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Research Article
Open Access Peer-reviewed

Modeling and in Silico Analysis for Prediction of Epitopes Vaccine against Norwalk virus from Capsid Protein (VP1) through Reverse Vaccinology

Elsideeq E. M. Eltilib, Yassir A. Almofti , Khoubieb Ali Abd-elrahman, Mashair A. A. Nouri
American Journal of Infectious Diseases and Microbiology. 2020, 8(1), 29-44. DOI: 10.12691/ajidm-8-1-5
Received February 11, 2020; Revised March 14, 2020; Accepted March 24, 2020

Abstract

Noroviruses are the leading cause of acute gastroenteritis and is responsible for approximately 685 million cases and 200,000 deaths annually worldwide. Currently, there is no vaccine to prevent human norovirus infection, and there is no specific therapy available to treat it. This study aimed to predict epitopes from the capsid VP1 protein that elicited the immune system and acted as safer efficacious vaccine. A total of 21 noroviurse strains were retrieved from the NCBI database. The IEDB analysis resources were used for epitopes prediction against B and T cells. The population coverage was calculated for the proposed epitopes against the whole world. Eight epitopes (48QVNP51, 159EVPLE163, 224VEQK227, 245RAPLP249, 376ISPPS380, 409VYPP412, 473FKAY476 and 492PQQLP496) successfully passed all B cell prediction tools and were shown to be antigenic, nonallergic and nontoxic. Thus were proposed as B cells epitopes. For cytotoxic T cells, a total of 103 epitopes were found to interact with MHC-I alleles. However, only 22 epitopes were shown to be antigenic, nonallergic and nontoxic. Among them four epitopes namely (140-AQATLFPHV-148; 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418) interacted with high number of MHC-I alleles and demonstrated favourable population coverage and thus were proposed as cytotoxic T lymphocytes MHC-1 epitopes. Moreover helper T cells, a total of 421 core epitopes were found to interact with MHC-П alleles. However, only 105 epitopes were shown to be antigenic, nonallergic and nontoxic. Eight epitopes namely (216-FLFLVPPTV-224; 499-GVFVFVSWV-507; 433-LPCLLPQEY-441; 90-NPFLLHLSQ-98; 394-NYGSSITEA-402; 247-PLPISSMGI-255; 220-VPPTVEQKT-228; 410-YPPGFGEVL-418) were interacted with most frequent MHC class II alleles, demonstrated higher population coverage and three of them (216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418) were shown to interact with both MHC-I and MHC-II alleles. Therefore they were proposed as T helper cells epitopes. The population coverage was 60.35% and 99.96% for MHC-I and MHC-II epitopes, respectively, and 100% for all T cells epitopes. Taken together 17 epitopes successfully proposed as vaccine candidate against noroviruse. In vivo and in vitro clinical trials studies are required to elucidate the effectiveness of these epitopes as vaccine.

1. Introduction

Noroviruses are the leading cause of acute gastroenteritis and is responsible for approximately 685 million cases and 200,000 deaths annually worldwide 1, 2. These viruses cause gastrointestinal disease, resulting in recurrent vomiting and diarrhea 1, 3, 4. The infection mostly characterized by high excreted viral loads 5, severe infectivity 6 and short-term immunity 7.

Norwalk viruses are the main cause of outbreak and irregular of nonbacterial gastroenteritis 8, 9 and connected to almost one over five of all reported cases are acute gastroenteritis internationally 9, 10. Contamination causes outbreaks of water - borne and food - borne illness in the society and generates signs of vomiting and diarrhea 11, 12, 13, 14. Diarrheal diseases are associated with high mortality rates 15, 16, 17, 18, 19 and noroviruses are an important cause of epidemic gastroenteritis together in children and adults worldwide 10, 20, 21, 22, 23, 24.

Noroviruses are an assemblage of single, positive-stranded RNA viruses classified into the Norovirus genus in the family Caliciviridae 11, 25, 26, 27. This family composed of five types; Norovirus, Sapovirus, Lagovirus, Vesivirus and Nebo virus. The first two genera are human while the others are animal genera 11, 12, 17, 18, 27. Genetically the human noroviruses are dissimilar 19 and are divided into six genogroups based on the amino acid sequence of the major structural proteins VP1 and VP2 10, 11, 12, 18.

The norovirus genome has three open reading frames (ORFs) of which ORF2 and ORF3 encode the major capsid protein (VP1) that determines the antigenicity of the virus, as well as the minor capsid protein (VP2). ORF1 encodes a large polyprotein that is cleaved by the viral protease in mature non-structural proteins, including the RNA-dependent RNA polymerase 28. To date, all norovirus vaccine candidates contain non-infectious recombinant VP1 proteins, either as virus-like particles (VLP), as P-particles, or as recombinant adenoviruses 29.

