Journal of
Computational Biology and Bioinformatics Research

  • Abbreviation: J. Comput. Biol. Bioinform. Res
  • Language: English
  • ISSN: 2141-2227
  • DOI: 10.5897/JCBBR
  • Start Year: 2009
  • Published Articles: 39

Full Length Research Paper

Selection of T cell epitopes from S. mansoni Sm23 protein as a vaccine construct, using Immunoinformatics approach

Onile Olugbenga Samson
  • Onile Olugbenga Samson
  • Biotechnology Unit, Department of Biological Sciences, Elizade University, Ilara-Mokin, Ondo State, Nigeria.
  • Google Scholar
Fadare Shadrach Olaleka
  • Fadare Shadrach Olaleka
  • Microbiology Unit, Department of Biological Sciences, Elizade University, Ilara-Mokin, Ondo State, Nigeria.
  • Google Scholar
Omitogun G. Ofelia
  • Omitogun G. Ofelia
  • Biotechnology Unit, Department of Biological Sciences, Elizade University, Ilara-Mokin, Ondo State, Nigeria.
  • Google Scholar


  •  Received: 20 July 2016
  •  Accepted: 19 January 2017
  •  Published: 31 May 2018

 ABSTRACT

Schistosomiasis, a neglected and most prevalenttropical diseases after malaria, have been a threat to people living in endemic areas. With regards to possible resistance to the popular drug (praziquantel) use for treatment of schistosomiasis, the need for a permanent vaccinating approach has been justified. This study uses an in silico approach to identify potential target vaccine candidate or T cell epitopes (T cell response activating epitope) for the treatment of schistosomiasis. This research therefore identified some candidate T cell epitopes from Sm23 protein of Schistosma mansoni using immunoinformatics tools. Nonameric epitopes like 85YMYAFFLVV93, 83MLYMYAFFL91, 8MRCLKSCVF16, 41SQYGDNLHK49 and 104VAVVYKDRI112 was found to exhibit strong binding affinity with some human leukocyte antigen (HLA). The predicted epitope was found to have no similarity with human proteome, a good attribute that is conferred on any good vaccine candidate. The predicted epitopes provide promising drug candidates and could be tested by wet laboratory as targeted vaccine against S. mansoni infection. 
 
Key words: Schistosomiasis, T-cell epitopes, human leukocyte antigen (HLA), vaccines.


 INTRODUCTION

Schistosomiasis is well-known as a significant public health problem in tropical and sub-Sahara Africa countries, despite the existence of effective drugs against the parasite. An estimated 732 million persons are vulnerable to schistosoma infection worldwide in renowned transmission areas (Onile et al., 2014; Adenowo et al., 2015). In 2008, 17.5 million people were treated globally for schistosomiasis, 11.7 million of these are from sub-Saharan Africa only. Approximately, 120 million individuals in sub-Saharan Africa have schistosomiasis-related symptoms while about 20 million undergo hardship as a result of chronic presentations of the disease (Adenowo et al., 2015).
 
The identification of a promising and sensitive vaccine candidate against schistosomiasis is important to help connect chemotherapy approach in controlling disease transmission (Fonseca et al., 2012). Epitopes based vaccines could provide a new strategy for the prophylactic and therapeutic application of pathogen specific immunity (Shah et al., 2010). T cell-based immunological responses are triggered by peptide antigens (T cell epitopes) by the major histocompatibility complex (MHC) molecules (also known as human leukocyte antigenHLA complex in human). This immunogenicity is dependent on several events; effective processing of the peptide from its protein source, stable peptide binding to the HLA molecule, and recognition of the HLA-bound peptide by the T cell receptor. Therefore, predicting HLA-peptide binding constitutes the principal basis for anticipating potential T cell epitopes and thus emphasises the relevance of epitope identification in vaccine design. Clinical trials of epitope based vaccines for human immunodeficiency virus, malaria and tuberculosis have produced promising results and thus support the identification and selection of T cell epitopes as vaccine candidates (Shah et al., 2010).
 
Sm23 belongs to the family of "cysteine-rich, hydrophobic proteins," which are expressed on mammalian hematopoietic cells or tumour cells. Sm23 shares the highly conserved hydrophobicity profile of these proteins, which predict four transmembrane segments, but is in addition linked to the membrane by a glycosylphosphatidylinositol (GPI) anchor. Sm23 is an integral membrane protein of the blood-vessel dwelling parasitic worm Schistosoma mansoni, which has been confirmed to be expressed in all schistosome life stages examined and in several tissues, including the adult tegument and therefore is of interest as a potential vaccine candidate (Reynolds et al., 1993; Carina et al., 2011).
 
