Selection of epitope-based vaccine targets of HCV genotype 1 of Asian origin: a systematic in silico approach

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.

Broad Spectrum Peptide Vaccine Design Against Hepatitis C Virus

BACKGROUND

Hepatitis C virus (HCV) infection is a global burden. There is no peptide vaccine found as modality to cure the disease is available due to the weak cellular immune response and the limitation to induce humoral immune response.

METHODS

Five predominated HCV subtypes in Indonesia (1a, 1b, 1c, 3a, and 3k) were aligned and the conserved regions were selected. Twenty alleles of class I MHC including HLA-A, HLA-B, and HLAC types were used to predict the potential epitopes by using NetMHCPan and IEDB. Eight alleles of HLA-DRB1, together with a combination of 3 alleles of HLA-DQA1 and 5 alleles of HLA-DQB1 were utilized for Class II MHC epitopes prediction using NetMHCIIPan and IEDB. LBtope and Ig- Pred were used to predict B cells epitopes. Moreover, proteasome analysis was performed by NetCTL and the stability of the epitopes in HLA was calculated using NetMHCStabPan for Class I. All predicted epitopes were analyzed for its antigenicity, toxicity, and stability. Population coverage, molecular docking and molecular dynamics were performed for several best epitopes.

RESULTS

The results showed that two best epitopes from envelop protein, GHRMAWDMMMNWSP (E1) and PALSTGLIHLHQN (E2) were selected as promising B cell and CD8+ T cell inducers. Other two peptides, LGIGTVLDQAETAG and VLVLNPSVAATLGF, taken from NS3 protein were selected as CD4+ T cell inducer.

CONCLUSION

This study suggested the utilization of all four peptides to make a combinational peptide vaccine for in vivo study to prove its ability in inducing secondary response toward HCV.

Short peptide epitope design from hantaviruses causing HFRS

Several genotypes of the hantavirus cause hemorrhagic fever with renal syndrome (HFRS) and is an important public health problem worldwide. There is now growing interest to develop subunit vaccines especially focused to elicit cytotoxic T lymphocyte responses which are important against viral infection. We identified candidate T-cell epitopes that bind to Class I HLA supertypes towards identifying potential subunit vaccine entity. These epitopes are conserved in all 5 hantavirus genotypes of HFRS (Hantaan, Dobrava- Belgrade, Seoul, Gou virus and Amur). The epitopes identified from S and M segment genomes were analyzed for human proteasome cleavage, transporter associated antigen processing (TAP) efficiency and antigenicity using bioinformatic approaches. The epitope MRNTIMASK which had the two characteristics of high proteasomal cleavage score and TAP score, also had high antigenicity score. Our results indicate that this epitope from the nucleocapsid protein may be considered the most favorable moiety for the development of subunit peptide vaccine.

In silico study of potential autoimmune threats from rotavirus infection

Rotavirus, the major cause of infantile nonbacterial diarrhea, was found to be associated with development of diabetes-associated auto-antibodies. In our study we tried to find out further potential autoimmune threats of this virus using bioinformatics approach. We took rotaviral proteins to study similarity with Homo sapiens proteome and found most conserved structural protein VP6 matches at two regions with ryanodine receptor, an autoimmune target associated with myasthenia gravis. Myasthenia gravis, a chronic neurodegenerative autoimmune disorder with no typical known reason, is characterized by fluctuating muscle weakness which is typically enhanced during muscular effort. Affected patients generate auto antibodies against mainly acetyl choline receptor and sarcoplasmic reticulum calcium-release channel protein ryanodine receptor. Further, we observed that two regions which matched with ryanodine receptor remain conserved in all circulating rotaviral strains and showed significant antigenecity with respect to myasthenia gravis associated HLA haplotypes. Overall, our study detected rotaviral VP6 as a potential threat for myasthenia gravis and enlighten an area of virus associated autoimmune research.