No vaccine is obtainable to put off norovirus illness or infection 8, 21, however there was attempts to make a vaccine from a novel strain of NOVs as plant - based oral vaccine, but unfortunately was invaluable 30. In this study we attempted to propose an epitopes from the capsid protein (VP1) of the virus that could elicited both B and T lymphocytes and act as safer vaccine.

2. Materials and Methods

2.1. Protein Sequence Retrieval and Alignment Tool

The protein sequences of 21 capsid proteins (VP1) were retrieved from the NCBI database (https: //www.ncbi.nlm.nih.gov/). The retrieved strains, accession numbers, country and date of collection were shown in (Table 1).


Determination of the conserved regions

The retrieved protein sequences were further aligned to obtain conserved regions using multiple sequence alignment (MSA) tools, Clustal W in the BioEdit program, version 7.0.9.0 31. Multiple sequence alignment (MSA) analysis was performed to analyze the conserved residue sequence amongst the screened B and T cell epitopes.

2.2. Evolution Analysis

The retrieved capsid protein sequences (VP1) were subjected to evolutionary divergence analysis and a phylogenetic tree was constructed to determine the common ancestor of each retrieved strain using MEGA7.0.26 (7170509) software 32.

2.3. Determination of B Cells Epitopes

The conserved regions of the candidate epitopes were analyzed by different prediction software tools obtained by Immune Epitope Database (IEDB) analysis (https: //www.iedb.org/). The reference sequence of VP1 was used as an input for the IEDB software resource analysis.

2.4. B Lymphocytes Epitopes Prediction

Tools from IEDB were used to identify the B cell epitopes (http: //tools.iedb.org/bcell/). This includes Bepipred linear epitope prediction analysis 33, Emini surface accessibility prediction 34 and Kolaskar and Tongaonkar antigenicity scale 35. These methods predicted specific epitopes in the capsid protein that were linear, at surface and immunogenic, respectively, and can bind to B cell receptors

2.5. T-lymphocytes Epitopes Prediction

The IEDB tools were used for the identification of the T cell epitopes prediction. The prediction method includes the major histocompatibility complex class I and П (MHC-I, MHC-П)

2.6. MHC-I Binding Predictions

Analysis of epitopes binding to MHC-I molecules was assessed by the software in IEDB MHC-I prediction tools (http: //tools.iedb.org/mhci/). The prediction method was obtained by Artificial Neural Network (ANN), Stabilized Matrix Method (SMM) or Scoring Matrices derived from combinatorial peptide libraries. Before the prediction step, epitopes lengths were set as 9mers. The conserved epitopes that bind to alleles at score equal to or less than 300 was considered as half-maximal inhibitory concentrations. Epitopes equal to or less than the IC50 were selected for further analysis

2.7. MHC-П Binding Predictions

Analysis of epitopes binding to MHC-II molecules was performed by the IEDB MHC-II prediction tools (http: //tools.iedb.org/mhcii/). The neural networks align (NN-align) that allow for simultaneous identification of the MHC-II binding core epitopes and binding affinity was used. All the predicted conserved epitopes that bind to many alleles at score equal to or less than 3000 half-maximal inhibitory concentration (IC50≤3000) was considered. Epitopes that equal to or less than the IC50 were selected for further analysis.

2.8. Antigenicity of the Predicted Epitopes

For determination of the antigenicity of the predicted epitopes, the sequence of the predicted epitopes for B and T lymphocytes were submitted to the VaxiJen v2.0 server (http: //www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html) for antigenicity prediction. The threshold of VaxiJen v2.0 server was set to the default threshold (0.4). Epitopes with antigenicity were further investigated for allergenicity and toxicity.

2.9. Allergenicity and Toxicity of the Predicted Epitopes

The following servers; AllergenFP 36, AllerTOP 37, Allermatch 38 and PA3P 39 were used to predict the allergenicity of the proposed epitopes for B and T lymphocytes. Epitopes found to be non-allergenic were further assessed for toxicity level by ToxinPred server 40.

2.10. Population Coverage Analysis of Predicted Epitopes

For the calculation of the population coverage for all potential MHC-I and II epitopes, the IEDB tools was used (http: //tools.iedb.org/population/). The capsid protein was assessed for population coverage against the whole world with selected MHC-I and MHC-II interacted alleles.

2.11. Homology Modeling

Raptor X for 3D structure prediction server (http: //raptorx.uchicago.edu/StructurePrediction/predict/) was used for creation the 3D structure of the reference protein. The reference sequence was used as an input and Chimera 1.8 41 was used as a tool to visualize the selected epitopes belonging to B cell and T cell (MHC-I and MHC-II). Homology modeling was used for visualization of the surface accessibility of the B lymphocytes predicted candidate epitopes as well as for visualization of all predicted T cell epitopes in the structural level.