Therefore identifying Sm23 T cell epitope-based vaccine will provide a promising and lasting solution to the spread and pathology of schistosomiasis in endemic areas. This study therefore focuses on predicting MHC-peptide binding epitope and discusses their most relevant advantages and drawbacks.


 METHODOLOGY

Schistosoma mansoni Sm23 protein
 
S. mansoni Sm23 protein sequence was retrieved from the NCBI database with the ID gi|124391|sp|P19331.1|IM23_SCHMA. A blast search was performed to screen for the homologues of Sm23 protein present in other Schistosoma species. The program compared the sequences with sequences database and the statistical significance of matches.
 
Protein sequence analysis, subcellular localization and 3D modeling
 
The Sm23 protein structural analysis was done using PSIPRED server (Bunchan et al., 2013). The biological and molecular function was also predicted, while selecting the ffpred link of PSIPRED server (Buchan et al., 2013). The Sm23 secondary structure prediction method used in this study was according to Jones (1999) (http://bioinf.cs.ucl.ac.uk/psipred). The subcellular localization of the protein was predicted using PROTEINPREDICT server (https://www.predictprotein.org/) and SignalP (Petersen et al., 2011). This was done to look at the functional annotation of Sm23 protein for predicting immunogenicity. The transmembrane topology modelling was done according to Nugent and Jones, (2009) which also achieved by using the ffpred link of PSIPRED. The initial Sm23 protein 3D structure modelling was predicted using the Phyre2serverb (http://www.sbg.bio.ic.ac.uk/phyre2).
 
Prediction of the T cell epitopes and determination of self-peptide
 
The targeted Sm23 protein was analysed for the MHC Class I binding epitopes using different algorithms.  BIMAS (Parker et al., 1994) was used to predict all overlapping peptides with human HLA alleles which then produced promiscuous epitopes that bind with the HLA showing high affinity. The binding affinity (T1/2) value based on half time association of β2 microglobulin from HLA was set at a value >=100 for peptide selection. The peptides with low affinity were also identified in cases where T(1/2) value was based on explicit number alone. Other computational tools like SYFPEITH was used to further help in predicting HLA binding T cell epitopes on Sm23 protein (http://www.syfpeithi.de/) (Rammensee et al., 1996). All the high affinity HLA binding peptides were analysed for the presence of human-self peptides using HLAPRED.
 
Prediction of sequencelogo plot
 
In order to determine the peptide characteristics binding motif to a MHC complex, the study of a sequence logo plot was carried out. The peptide predicted by the above mentioned tools were given as input sequences to weblogo tool (http://weblogo.threeplusone.com/create.cgi) to create a sequence logo of the predicted binder and to look for frequency of each amino acid in the 9mer peptide sequences. The sequence logo was created by taking all top scoring peptides obtained from SYFPEITH database.

 


 RESULTS

Homologous and subcellular localization of Sm23 protein
 
The blast search revealed that the Sm23 protein is specific to S. mansoni, as the protein was not found in human beings. Predictprotein (https://www.predictprotein.org) server predicted the protein as a 23 kDa integral membrane protein, this assertion was later support by further protein analysis using PSIPRED server to predict the protein  transmembrane topology (Figure 1B). The 3D structure of Sm23 protein as predicted by phyre 2 server is shown in Figure 1A and the secondary structure analyses of the queried protein have revealed that majority of the target protein consist mostly of α-helices with few loops and no β-sheet (Figure 5). The signalP tool which incorporates a prediction of cleavage sites and signal/non-signal peptide predicted no presence of signal peptide in the protein. Further protein analysis also suggested its biological and molecular role in transmembrane transport activity and also its function in signal transduction activity (Tables 1 and 2).
 
 
 
 
Prediction of specific HLA Class I T cell epitope
 
The predicted epitope with their HLA alleles have been summarized in Table 3. Identifying the affinity of interaction between the predicted T-cell epitope and HLA is essential, as the inclusion of such peptides in vaccine design will provide more population coverage and help reduce the number of peptides that need to be involved in the vaccine (Brusic et al., 2002; Shah et al., 2010). The results from predicted overlapping sequences of the consensus Sm23 protein to the human 33 Class I HLA alleles at various affinities identified 53 nonameric peptide sequences which bind both at low and high affinity to the different HLA alleles (Table 3). The observed binding affinities of the predicted epitopes with the HLA alleles shows that alleles like HLA B_2705, HLA B_5102 and HLA B_5201 bind to most of the peptides showing the tallest bar in the graph (Figure 4) and the rear peptides binder like HLA A1, HLA A24, HLA Cw_0702, HLA B­_2702, B60 and B40 binds to very less peptides while some do not bind at all.
 
