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Table of Contents
ORIGINAL ARTICLE
Year : 2023  |  Volume : 9  |  Issue : 1  |  Page : 71-80

Inhibitory interaction and pharmacological analyses of berries phenolics against Listeria monocytogenes virulent protein internalin B


1 School of Agriculture, Indira Gandhi National Open University, New Delhi, India
2 Department of Bioengineering, Integral University, Lucknow, Uttar Pradesh, India
3 Department of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh, India

Date of Submission04-Nov-2021
Date of Acceptance04-Jan-2022
Date of Web Publication21-Dec-2022

Correspondence Address:
Dr. Archana Vimal
Department of Bioengineering, Integral University Lucknow-266026, Uttar Pradesh
India
Dr. Awanish Kumar
Department of Biotechnology, National Institute of Technology, Raipur-492010, Chhattisgarh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2311-8571.364413

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  Abstract 


Background: Traditional plants, their parts, and phytochemicals obtained from them are beneficial for human beings. They are used as potent antimicrobials, but very little research is conducted on the use of traditional medicine against food-borne infection. Different berry plants are rich in phenolic compounds and conventionally known to have many properties such as antioxidants, anti-carcinogenic, anti-inflammatory, anti-bacterial, and anti-diabetics. However, only limited polyphenols are known for their antilisterial effect. The present study aimed to explore the antimicrobial efficacy of phenolic compounds of berries for the treatment of food-borne infection caused by the bacteria Listeria monocytogenes. Materials and Methods: Molecular docking studies employing the SwissDOCK server were performed to evaluate the antimicrobial activity of phenolic compounds obtained from different varieties of berries. Internalin B (InlB), a virulence protein of L. monocytogenes was selected as a target. The absorption, distribution, metabolism, excretion, and toxicity profiling of each test ligand was done through the SwissADME tool. Results: Among all the test ligands, p-coumaric acid, epicatechins, chlorogenic acid, and quercetin showed better binding efficiency with the target protein InlB. The binding energy obtained for quercetin, p-coumaric acid, chlorogenic acid, and epicatechins was-8.93,-8.23,-8.18,-7.58, kcal/mol, respectively. Quercetin and p-coumaric acid were forming 4 H-bonds, whereas chlorogenic acid and epicatechins were forming 3-H bonds inside the binding pocket. Conclusion: In a nutshell, analyses indicated that identified ligands have the potential to block the virulent protein InlB of L. monocytogenes and help combat Listeria infection. These phenolic compounds could be a substitute for synthetic antimicrobials and can be used in food preservation and combat food-borne diseases. However, future in-depth in vitro and in vivo analysis is needed to get more information on these four phenolic ligands of berries.

Keywords: Berry plant, internalin B, Listeria monocytogenes, pharmacological analyses, phenolics, potent inhibitor, traditional medicine


How to cite this article:
Kumar A, Vimal A, Kumar A. Inhibitory interaction and pharmacological analyses of berries phenolics against Listeria monocytogenes virulent protein internalin B. World J Tradit Chin Med 2023;9:71-80

How to cite this URL:
Kumar A, Vimal A, Kumar A. Inhibitory interaction and pharmacological analyses of berries phenolics against Listeria monocytogenes virulent protein internalin B. World J Tradit Chin Med [serial online] 2023 [cited 2023 Feb 3];9:71-80. Available from: https://www.wjtcm.net/text.asp?2023/9/1/71/364413




  Introduction Top


Education and urbanization encourage people to know how their food and dietary interventions can protect them from food-borne illness, metabolic syndrome, digestive disorders, and urinary tract infections. The increasing market for natural remedies like organic food or antioxidant-rich food requires complete information about their safety and efficiency. Many natural products from grapes, bananas, and berries are being studied for their antimicrobials and prebiotic properties because of their potential for selective inhibition of pathogens and in the meantime, promoting beneficial microorganisms in the gut.[1],[2],[3] Berries also contain phytochemicals that are reported to have inhibitory effects against pathogens. It causes structural damage, changes in metabolism, gene expression, and cell membrane synthesis through the unknown mechanism of interactions, and synergistic effects against pathogenic bacteria. Berries also exhibited various antimicrobial activities like preventing adhesion of microbes to the urinary tract, reduced biofilm formation in humans, and modulation in colonic gut microbiota, gene expression, metabolism, and cell membrane synthesis.[4],[5],[6],[7]