3. Results

3.1. Phylogenetic Tree

According to the result of the conserved regions of the retrieved strains of the VP1 proteins using multiple sequence alignment analysis, the protein sequences demonstrated various strains with less mutated regions. This resulted in closed relationship of the retrieved sequences despite the possibilities of mutations in VP1 capsid protein. Generally Figure 1 provided the phylogenetic tree of the retrieved strains and the strains demonstrated molecular evolutionary divergence.

3.2. Alignment

The multiple sequence alignment was performed to obtain the regions of conservancy among Norwalk virus variants using multiple sequence alignment (MSA) tools, of Clustal W in the BioEdit program, version 7.0.9.0. As shown in Figure 2 the dots meant that amino acids at that position were conserved while the letters meant that the amino acids at that position were mutated. Generally the retrieved strains demonstrated less mutated regions during the alignment process. Thus multiple epitopes were predicted to be conserved among the retrieved strains. It is noteworthy that only the conserved epitopes (100% conserved epitopes) were selected for further analysis. Thus the proposed epitopes elected when they showed 100% conservancy among the retrieved strains

  • Table 3. The 15 epitopes of the B-cell that overlapped the Bepipred linear epitope prediction, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity prediction tools and further subjected to antigenicity, allergenicity and toxicity. The position of epitopes is according to the position of amino acids in the capsid protein (VP1)

3.3. Prediction of B Cell Epitope

The capsid protein (VP1) sequence was subjected to Bepipred linear epitope, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity methods in IEDB. Figure 3 demonstrated the thresholds of the methods used to predict the B cell epitopes. For instance the Bepipred linear epitopes prediction method showed a threshold binding score to B cell of 0.350 (minimum -0.005 and maximum 2.401). This method predicted thirty four linear epitopes eliciting the B cell from the conserved regions. In Emini surface accessibility the prediction threshold of the surface accessibility area of the epitopes was 1.000 (minimum of 0.054 and maximum of 7.701). Twenty five epitopes were potentially in the surface by passing the default threshold 1.000. For Kolaskar and Tongaonkar antigenicity the average of antigenicity was 1.038 (minimum of 0.871 and maximum of 1.190). Nineteen epitopes gave score above the default threshold 1.038. All these epitopes and their scores against the B cell were provided in Table 2. However, only fifteen epitopes successfully overlapped the three tools and were shown in Table 3. These fifteen epitopes were further investigated for their antigenicity, allergenicity and toxicity. Eight epitopes namely (48QVNP51, 159EVPLE163, 224VEQK227, 245RAPLP249, 376ISPPS380, 409VYPP412, 473FKAY476 and 492PQQLP496) were shown to be antigenic, nonallergic and nontoxic and thus were proposed as B cell epitopes. The positions of the proposed epitopes in the 3D structural level of VP1 capsid protein were shown in Figure 4.

  • Table 4. The 22 epitopes that interacted with MHC-1 from the capsid protein (VP1) of the Norwalk virus that demonstrated antigenicity, nonallergic and nontoxic. The population coverage for each predicted epitope was calculated and election of the proposed epitopes was based on the higher population coverage score. The position of epitopes is according to the position of amino acids in the capsid protein

  • Table 5. The best four proposed epitopes from the capsid protein (VP1) of the Norwalk virus that interacted with MHC class I alleles. The position of epitopes is according to the position of amino acids in the capsid protein

3.4. Prediction of Cytotoxic T-lymphocyte Epitopes and Interaction with MHC Class I

The reference sequence of the capsid protein was analyzed using IEDB MHC-1 binding prediction tools to predict T cell epitopes interacting with MHC Class I alleles. Based on Artificial Neural Network (ANN) with half-maximal inhibitory concentration (IC50) ≤300, 103 epitopes were predicted to interact with different MHC-1 alleles. All these epitopes were further investigated for their antigenicity, allergenicity and toxicity. Only 22 epitopes were shown to be antigenic, nonallergic and nontoxic. Furthermore these 22 epitopes were investigated for their population coverage against the whole world. The 22 epitopes and their population coverage were shown in Table 4. Four epitopes namely 140-AQATLFPHV-148; 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418 demonstrated favourable population coverage and thus were proposed as cytotoxic T lymphocytes MHC-1 epitopes. The proposed four epitopes with their corresponding MHC-1 alleles were shown in Table 5. The positions of the proposed epitopes in the 3D structural level of capsid protein were shown in Figure 5.

3.5. Prediction of T Helper Cell Epitopes and Their Interaction with MHC Class II

The reference sequence of VP1 capsid protein was analyzed using IEDB MHC-II binding prediction tools. Based on NN-align with half-maximal inhibitory concentration IC50)≤3000 there were 421 predicted epitopes found to interact with MHC-II alleles. When these epitopes subjected to antigenicity, allergenicity and toxicity investigations, only 105 epitopes were shown to be antigenic, non-allergic and nontoxic and the population coverage of each epitope alleles was calculated. The 105 epitopes were provided in Table 6.