The epitope HLA_A0201 bind to peptide sequences 85YMYAFFLVV93 and 83MLYMYAFFL91 at an affinity score of 2189 and 3707.145, respectively. Peptides 8MRCLKSCVF16 AND 41SQYGDNLHK49 bind to HLA B_2705 both at affinity score of 1000. Sequence 104VAVVYKDRI112 binds to HLA B_5102 at score 1200 and also bind to HLA B_5101 (score 314.6) and B_5103 (score 133.1). It is therefore necessary to include peptides that bind to the rare HLA alleles in a vaccine cocktail to achieve the desired population coverage (Parida et al., 2007). The choice of multiple computational tools in selecting HLA Class I T-cell epitope is to minimize the chances of failure in selection of a universal vaccine candidate while ensuring that only peptides with positive scores were selected. The prediction of presence of human-self peptides using HLAPRED showed that the predicted epitopes are nonhuman but parasite specific (Figure 3).
 
 
 
 
 

 


 DISCUSSION

Investigation using bio-computational approach was conducted on antigen presentation and identification of epitopes on different HLA molecules. Interest was on S. mansoni, as there is no efficacious vaccine reported against this parasite. The highly reported S. mansoni Sm23 protein was chosen in this study, in order to predict epitope that could be useful as possible vaccine candidate in eliciting immunological response against the parasite.
 
The blast search conducted proved that the homologous protein obtained was specific for S. mansoni pathogen. It is important to establish the subcellular localization of a pathogen protein to predict the most accessible pool of potential target using integrative approaches (Shah et al., 2010). Hence, the subcellular localization information obtained using in silico approaches (Psipred, proteinpredict and SignalP) confirmed the protein to function in cell surface signal pathways and substrate-specific transmembrane transporter activity. This information provides valuable clues regarding the protein molecular function in drug design as secreted or surface exposed protein and periplasmic protein were reported to be of primary interest due to their potentials as vaccine candidate and the ease with which they are accessible to drugs (Namrata et al., 2010). In all the 53 peptides epitopes predicted from the Sm23 protein with several computational tools like ProPred, SYFPEITHI, nHLAPred, only 5 promiscuous peptides recorded high immunogenicity. The need to use several analytic tools for peptide prediction became imperative to select only peptides that exhibit positive binding scores under extensive analysis by multiple methods because some peptide do bind when analysed by one algorithm and do not by another. All efforts to predict accurately peptide immunogenicity will help reduce several experimental efforts (Shah et al., 2010). It should also be noted that the prediction of peptide immunogenicity is influenced by many factors which include intrinsic physicochemical properties and extrinsic factors such as host immunological repertoire (Saffari et al., 2008, Namrata et al., 2010).
 
Namrata et al. (2010) suggested that predicted epitopes with high binding affinity are better suited for wet lab studies. It was observed that 4 out of the 5 predicted epitopes (85YMYAFFLVV93,83MLYMYAFFL91, 8MRCLKSCVF16 and 104VAVVYKDRI112) with high affinities to the HLA alleles are rich with hydrophobic and charged amino acids residue thus making them a good choice for inclusion in an experimentally drug design study. It is has been reported that MHC pockets favourably interact with hydrophobic or charged amino acid residues at carboxyl to enhance proper binding in pockets (Brusic et al., 2002). The interaction between peptide and a MHC molecule is mediated through anchors on the peptide side chains of amino acids at predetermined positions  that  protrude  into  complementary pockets of the class I groove (Parida et al., 2007; Petersen et al., 2004; Namrataet al., 2010). In peptide interaction with MHC class I, most of the bonding forces are provided by non-allele specific interactions such as the bonds between the peptides termini and the class I groove (Guo et al., 1993; Namrate et al., 2010). The MHC groove pockets determined the specificity of peptide interactions with fixed spacing from each other and the class I pockets are generally more specific in the amino acid residues that they bind (Brusic et al., 1995).


 CONCLUSION

The study therefore concluded that with predicted T-cell epitopes from Sm23, a transmembrane transporter protein using in silico approach can be targeted for vaccine constructs while considering its expression throughout all schistosome life stages. Also, all high binding affinity epitopes will be suited for wet laboratory experiment while understanding that vaccine formulations against schistosomiasis can be achievable only if the epitopes are able to elicit immune response under in vitro studies.

 


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interest.



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