The inclusion of berries in daily diet has shown prebiotic capabilities that influence gut microbial population and improvise gastrointestinal tract (GIT) condition. Functional foods promote gut microbiota which becomes important in preventive medicine. Almost every variety of berries is rich in nutrients, fiber, and polyphenols that directly or indirectly influence the microbial ecosystems. The microbial interaction of berries phytoconstituents seeks scientific attention. This is because the in situ enzymatic transformations that occur in the presence of phenolics compound can have an influential effect on human physiology.[8],[9] Plants produce phytoalexins (low-molecular weight compounds produced in response to biotic and abiotic stress) as a protection mechanism against insects and parasites. Food industries are trying to harness these qualities to produce higher-quality consumer products. Industries and people usually face huge economic losses and health hazards due to pathogenic microorganisms. To reduce this, it is needed to study which particular compounds from the wide variety of berries have high activity against microbes, and which pathogens are susceptible to it.[10],[11],[12] Berries are rich in polyphenols that have an extensive antioxidant property that inhibits pathogens and, therefore, are used for food preservation. However, only selective compounds are effective against L. monocytogenes. This is because different phenolic compound has diverse structure and are required in different amount, and interact differently against each microbe. The OH radicals generated from phenolic compounds disrupt the bacterial cell membrane, that in turn causes depolarization of bacteria, loss of cellular content, and reduction of ATP levels, leading to cell death.[13],[14],[15]

Food science creates a platform where engineering, biological and physical science comes together to study food and improve its quality by understanding the nature of food, causes of food degradation/spoilage, food processing, etc. The implementation of modern science has equipped us to deal with problematic situations such as food shortage, nutritional quality, and food deterioration. Bioinformatics plays an important role in many of these processes. Nowadays, bioinformatics has various approaches in the different biological fields along with food science. It helps in managing biological data so that it can be used easily in biotechnology. This field is gaining success day by day and become an easier and essential tool for research. It is an integrative field and established as an imperative scientific discipline. It creates a standard shift in disciplines, including drug discovery, molecular medicine, molecular evolution, comparative genomics, and applications in microbial genomics and biotechnology. Bioinformatics has a significant contribution to food science, but this field is less explored and appreciated. Many approaches can be applied in food technology and nutritional science to explore and speed up the discovery of drugs. Bioinformatics assists in predicting and estimating the wanted and unwanted effects of microbes on food, genomics and proteomics level study to enhance the food production, enhancing the food quality and nutritional value, food processing, preservation, and several other studies.[4],[16],[17] Keeping the above points into consideration, the present work is designed to identify the antimicrobial efficacy of phenolic compounds present in different berries against one of the major food pathogens L. monocytogenes through in silico studies. Furthermore, the pharmacokinetic behavior of these phenolic compounds was evaluated through in silico absorption, distribution, metabolism, excretion, and toxicity studies.


  Materials and Methods Top


Selection of target protein

Listeria monocytogenes are among the most virulent food-borne pathogens that cause the infection called listeriosis. The “internalin” protein that is mainly involved in pathogenesis is selected as the target protein in the present study.[17],[18]

Retrieval of the tertiary structure of the target protein from Protein Data Bank

The internalin B (InlB) from L. monocytogenes containing SH3-like domains having Protein Data Bank (PDB) ID 1M9S, resolution 2.65 Å, and total structure weight of 69.83 kDa was selected as the target protein.[18],[19] The tertiary structure of the selected target protein was obtained from the PDB (https://www.rcsb.org/).