  • Table 6. The 105 epitopes from the capsid protein (VP1) and their interaction with MHC class II. These epitopes demonstrated antigenicity, nonallergic and nontoxic. The population coverage for each predicted epitope was calculated and election of the proposed epitopes was based on the higher population coverage score.

Among the 105 epitopes, eight epitopes namely (216-FLFLVPPTV-224; 499-GVFVFVSWV-507; 433-LPCLLPQEY-441; 90-NPFLLHLSQ-98; 394-NYGSSITEA-402; 247-PLPISSMGI-255; 220-VPPTVEQKT-228; 410-YPPGFGEVL-418) were interacted with most frequent MHC class II alleles, demonstrated higher population coverage and three of them were shown to interact with both MHC class I and MHC class II alleles. Therefore they were proposed as T helper cells epitopes. The eight epitopes and their corresponding MHC-II alleles were shown in Table 7. The position of these predicted epitopes in the 3D structural level in the capsid protein was illustrated in Figure 5 and Figure 6.

  • Table 7. The best eight epitopes that were proposed as a vaccine candidate from the capsid protein (VP1) of the Norwalk virus and interacted with high affinity with MHC class II alleles. The position of epitopes is according to the position of amino acids in the capsid protein

  • Figure 6. T cell proposed epitopes that interact with MHC-1I alleles. Three epitopes ( 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418) were not shown in this figure since they were shown in figure (5) (interacted with MHC-1 and MHC-1I alleles). The other five epitopes (433-LPCLLPQEY-441; 90-NPFLLHLSQ-98; 394-NYGSSITEA-402; 247-PLPISSMGI-255 and 220-VPPTVEQKT-228) were only shown in this figure since they only interacted with MHC-1I alleles. The positions of these proposed epitopes was according to their position in the capsid protein
3.6. Analysis of the Population Coverage

The predicted epitopes from the capsid protein (VP1) that interacting with MHC class I and II alleles were subjected to population coverage analysis. The proposed vaccine epitopes were elected as peptide vaccine based on their high population coverage score, number of their interacted alleles and/or their interaction with both MHC class I and II alleles. As shown in (Table 4) 22 predicted epitopes interacted with MHC class I alleles with different population coverage scores. Among them four epitopes scored high population coverage % and highly interacted with most frequent MHC class I alleles. This strengthen their potentiality to act as promising vaccine candidate against MHC class I therefore were proposed as peptide vaccine. The epitope set of these four epitopes against MHC-1 alleles was 60.35% (Table 8).

In addition to that, as shown in Table 6 MHC class II, 105 predicted epitopes interacted with MHC class II alleles with different population coverage scores and were shown to be antigenic, nonallergic and nontoxic. Among them eight epitopes highly interacted with most frequent MHC class II alleles therefore they were proposed as peptide vaccine.

  • Table 8. The population coverage (PC) of MHC-I and MHC-II proposed epitopes. The population coverage of MHC-I was 80.53%, MHC-II was 99.99% and the combined alleles was 100% for all proposed epitopes )PC: Population Coverage)

The epitope set of these eight epitopes against MHC-II alleles was 99.96% (Table 8). Furthermore as shown in Table 8 all proposed epitopes were subjected to population coverage tools to assess population coverage of their MHC-I and MHC-II combined alleles. The population coverage of the proposed epitopes against the combined alleles was 100%.

4. Discussion

Norwalk viruses are considered as a leading etiology of epidemic acute gastroenteritis as well as an important cause of sporadic cases of acute gastroenteritis 42. Currently, there is no vaccine to prevent human norovirus infection, and there is no specific therapy available to treat it 20. The norovirus genome has three open reading frames (ORFs) of which ORF2 and ORF3 encode the major capsid protein (VP1) that determines the antigenicity of the virus, as well as the minor capsid protein (VP2). The majority of the studies performed to design vaccine for norovirus used VP1 as a vaccine construct. For instance vaccine using recombinant adenovirus expressing the norovirus major capsid protein VP1was developed. The vaccine measured the cross-reactive neutralizing antibody responses which are required for a successful norovirus vaccine 43. A study by Tucker et al (2008) 44 developed a currently human clinical trials vaccine that employs a recombinant adenovirus expressing the norovirus GI.1 major capsid protein (VP1) in an oral tablet formulation developed by Vaxart, Inc. Moreover recombinant adenovirus vaccine expressing the norovirus GII.4 major capsid protein VP1 45 and multiple VLP vaccine developed from VP1 protein 46 were developed by the Chinese center for disease control and prevention. Both studies demonstrated the antigenicity of VP1 as a vaccine candidate. Therefore this study aimed to propose multiple epitopes vaccine candidates from the capsid protein (VP1) to elicit B and T lymphocytes and act as a vaccine candidate using immune-informatics tools.

