Epitope Based Vaccine Designing- A mini review

A vaccine is an antigen derived from pathogen. In its crudest form vaccine contains either attenuated pathogen, or an antigen molecule as in case of subunit vaccine, yet what interacts with immune system are few amino acids in the form of epitopes [1]. The idea to form a vaccine from selective few epitopes has emerged as a more logical approach owing to the fact that the conventional approaches are slow and selection of antigen is more or less random. In the last 5 years a lot of new vaccine candidates have been proposed which are based on B Cell Epitopes (BCE) and T Cell Epitopes (TCE) [2]. This approach of rapid identifi cation of immuno epitopes is centered on computational predictions, which utilize advance algorithms and increasing epitope data base. Epitope prediction is one of the most important corner stones of in-silico vaccine designing, however it depends on antigen identifi cation, and most crucially epitope selection for an effective immune response.


Introduction
A vaccine is an antigen derived from pathogen. In its crudest form vaccine contains either attenuated pathogen, or an antigen molecule as in case of subunit vaccine, yet what interacts with immune system are few amino acids in the form of epitopes [1]. The idea to form a vaccine from selective few epitopes has emerged as a more logical approach owing to the fact that the conventional approaches are slow and selection of antigen is more or less random. In the last 5 years a lot of new vaccine candidates have been proposed which are based on B Cell Epitopes (BCE) and T Cell Epitopes (TCE) [2]. This approach of rapid identifi cation of immuno epitopes is centered on computational predictions, which utilize advance algorithms and increasing epitope data base. Epitope prediction is one of the most important corner stones of in-silico vaccine designing, however it depends on antigen identifi cation, and most crucially epitope selection for an effective immune response.
The in-silico vaccine designing is known as computational vaccinology. The advantage of computational vaccinology is, utilization of high through put data analysis methods for rapid antigen identifi cation, molecular docking and simulation models to test immunological responses [3]. This method can analyze multiple antigen candidates and whole proteomes for antigenicity and effi cacy in a relatively short time. Epitope search has an additional advantage to further narrow down the antigen screening for very short specifi c regions, thereby providing a possibility where protein-based manipulation can be used to synergies and select the appropriate immune response type (Figure 1).

Identifi cation of antigen and computational vaccinology
With the advent of high through put proteomics, vaccinologists now have access to multiple tools which can analyze a protein sequence for identifi cation and functioning in an organism along with its interaction and possible evolutionary conservation [4][5][6][7]. This approach is helpful in providing novel vaccine candidates in a relatively shorter time. One of the main reasons for the failure of a vaccine is its inability to generate specifi c immune response. By identifying and selecting the most potent antigens, this shortcoming can be avoided. In a recent attempt for a vaccine candidate for visceral leishmaniasis, the authors have applied extensive immuneinformatics approach to identify the most potent antigens based on KEGG (Kyoto Encyclopedia of Genes and Genomes] analysis of proteins involved in Protein-Protein Interaction (PPI)) networks and metabolic pathways [8,9]. VaxiJen2.0 is an alignment independent antigen prediction server, based on physico chemical properties of protein sequences, utilizing Auto Cross Covariance (ACC) [10,11]. Another online serve Jenner-Predict predicts antigen from functional domains of proteins involved in host pathogen interaction [12]. Similarly VacSol can predict potential therapeutic targets using subtractive reverse vaccinology [13]. AntigenDB is a database of previously validated antigens, the dataset includes data from various other databases like Swiss-Prot, MHCBN, AntiJen, IEDB, and BCIPEP [14]. These tools can help in identifi cation of most probable antigens which are able to generate desired immune response.

Epitope mapping and selection
B-cells recognize discontinuous conformational epitopes and continuous linear epitopes [15][16][17]. BCE arise due to protein folding as these epitopes are recognized by antibodies. The role of hydrophobic vs hydrophilic regions is open to discussion as it is now known that surface regions of protein contain same number of hydrophilic and hydrophobic residues [18]. Amino acid propensity scales applicable for B-cell epitope prediction are generally based on fl exibility [19], -turn propensity [20], and surface accessibility [21]. Prediction of 3D conformational epitope is more diffi cult than T cell epitopes owing to the uncertainty in prediction models of protein folding. The existing prediction models of conformational B cell epitopes require antigen 3D structure or homology-based model of the amino acid sequence. So far, no method is available which can predict conformational B cell epitope using antigen primary sequence in the absence of any homology with the known structures. The conformational B cell epitopes tend to be longer than 17 amino-acid (aa) sequence, since shorter aa sequences generally do not form conformational epitopes. ABCPred and BCPRED are B cell epitope prediction web servers which are based on ANN (Artifi cial Neural Network) and SVM (Support Vector Machine) [22,23]. Bcepred, predict B-cell epitopes on the basis of the physico-chemical properties (hydrophilicity, fl exibility/mobility, accessibility, polarity, exposed surface and turns) [24]. The accuracy for ABCPred and Bcepred is 65% and 58% respectively. One of the major constraints of accurate B cell epitope prediction is the small size of dataset used for model training, and use of random peptides as non B cell epitopes. CBtope is another webserver which can predict conformational B cell epitopes using SVM mechanics up to a prediction accuracy of more than 85% and Area Under Curve (AUC) 0.9 [25]. LBtope is a linear B cell epitope prediction model which is based on SVM and uses a larger dataset of validated B-cell epitopes and non-epitopes (12063 epitopes and 20589 non epitopes obtained from IEDB database) [26]. PickPocket for more accurate prediction than its competitors [29]. NetChop can predict the proteasomal cleavage sites for MHC-1 epitopes, while TAPPred can predict the binding affi nity towards TAP (Transporter associated with antigen processing) [30,31]. The TCE prediction software are basically divided in two groups viz. for MHC-I binders and for MHC-II binders.
The large number of alleles and sub alleles make it diffi cult ligands [32]. Similarly, NET MHC-I and NET MHC-II are able to predict TCE for humans as well as mouse [33]. The Propred is an MHC-II prediction server based on quantitative matrix [34]. has not been shown to be dependent on the nature of epitope, although the alteration of single amino acid in epitope has been shown to completely alter the immune response type [36,37]. In this context so far, it has been impossible to predict the epitopes for Th1 or Th2 cell responses. One online server, the IFNepiotpe can predict IFN- inducing epitopes, thereby predicting the immunological response type [38]. Similar to IFNepiotpe CTLpred is based on direct methods of prediction where the information or patterns of T cell epitopes, instead of MHC binders, are used for the development of methods [39].
The method is based on Artifi cial Neural network and support vector machine, which allows the consensus and combined prediction based on these two approaches.