Structure validation of target protein

The tertiary structure of the target protein is optimized and validated. The validation task was performed by Ramachandran through an online tool ProCheck Server (https://servicesn.mbi.ucla.edu/PROCHECK/).[20],[21]

Prediction of drug-binding site/active binding site

The drug-binding pocket or site was predicted using the online server servers 3DLigandSite and MetaPocket (http://www.sbg.bio.ic.ac.uk/3dligandsite/, https://projects.biotec.tu-dresden.de/metapocket/).[22],[23]

Ligand selection

The literature suggests that the phenolic compounds (phytochemicals) present in different berries have antimicrobial activity. Based on scientific reports available, 14 phenolic compounds present in different berries were selected to evaluate their antimicrobial activity against the L. monocytogenes. These phenolic compounds were not explored earlier as inhibitors of L. monocytogenes.

Ligand preparation and drug-likeness prediction

PubChem database was used to find the structure of selected phytochemicals (https://pubchem.ncbi.nlm.nih.gov/). Then explicit hydrogens were added to the structures from the add hydrogen option. The structures were cleaned, and the structures were saved in SMILES (Simplified Molecular-Input Line-Entry System) and PDB formats.[24]

Molecular docking

Each selected ligand was individually docked against the target protein using the online server provided by SwissDOCK (http://www.swissdock.ch/).[25] Docking analysis using the SwissDock server was carried out, by submitting the target protein in PDB format and the ligands in mol2 format. SwissDock allows the user to edit advanced parameters and gives the grid space inputs, which include the center x, y, z, and size x, y, z values. The results are generated as zip files which can be extracted to view the different docking poses of the ligand with the protein, and the server also has an inbuilt JSMOL viewer to view the binding pose of the ligands.[26]

Visualization of docking results

UCSF Chimera was used to visualizing the molecular docking results. This tool is developed by the UCSF Resource for Biocomputing, Visualization, and Informatics and supported in part by the National Institutes of Health (http://www. rbvi. ucsf. edu/chimera).[26]

Determination of protein-ligand interaction

The protein-ligand interaction was also studied using the USCF Chimera (http://www.rbvi.ucsf. edu/chimera).[26]

ADME profiling

The ADME studies of all the phenolic compounds selected as test ligands were performed using the platform provided by SwissADME. It is a free web tool that is used to study the drug-likeness and pharmacokinetics of small molecules (http://www.swissadme.ch/).[27],[28] The server accepts input in SMILES format and also by drawing through its embedded structure drawing plugin on the site. The ligands were submitted on SwissADME servers (in SMILES format). After submission, the results are returned as the predicted LD50 value in mg/kg weight. The prediction accuracy in percentage, and the similarity of the input compound with other similar toxic compounds from the database with identified rodent oral toxicity values.


  Results and Discussion Top


Target protein selection

L. monocytogenes is responsible for causing food-borne infection listeriosis. It secretes a protein called internalin that helps the pathogen to attach to the intestinal cell membrane of the host. Once it is attached to the intestinal membrane, it may translocate to the gastrointestinal epithelium. It can also invade the host's monocytes, macrophages, or polymorphonuclear leukocytes and cause septicemia. The pathogenicity of this microbe can be checked by preventing its attachment to the host system. This could be achieved by blocking the internalin protein. Therefore, this protein is taken under consideration for the present study.[17],[18]

Retrieval of the tertiary structure of the target protein from Protein Data Bank

The InlB from L. monocytogenes containing SH3-like domains involved in the virulence mechanism of the pathogen is retrieved from PDB. It has PDB ID 1M9S, resolution 2.65 Å, and a total structure weight of 69.83 kDa.[17],[18],[19] The structure of the target protein is shown in [Figure 1].
Figure 1: Target protein internalin B isolated from Listeria monocytogenes

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Structure validation of target protein

The tertiary structure of the target protein InlB was retrieved from PDB. Then, the energy minimization of the target protein was done before subjecting it to molecular docking studies. The minimum energy conformation of the target protein was validated through the Ramachandran plot. The minimum energy conformation 3-D structure of InlB was submitted to the Procheck server.[20],[21] The Ramachandran plot maps the psi versus phi backbone angles for each amino acid residue in a protein structure. This plot thus gives essential information about the conformation and folding of a protein structure. The modeled protein follows the expected range of the Ramachandran plot, as shown in [Figure 2]. Thus, it can be deemed as a stable protein structure. The resulting output is the number of residues in the allowed regions, favored regions, and outliers, as summarized in [Table 1].
Figure 2: Ramachadran plot to validate the 3-D structure of target protein Internalin B isolated from Listeria monocytogenes