In the current study the B cell epitopes were predicted from the capsid protein VP1 to find the potential epitopes that would interact with B lymphocytes and initiate immune response. For the vaccine to be recognized by the B cell antibodies it must be linear and located on the surface of the antigen protein to be easily accessible. In addition to that the candidate vaccine should demonstrate greater antigenicity to elicit antibodies production. Therefore several tools from IEDB analysis resources were used to identify B cell epitopes such as Bepipred linear epitope prediction analysis 33, Emini surface accessibility prediction 34 and Kolaskar and Tongaonkar antigenicity scale 35. These tools provided multiple epitopes that were linear, on the protein surface and antigenic. However, for the epitopes to be proposed as a vaccine candidate it should be nonallergic and nontoxic to the host cells 47. Thus the predicted epitopes further subjected to Vaxigen antigenicity, allergenicity and toxicity investigations. Eight epitopes eight epitopes namely 48QVNP51, 159EVPLE163, 224VEQK227, 245RAPLP249, 376ISPPS380, 409VYPP412, 473FKAY476 and 492PQQLP496 passed these criteria and proposed as a B cell epitopes.

Since the immune response of T cell is long lasting response compared to B cell, where the antigen can easily escape the antibody memory response. This considered that CD8+T and CD4+T cells response play a major role in antiviral immunity 48. Cytotoxic CD8+T lymphocytes are considered as an important parameter in recognizing and killing infected cells or producing specific cytokines that prevent the infection in the body 49, 50. Thus, T cell epitope-based vaccination is a unique process of eliciting strong immune response against infectious agents such as viruses 51. In this study four epitopes were shown to interact with Cytotoxic CD8+T lymphocytes with high number of MHC-1 alleles and they demonstrated antigenicity and were shown to be nonallergenic and nontoxic. Beside that the four proposed epitopes showed favourable population coverage against the whole world population with epitopes set 60.35%. Therefore were proposed as Cytotoxic CD8+T lymphocytes epitopes.

For Helper CD4+T lymphocytes eight epitopes namely 90-NPFLLHLSQ-98; 216-FLFLVPPTV-224; 499-GVFVFVSWV-507; 433-LPCLLPQEY-441; 394-NYGSSITEA-402; 247-PLPISSMGI-255; 220-VPPTVEQKT-228; 410-YPPGFGEVL-418 were shown to interact with Helper CD4+T lymphocytes with high number of MHC-11 alleles and they were shown to be antigenic, nonallergenic and nontoxic. Among the eight epitopes three epitopes namely 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418 were shown to interact with both MHC-1 and MHC-11 alleles. This favoured them to be elected as a vaccine candidate. Also the eight epitopes demonstrated favourable interaction with the whole world population coverage with epitopes set 99.96%. Therefore were proposed as Helper CD4+T lymphocytes epitopes. The overall epitope set for the MHC-I and MHC-II combined alleles for the proposed epitopes showed excellent population coverage against whole world population (100%). Accordingly these epitopes were strongly recommended as promising epitopes vaccine candidates against T lymphocyte cells.

Recently a study by Azim et al (2019) 47 used multiple bioinformatics tools to predict epitopes from the VP1 and VP2 proteins of the noroviruse. However none of their predicted epitopes for B and T lymphocytes were corroborated to our proposed epitopes. This might be attributed to the differences in the software used in both studies to predict vaccine candidates.

5. Conclusion

The developing of an effective and safe vaccine is recommended to combat the infection and noroviruses. Vaccine design using reverse vaccinology prediction methods is highly appreciated as it provided specific epitopes in protein to act as a vaccine without using the virus particles as components of the vaccine. In this study eight epitopes were successfully proposed to interact against B cells. Moreover nine epitopes were successfully predicted to interact against T cell with population coverage epitope set of 100%. These epitopes provided excellent results as promising vaccine against noroviruses. However in vitro and in vivo trials are required to achieve the effectiveness of these epitopes as vaccine candidates.

Acknowledgments

Authors would like to thank the staff members of the Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Sudan for their cooperation and support.

Competing Interest

The authors declared that they have no competing interests.

Funding

No funding was received.

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[29]  Claire P. Mattison, Cristina V. Cardemil & Aron J. Hall: Progress on Norovirus vaccine research: Public health considerations and future directions, Expert Review of Vaccines.
In article      
 
[30]  Tacket CO, Mason HS, Losonsky G, Estes MK, Levine MM, Arntzen CJ. Human immune responses to a novel norwalk virus vaccine delivered in transgenic potatoes. The Journal of infectious diseases. 2000; 182(1): 302-5.
In article      View Article  PubMed
 
[31]  Hall, T.A. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. in Nucleic acids symposium series. 1999. [London]: Information Retrieval Ltd., c1979-c2000.
In article      
 
[32]  Kumar, S., G. Stecher, and K. Tamura, MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular biology and evolution, 2016. 33(7): p. 1870-1874.
In article      View Article  PubMed
 