Effective vaccine
In natural course of infection both cell-mediated immunity as well as humoral immunity are required to clear the infection, therefore an integral approach, combining both T-cell and B-cell epitopes, is the appropriate way to design a vaccine.
The BCE and TCE can be linked by linker sequences which are amino acids with neutral charge and maximum rotational degree of freedom. Another possibilty to combine TCE and BCE is to isolate those regions of antigens which are both B cell epitope positive and T cell epitope positive. For designing an epitope-based vaccine one must address the question of, how many epitopes and which epitopes to choose. There is no straight forward solution to this problem but it is evident from previous research that large size molecules generate better immune response as they are able to mimic the natural antigen and its course of immune activation, shorter peptides have high Expect value (e value) and the probability of fi nding similar peptides as self-antigen is relatively larger compared to proteins with larger size [40,41]. One possibilty is to take it one step further in this regard by integrating multiple epitopes from different antigens and use them in a cocktail/chimeric manner forming a multiepitope construct to synergize the immune response of single epitope into a cumulative effect. One of the advantages of multiple epitope utilization is the increase in the HLA diversity. More research is required to understand the synergy of epitope integration as very few vaccine candidates with chimeric epitopes have been tested as on today [42,43]. T-cell population [49]. Therefore, it is expected from a vaccine candidate to induce a larger effector T-cell population possible.
Epitope based vaccines can enhance this initial effector burst phase by utilizing only the relevant and immunogenic epitopes. Another advantage of using epitope-based vaccine compared to conventional vaccines is in case of chronically ill patiens, which have consistent high antigen levels causing T cell exhaustion. In those cases, epitope identifi cation and use of newer or protective epitopes can provide a better vaccine candidate. Epitope based vaccine development provides a better grip on the amount and specifi city of antigen required to activate T cells and can provide better candidates which are effective in generating either Memory CD4+ T cells by using selective MHC-II epitopes or Memory CD8+ T cells by MHC-I epitopes.

Recent developments
Most important implication of epitope-based vaccines would be to address diseases for which conventional methodologies  [50,51]. Remarkably weak TCR stimulation at immuno synapse is enough to generate a robust memory response, while sustained duration of signal along with higher antigen levels generates enhanced proliferation [52]. The role of epitope alone during TCR and HLA association dictating the downstream events would need to be explored, as this will answer the question why certain antigens are able to generate good memory response and others fail.
Epitope based vaccines are also emerging for cancer therapy and many candidates are being tested on both therapeutic and prophylactic basis. Since almost all proteins from a cancerous cell are similar to the normal proteins present in the body, the minute differences limit to only a few amino acid alterations, which can be utilized as epitope-based vaccine candidate. One candidate to use multiple epitopes is Survivin derived multiepitope vaccine EMD640744 for advanced solid tumors [53].  [57]. For all the proposed vaccines for SARS-CoV-2 the immune-effi cacy has been assessed in-silico by immune-simulation. Many of these candidates are hypothetical and are not validated by in-vitro analysis for immunological responses instead they have utilized molecular docking to give an early assessment.
The vaccine designing for SARS-COV-2 has emphasized the importance of immune-informatics and epitope mapping to identify protein regions, which are physiologically vital for the virus and have the ability to generate immune response.

Concluding remarks
With ever increasing database of confi rmed epitopes and new algorithms for computation, B and T cell epitope prediction is becoming more reliable for novel vaccine designing. After the emergence of servers like IFNepitope, it might become possible in future to identify cytokine specifi c epitopes . These cytokine specifi c epitopes could then be used as therapeutic candidates. The presence of cytokine specifi c epitopes could be the reason why crude antigens fail to generate a specifi c immune response (presence of undesirable epitopes), although there is no experimental evidence present and this idea requires more research. Nonetheless, the possibility of cytokine specifi c epitopes has not only provided us a tool for vaccine designing but has also emphasized on the possible role of epitope alone in T cell activation. This question seems to be centered around the role of T cell receptor and its mechanism of activation.
Currently two mechanisms available to address this scenario are, Conformation Change Model and the Kinetic Segregation Model, both models fail to address how a single amino acid substitution in the epitope can results in different downstream pathway activation. Since it is an epitope, which actually holds the specifi city while generating an antibody response and T cell activation, the non-epitope domains of protein become not only useless but can also sterically shield the immunogenic epitope domains. Thus, the epitope-based vaccine designing can provide us with new candidates in this regard where large antigen derived vaccines have not been successful.