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Table 1: Ramachandran Plot statistics for 1M9S (Internalin B) using Procheck server

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Prediction of drug-binding site/active binding site

The drug-binding site or active site in the target protein InlB of L. monocytogenes was also identified before proceeding to the docking steps [Figure 3]. The structure was submitted on server 3D LigandSite and MetaPocket,[29],[30] and the predicted sites by these servers are summarized in [Table 2]. These two servers have different algorithms, and their combined results give us information regarding increased probable binding pockets located in the 3-D structure of the target protein.
Figure 3: Protein (Int B)-ligand (p-Coumairc Acid) interaction (a) hydrophobicity interaction, (b) Ribbon interaction, (c) ribbon interaction

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Table 2: Active site results predicted by 3DLigandSite and MetaPocket site servers for target protein Internalin B of Listeria monocytogenes

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Ligand selection

Berries are a nutritionally rich food resource and also possess significant antioxidant properties. They are also reported to have anti-microbial activity against a vast range of microbes. This is because they are rich in phenolic compounds. Some of such phytochemicals present in different berries were selected as ligands in the undertaken study.[5],[6],[15] The chemical structure and source of these phytochemicals are presented in [Table 3]. These ligands were examined for their potency to block the virulent protein InlB from L. monocytogenes [Figure 4], [Figure 5], [Figure 6].
Table 3: List of ligands with structure and presence in berries

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Figure 4: Protein (Int B)-ligand (Epicatechins) interaction (a) hydrophobicity interaction, (b) Ribbon interaction, (c) ribbon interaction

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Figure 5: Protein (Int B)-ligand (Chlorogenic Acid) interaction (a) hydrophobicity interaction, (b) Ribbon interaction (c) ribbon interaction

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Figure 6: Protein (Int B)-ligand (Quercetin) interaction (a) hydrophobicity interaction, (b) Ribbon interaction, (c) ribbon interaction

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Molecular docking, visualization of docking results, and determination of protein-ligand interaction

The InlB of L. monocytogenes was docked with the 14 polyphenolic ligands obtained from different berries after the in silico toxicity tests using the SwissADME parameters.[27],[28] The output of the molecular docking that was carried out using SwissDock is the full fitness (kcal/mol) and estimated ΔG (kcal/mol) with which the ligand binds to the pocket of the target protein. The docking results of the ligands are summarized in [Table 4]. SwissDock results observed in Chimera[26] for InlB with all the ligands their full fitness and estimated ΔG (kcal/mol) values and the number of hydrogen interactions are also shown in [Table 4].
Table 4: Docking summary of Internalin B of Listeria monocytogenes with the phenolic compounds present in different berries

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ADME profiling

The phytochemicals from different berries were selected after the literature review and we get about 14 potential phytochemicals; then, their SMILES format was obtained from PubChem, which was submitted to the SwissADME server to check if they have potential properties to be a drug-like compound [Table 5]. After submitting fourteen ligands, the results are evaluated on various parameters.[24],[26],[27],[28]
Table 5: Properties of ligands following Lipinski's rule

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The ligands were checked for Lipinski's rule of five properties, Topological Polar Surface Area (TPSA), water solubility [Table 6], and gastrointestinal absorption [Table 7]. The Lipinski's filter of five states that for a molecule to be considered drug-like and orally bioavailable, it should pass four different physicochemical parameters (molecular weight ≤500, Hbond donors ≤5, Hbond acceptors ≤10, log P ≤ 5); only 2 out of 14 violates the rules.
Table 6: Water solubility prediction of test ligands

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Table 7: Gastrointestinal absorption and P-glycoprotein prediction of test ligands

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The SwissADME share important detail and general physicochemical factors, ADME, and medicinal chemistry property of a test compound. Two parameters (partition coefficient and solubility) play an important role in terms of physicochemical factors. According to the predicted LogP value, screened compounds lie within the range of −0.38–3.31. This parameter can illustrate the probability of a compound as a drug, but the LogP value does not always correspond to certain ADME aspects. In the present study, all 14 compounds have all these qualities to be considered potential drug-like molecules.