[33]  Jespersen, M.C., Peters, B., Nielsen, M., Marcatili, P. BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017; 45, W24-W29.
In article      View Article  PubMed
 
[34]  Emini, E.A., Hughes, J.V., Perlow, D., Boger, J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J. Virol. 1985; 55, 836-839.
In article      View Article  PubMed
 
[35]  Kolaskar, A., Tongaonkar, P.C. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990; 276, 172-174.
In article      View Article
 
[36]  Dimitrov, I., Naneva, L., Doytchinova, I.A., Bangov, I. Allergen FP: allergenicity prediction by descriptor fingerprints. Bioinformatics. 2014; 30, 846-851.)
In article      View Article  PubMed
 
[37]  Dimitrov et al., 2013 Dimitrov, I., Bangov, I., Flower, D.R., Doytchinova, I.A. AllerTOP v.2- a server for in silico prediction of allergens. J Mol. Model. 2013; 20, 2278.
In article      View Article  PubMed
 
[38]  Fiers, M.W.E.J., Kleter, G.A., Nijland, H., Peijnenburg, A., Nap, J.P., Ham, R. Allermatch™, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines. BMC Bioinform. 2004; 5, 133.
In article      
 
[39]  Chrysostomou, C., Seker, H. Prediction of protein allergenicity based on signal-processing bioinformatics approach. In: 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2014.
In article      View Article  PubMed
 
[40]  Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R. Open source drug discovery consortium, Raghava GP in silico approach for predicting toxicity of pep-tides and proteins. PLoS One. 2013; 8 (9), e73957.
In article      View Article  PubMed
 
[41]  Peng, J. and J. Xu, A multiple‐template approach to protein threading. Proteins: Structure, Function, and Bioinformatics. 2011. 79(6): p. 1930-1939.
In article      View Article  PubMed
 
[42]  Glass RI, Parashar UD, Estes MK. Norovirus gastroenteritis. N Engl J Med. 2009; 361: 1776-85.
In article      View Article  PubMed
 
[43]  Ettayebi K, Crawford SE, Murakami K, et al. Replication of human noroviruses in stem cell-derived human enteroids. Science. 2016; 353(6306): 1387-1393
In article      View Article  PubMed
 
[44]  Tucker SN, Tingley DW, Scallan CD. Oral adenoviral-based vaccines: historical perspective and future opportunity. Exp Rev Vaccines. 2008; 7: 25-31.
In article      View Article  PubMed
 
[45]  Guo L, Wang J, Zhou H, et al. Intranasal administration of a recombinant adenovirus expressing the norovirus capsid protein stimulates specific humoral, mucosal, and cellular immune responses in mice. Vaccine. 2008; 26; 460-468.
In article      View Article  PubMed
 
[46]  Guo L, Zhou H, Wang M, et al. A recombinant adenovirus prime-virus-like particle boost regimen elicits effective and specific immunities against norovirus in mice. Vaccine. 2009; 27: 5233-5238.
In article      View Article  PubMed
 
[47]  Azim KF, Mahmudul H, Hossain Md N, Somana SR et al. Immunoinformatics approaches for designing a novel multi epitope peptide vaccine against human norovirus (Norwalk virus). Infection, Genetics and Evolution. 2019; 74 (103936)
In article      View Article  PubMed
 
[48]  Black M, Trent A, Tirrell M, Olive C. Advances in the design and delivery of peptide subunit vaccines with a focus on toll-like receptor agonists. Expert review of vaccines. 2010; 9(2): 157-73.
In article      View Article  PubMed
 
[49]  Hasan, M., Azim, K.F., Begum, A., Khan, N.A., Shammi, T.S., Imran, A.S., Chowdhury, I.M., Urme, S.R. Vaccinomics strategy for developing a unique multi-epitope monovalent vaccine against Marburg marburgvirus. Infect. Genet. Evol. 2019; 70, 140-157.
In article      View Article  PubMed
 
[50]  Garcia, K.C., Teyton, L., Wilson, I.A. Structural basis of T cell recognition. Annu. Rev. Immunol. 1999; 17, 369-397.
In article      View Article  PubMed
 
[51]  Shrestha, M.P., et al., Safety and efficacy of a recombinant hepatitis E vaccine. New England Journal of Medicine, 2007. 356(9): p. 895-903.
In article      View Article  PubMed
 

Published with license by Science and Education Publishing, Copyright © 2020 Elsideeq E. M. Eltilib, Yassir A. Almofti, Khoubieb Ali Abd-elrahman and Mashair A. A. Nouri

