luxS inhibitor

The molecule with the id ZINC703741 was found to pose significantly a very high libdock score of 94.69. The binding energy was −33.67 kcal/mol. The structure of the lead molecule is presented in [Figure 5]. Molecular docking of the lead compound indicated high interactions with the receptor protein [Figure 6]A. A high docking score of the top ligands increased the confidence that the selected compound has soaring potential to inhibit the target protein of interest. Strong hydrogen bond interactions were also observed in ARG16 and GLU145 residues. Pi–Pi stacking was seen in TYR142 and PRO158 [Figure 6]B.
Figure 5: 3D structure of the lead molecule

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Figure 6: (A) Docked pose of the potential inhibitor molecule with the target protein and (B) Molecular interaction diagram of the ligand with the binding site residues

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  Discussion Top


The currently existing models to explain the involvement of AI-2/AHLs during dental plaque formation/inhibition are not fully elucidated. Although a few strains are successfully isolated from human dental plaque and tongue surfaces and depicted their roles in biofilm formation, the reason that AHLs were unable to be identified from pure oral pathogenic bacterial cultures is attributed to the poor identification of its mechanistic role. The current study is an attempt to unveil the contribution of AI-2 during the prevention of oral biofilm formation by screening the AI-2 inhibitor in F. nucleatum.

Using the template of luxS protein from B. subtilis, the structure of F. nucleatum has been illustrated in the present study through homology modeling. Previous studies have shown that luxS produces the signaling molecule (AI-2), which is represented as the only available mode of QS led by the bacterial strains.[10 The intracellular communication is a complex event during biofilm organization and protection, while on the other hand, a few QS mechanisms, such as luxS–AI-2 have been considered to interact with biofilm formation. Further, the availability of low-sensitive biosensors may also be attributed to the less number of AHL-producers reported in the oral cavity.[30] However, the influence of luxS and AI-2 during biofilm establishment always remains a dispute. It has been further hypothesized that since surface adherence/cell-to-cell adherence is essential for the activation of AHL synthesis in certain bacterial systems, some exclusive bacterial species may also specifically alter the gene expression during the formation of oral biofilms.[31] It is probably because of triggering of biofilm promoting conditions during cultivation toward the expression of QS-related genes which are not expressed due to either the axenic nature of cultures or culture under agitated conditions. Also, it has been found that the production of AHL increases during the mixed cultures of Porphyromonas gingivalis. Therefore, the current observation depicted high structural similarity between the two luxS proteins with RMS values as low as 0.6 Å. Further, the key mutations observed are highly responsible during the signaling of AI-2 on biofilm formation or inhibition.

Importantly, the key interactions required for the inhibition of the target protein, luxS was determined in the present study using the pharmacophore model with the compounds, such as 2-(4-amino-5H-pyrrolo [3,2-d] pyrimidin-7-yl)-5-(hydroxymethyl) pyrrolidine-3,4-diol, 3-butyl-5-(dibromomethylene)-2(5H)-furanone, (2S)-2-amino-4-[(2R,3S)-2,3-dihydroxy-3-N-hydroxycarbamoyl-propylmercapto] butyric acid, and N-(4-fluorophenyl) sulfonyl-N-methyl-4-propyl-benzenesulfonamide. Similarly, a study conducted on AI-2 regulated genes of Salmonella typhimurium found an unidentified operon encoding an ATP binding cassette-type transporter, namely, the lsr (luxS regulated) operon.[32] Mutations in the lsr operon point out the inability of S. typhimurium to discard AI-2 from the extracellular environment, indicating the role of lsr. The above study further concluded that AI-2 is originated from the ribosyl moiety of S-ribosylhomocysteine.

Screening of key residues involved in the inhibition of luxS is an important study, owing to the fundamental task carried out by QS during bacterial pathogenesis and resistance marked by virulence expression and biofilm establishment, respectively. Hence, QS receptors have been considered as prospective focal points toward anti-infective therapy. Because AI-2 is the signaling molecule in QS, it is imperative to note that antagonists of AIs could possibly reduce the production of toxin and biofilm formation in many bacterial species. Importantly, it is noteworthy to consider many other regulatory pathways possible in this regard in addition to QS.[10]

In the current study, the selected five compounds using pharmacophore study indicate the hydrogen bond receptors and ionizable groups. In continuation with the above findings, virtual screening using ZINC 15 with commercially available compounds highlights about 42 molecules that possess the ability to inherit the molecular features indispensable for preventing the luxS protein from producing AI-2. Corroborating to the current observation, one of the earlier studies reported that AI-2 molecules are found to show structural resemblances in many bacterial species as compared to the variable molecular configuration of acyl-HSL and peptide autoinducers.[32]