SwissADME LogP value was calculated by using five different algorithms; therefore, it is predicted that the value obtained represents the real condition. On the other hand, solubility is predicted by three different methods with the output of LogS (molar solubility in water) value. In general, the studied compounds are predicted to have optimum water solubility. It is observed even if there was a slightly different result among the method. The most common difference was observed in SILICOS-IT (Estimating Aqueous Solubility [http://silicos-it.be.s3-website-eu-west-1.amazonaws.com/software/filter-it/1.0.2/filter-it.html]) method is based on the fragment-based approach in LogS calculation. The other methods used are based on complete molecular topology.[31]

TPSA is a very important property for drug-like molecules in determining their intestinal absorption, bioavailability, drug absorption, and blood–brain barrier (BBB) penetration. TSPA should always be less than140 Å and out of 14 test compounds, 2 are having TSPA of more than 140 Å. In silico ADME prediction showed that the test compounds possess several favorable ADME properties. Based on the WlogP to TPSA ratio, all the test compounds were predicted to have absorption good absorption GIT and 13 of them could penetrate the BBB.

Among all the test compounds, only Epicatechin acts as a P-gp substrate. P-glycoprotein [Table 7] is a macromolecule that is overexpressed in multi-drug resistant cancer; it also helps in xenobiotics transportation out from the cell. Therefore, the study shows that the scaffold of 1-benzyl-3-benzoylurea has potential against cancer. In addition, SwissADME also helps in predicting the CYP450-mediated (Cytochromes P450) biotransformation [Table 8]. The result reveals that out of 14, 6 compounds do not interact with either isoform, while 2 compounds interact with at least one of the five isoforms. On the other hand, Pterostilbene could show interaction with four isoforms of the CYP450. This study also reveals that 1A2 and 3A4 are two significant isoforms that could become the target of phenolic compounds isolated from berry plants, while only one interaction is predicted to happen with C19.[32]
Table 8: Cytochromes P450 prediction of test ligands

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  Conclusion Top


Protein modeling and docking analysis using SwissDock of InlB, a protein target against the fatal food-borne disease, was performed using selected phytochemicals from berries. InlB was selected as the bacterial target after studying the importance of the protein and its importance in the entry into the host. After obtaining protein structure from PDB this protein, fourteen polyphenols were screened for various properties, including the physicochemical properties, pharmacokinetic properties (GI absorption), water-solubility, Log P values, TPSA, etc., after which only four test ligands p-coumaric acid, epicatechins, chlorogenic acid, and quercetin passed all these filters they were used for the docking analysis against the modeled protein. These four polyphenols gave better binding affinity toward the target protein InlB of food-borne pathogen L. monocytogenes and proved as a natural inhibitor of this pathogenic microbe. However, these phenolic ligands from berries can further be evaluated for their role as food preservatives against foodborne pathogen L. monocytogenes through in vitro, in vivo, and clinical trial studies. This is because their pharmaceutical behavior is dependent on their chemical properties, food matrix and storage condition, elaboration process, and how they interact with other materials. In addition, a detailed molecular study has required the revelation of the action mechanism of these polyphenols against the pathogen. Furthermore, it can be combined with other advanced techniques to explore their usage in food preservation and storage.[2],[3]

Authors' contributions

AbK: Experiment, Writing manuscript; AV: Design, Analysis, Writing manuscript; AwK: Design, Analysis, Writing the manuscript.

Acknowledgments

Authors are grateful to the National Institute of Technology, Raipur (CG) and Integral University, Lucknow (UP), and Indira Gandhi National Open University, New Delhi, for providing the facility and space for this work.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

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

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

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