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Normal Style
Elsideeq E. M. Eltilib, Yassir A. Almofti, Khoubieb Ali Abd-elrahman, Mashair A. A. Nouri. Modeling and in Silico Analysis for Prediction of Epitopes Vaccine against Norwalk virus from Capsid Protein (VP1) through Reverse Vaccinology. American Journal of Infectious Diseases and Microbiology. Vol. 8, No. 1, 2020, pp 29-44. http://pubs.sciepub.com/ajidm/8/1/5
MLA Style
Eltilib, Elsideeq E. M., et al. "Modeling and in Silico Analysis for Prediction of Epitopes Vaccine against Norwalk virus from Capsid Protein (VP1) through Reverse Vaccinology." American Journal of Infectious Diseases and Microbiology 8.1 (2020): 29-44.
APA Style
Eltilib, E. E. M. , Almofti, Y. A. , Abd-elrahman, K. A. , & Nouri, M. A. A. (2020). Modeling and in Silico Analysis for Prediction of Epitopes Vaccine against Norwalk virus from Capsid Protein (VP1) through Reverse Vaccinology. American Journal of Infectious Diseases and Microbiology, 8(1), 29-44.
Chicago Style
Eltilib, Elsideeq E. M., Yassir A. Almofti, Khoubieb Ali Abd-elrahman, and Mashair A. A. Nouri. "Modeling and in Silico Analysis for Prediction of Epitopes Vaccine against Norwalk virus from Capsid Protein (VP1) through Reverse Vaccinology." American Journal of Infectious Diseases and Microbiology 8, no. 1 (2020): 29-44.
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  • Figure 1. Phylogenetic tree of the capsid protein (VP1) of the retrieved strains. The retrieved strains demonstrated divergence in their common ancestors
  • Figure 2. Multiple sequence alignment (MSA) of the retrieved strains of the capsid protein (VP1) using Bioedit software and ClustalW. Dots indicated the conservancy of the retrieved strains and letters within the rectangular indicated no conservancy (mutation) in amino acid
  • Figure 3. Prediction of B-cell epitopes by different IEDB scales (a- Bepipred linear epitope prediction, b- Emini surface accessibility, c- Kolaskar and Tongaonkar antigenicity prediction) for the capsid protein. Regions above threshold (red line) were proposed as a part of B cell epitope while regions below the threshold (red line) were not
  • Figure 4. Position of proposed eight conserved B cell epitopes in structural level of the capsid protein (VP1). The epitopes were shown in dark red ball and sticks shapes. These epitopes showed conservancy, high score in surface accessibility and antigenicity using IEDB software, nonallergic and nontoxic. The position of these epitopes was according to their position in the capsid protein
  • Figure 5. T cell proposed epitopes that interact with MHC-I alleles. Four epitopes (140-AQATLFPHV-148; 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418) were shown in this figure since they interacted with MHC-1 alleles. The positions of these proposed epitopes was according to their position in the capsid protein
  • Figure 6. T cell proposed epitopes that interact with MHC-1I alleles. Three epitopes ( 216-FLFLVPPTV-224; 499-GVFVFVSWV-507 and 410-YPPGFGEVL-418) were not shown in this figure since they were shown in figure (5) (interacted with MHC-1 and MHC-1I alleles). The other five epitopes (433-LPCLLPQEY-441; 90-NPFLLHLSQ-98; 394-NYGSSITEA-402; 247-PLPISSMGI-255 and 220-VPPTVEQKT-228) were only shown in this figure since they only interacted with MHC-1I alleles. The positions of these proposed epitopes was according to their position in the capsid protein
  • Table 1. Retrieved strains of capsid protein (VP1) with their date of collection, accession numbers and geographical regions
  • Table 2. B-cell epitopes prediction from the capsid protein, the position of peptides is according to the position of amino acids in the capsid protein
  • Table 3. The 15 epitopes of the B-cell that overlapped the Bepipred linear epitope prediction, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity prediction tools and further subjected to antigenicity, allergenicity and toxicity. The position of epitopes is according to the position of amino acids in the capsid protein (VP1)
  • Table 4. The 22 epitopes that interacted with MHC-1 from the capsid protein (VP1) of the Norwalk virus that demonstrated antigenicity, nonallergic and nontoxic. The population coverage for each predicted epitope was calculated and election of the proposed epitopes was based on the higher population coverage score. The position of epitopes is according to the position of amino acids in the capsid protein
  • Table 5. The best four proposed epitopes from the capsid protein (VP1) of the Norwalk virus that interacted with MHC class I alleles. The position of epitopes is according to the position of amino acids in the capsid protein
  • Table 6. The 105 epitopes from the capsid protein (VP1) and their interaction with MHC class II. These epitopes demonstrated antigenicity, nonallergic and nontoxic. The population coverage for each predicted epitope was calculated and election of the proposed epitopes was based on the higher population coverage score.
  • Table 7. The best eight epitopes that were proposed as a vaccine candidate from the capsid protein (VP1) of the Norwalk virus and interacted with high affinity with MHC class II alleles. The position of epitopes is according to the position of amino acids in the capsid protein
  • Table 8. The population coverage (PC) of MHC-I and MHC-II proposed epitopes. The population coverage of MHC-I was 80.53%, MHC-II was 99.99% and the combined alleles was 100% for all proposed epitopes )PC: Population Coverage)
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In article      View Article  PubMed
 