Molecular docking of the lead compound indicated high interactions with the receptor protein. A high docking score of the top ligands augmented the confidence that the selected compound has elevated potential to reduce the target protein of interest. In the current study, strong hydrogen bond interactions were observed in ARG16 and GLU145 residues, as well as Pi–Pi stacking, which was noted in TYR142 and PRO158 positions. In line with the present investigation, a new class of autoinducers has been reported from the strains of Pseudomonas by its ability to activate AHL biosensors, and correspondingly, new signal molecules have been identified using the structural analysis as diketopiperazines {cyclo (L-Ala–L-Val) and cyclo (L-Pro–L-Tyr).[33] Meanwhile, L-canavanine was also identified as one of the autoinducers, which was found to act as an allelopathic compound by suppressing bacterial growth.[34] Further, it was also observed to prevent biofilm formation by Bacillus cereus.[35] Interestingly, (5Z)-4-bromo-5-bromomethylene-3-butyl-2 (5H)-furanone, inherent synthesis of D. pulchra, was found to minimize AI-2-dependent QS in E. coli. It has been further documented that the furanone decreases the motility and therefore significantly inhibits the biofilm formation in E. coli.[36]

Similarly, the adherence of Streptococcus gordonii with salivary pellicle present over the surface of tooth was observed to trigger augmented expression of AgI/II family proteins,[37] which are adhesive to salivary proteins[38] and the above transcription regulation is arbitrated by a two-component system involving BrfAB. Hence, the direct salivary contact was found to enhance the adherence of S. gordonii with tooth surfaces and the enhancement of many late colonizing species, including Actinomyces, facilitating the spatio-temporal organization of multispecies communities. Importantly, another bacterial species, P. gingivalis was found to display high adhesive property with many substrata by means of upregulated expression upon direct contact with T. denticola.[39]

A peptide analog related to competence-stimulation has also been documented to hold the potency to inhibit the competence display in addition to minimize the expression of pneumococcal virulence factors, like autolysin and choline-binding protein D.[40] LuxU, LuxO (an F54 dependent response regulator), and a number of small regulatory RNAs in alignment with Hfq chaperone alter the functioning of LuxR, a master regulator of the QS regulon. A lot of substantial pieces of evidence have portrayed in detail the influence of AHL and monopeptide analogs to achieve the reduction of QS circuits in few bacterial species.[41] The common occurrence of luxS in Gram-positive and Gram-negative bacteria indicates the importance of AI-2 as a widespread QS system that intercedes interspecies communication.

The key physiological mechanisms like the uptake of iron/hemin, organization of structured biofilms, and stress response have also been attributed to AI-2 signaling in periodontal pathogens. Further, it is also well documented that the AHL-dependent QS system is a major autoinducer in dental biofilm formation.[41] All the above findings authenticate the structural configuration of luxS protein, the mechanistic pathway of AI-2, and its vital task in the prevention of biofilm development. Overall, the AI-2 QS system acts as a potential target for the developmental progress of new therapies to direct the periodontal pathogenic population and biofilm development/inhibition.

Therefore, the application of small molecule inhibitors in preventing plaque formation by oral pathogens can further be studied. Small molecules can be a promising way for controlling biofilm formation because of their stability, activity at low concentration, and low toxicity.[42] According to various reports, the coating of screened small molecules on metal caps such as titanium (Ti), silver, chromium, etc. could further restrict the growth of oral pathogens.[43] Rapid coating of luxS inhibitors on Ti metal caps may further accelerate the process of preventing aggregation of oral pathogens. This process can significantly control the rate of dental decay further. Also, the coating of antimicrobial peptides on metal caps would also efficiently block the colonization of microbes on the metal surface preventing the formation of oral biofilm as already suggested.[44],[45]


  Conclusions Top


LuxS protein plays a major role in bacterial communication and hence was chosen as the target of interest. Our study clearly indicates that the high throughput virtual screening resulted in identifying an inhibitor for luxS in Fusobacterium for the first time. Further, the validation of screened inhibitors and their analogs responsible for potential luxS inhibitory activity is highly recommended through in silico structure-activity studies and in vitro assays to authenticate its biological activity.

Acknowledgements

The funding support extended by the Commerce and Consumers Integrals of India, East Tambaram, Chennai 600059, India, is gratefully acknowledged (Grant Ref. No. AU/D-315/279). The authors are indeed thankful to Saveetha Dental College (SDC) for providing the infrastructure facilities needed for this study. The kind cooperation extended by the Faculties and Students of the Department of Orthodontics, SDC, during the course of the work is also acknowledged. The authors declared no potential conflicts of interest with regard to publication, authorship, and research of this article.

Financial support and sponsorship

Nil

Conflicts of interest

None

Author contributions

K.K.S., R.R., and R.V. contributed to study conception, data collection, data acquisition and analysis, data interpretation and article writing and article revision. R.R. and R.V. contributed to the study conception and article corrections and article revision. All the authors approved the article for final submission.

Ethical policy and institutional review board statement

Not applicable.

Patient declaration of consent

Not applicable.

Data availability statement

All the data pertaining to this study is obtained in the article itself.

 
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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]



 

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