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In article      View Article  PubMed
 
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In article      
 
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In article      View Article  PubMed
 
[31]  Hall, T.A. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. in Nucleic acids symposium series. 1999. [London]: Information Retrieval Ltd., c1979-c2000.
In article      
 
[32]  Kumar, S., G. Stecher, and K. Tamura, MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular biology and evolution, 2016. 33(7): p. 1870-1874.
In article      View Article  PubMed
 
[33]  Jespersen, M.C., Peters, B., Nielsen, M., Marcatili, P. BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017; 45, W24-W29.
In article      View Article  PubMed
 
[34]  Emini, E.A., Hughes, J.V., Perlow, D., Boger, J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J. Virol. 1985; 55, 836-839.
In article      View Article  PubMed
 
[35]  Kolaskar, A., Tongaonkar, P.C. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990; 276, 172-174.
In article      View Article
 
[36]  Dimitrov, I., Naneva, L., Doytchinova, I.A., Bangov, I. Allergen FP: allergenicity prediction by descriptor fingerprints. Bioinformatics. 2014; 30, 846-851.)
In article      View Article  PubMed
 
[37]  Dimitrov et al., 2013 Dimitrov, I., Bangov, I., Flower, D.R., Doytchinova, I.A. AllerTOP v.2- a server for in silico prediction of allergens. J Mol. Model. 2013; 20, 2278.
In article      View Article  PubMed
 
[38]  Fiers, M.W.E.J., Kleter, G.A., Nijland, H., Peijnenburg, A., Nap, J.P., Ham, R. Allermatch™, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines. BMC Bioinform. 2004; 5, 133.
In article      
 
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In article      View Article  PubMed
 
[40]  Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R. Open source drug discovery consortium, Raghava GP in silico approach for predicting toxicity of pep-tides and proteins. PLoS One. 2013; 8 (9), e73957.
In article      View Article  PubMed
 
[41]  Peng, J. and J. Xu, A multiple‐template approach to protein threading. Proteins: Structure, Function, and Bioinformatics. 2011. 79(6): p. 1930-1939.
In article      View Article  PubMed
 
[42]  Glass RI, Parashar UD, Estes MK. Norovirus gastroenteritis. N Engl J Med. 2009; 361: 1776-85.
In article      View Article  PubMed
 
[43]  Ettayebi K, Crawford SE, Murakami K, et al. Replication of human noroviruses in stem cell-derived human enteroids. Science. 2016; 353(6306): 1387-1393
In article      View Article  PubMed
 
[44]  Tucker SN, Tingley DW, Scallan CD. Oral adenoviral-based vaccines: historical perspective and future opportunity. Exp Rev Vaccines. 2008; 7: 25-31.
In article      View Article  PubMed
 
[45]  Guo L, Wang J, Zhou H, et al. Intranasal administration of a recombinant adenovirus expressing the norovirus capsid protein stimulates specific humoral, mucosal, and cellular immune responses in mice. Vaccine. 2008; 26; 460-468.
In article      View Article  PubMed
 
[46]  Guo L, Zhou H, Wang M, et al. A recombinant adenovirus prime-virus-like particle boost regimen elicits effective and specific immunities against norovirus in mice. Vaccine. 2009; 27: 5233-5238.
In article      View Article  PubMed
 
[47]  Azim KF, Mahmudul H, Hossain Md N, Somana SR et al. Immunoinformatics approaches for designing a novel multi epitope peptide vaccine against human norovirus (Norwalk virus). Infection, Genetics and Evolution. 2019; 74 (103936)
In article      View Article  PubMed
 
[48]  Black M, Trent A, Tirrell M, Olive C. Advances in the design and delivery of peptide subunit vaccines with a focus on toll-like receptor agonists. Expert review of vaccines. 2010; 9(2): 157-73.
In article      View Article  PubMed
 
[49]  Hasan, M., Azim, K.F., Begum, A., Khan, N.A., Shammi, T.S., Imran, A.S., Chowdhury, I.M., Urme, S.R. Vaccinomics strategy for developing a unique multi-epitope monovalent vaccine against Marburg marburgvirus. Infect. Genet. Evol. 2019; 70, 140-157.
In article      View Article  PubMed
 
[50]  Garcia, K.C., Teyton, L., Wilson, I.A. Structural basis of T cell recognition. Annu. Rev. Immunol. 1999; 17, 369-397.
In article      View Article  PubMed
 
[51]  Shrestha, M.P., et al., Safety and efficacy of a recombinant hepatitis E vaccine. New England Journal of Medicine, 2007. 356(9): p. 895-903.
In article      View Article  PubMed