Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein：An in silico approach

Hamza Dar， Tahreem Zaheer， Muhammad Talha Rehman， Amjad Ali， Aneela Javed✉， Gohar Ayub Khan， Mustafeez Mujtaba Babar， Yasir Waheed

1Atta-ur-Rahman School of Applied Biosciences （ASAB）， National University of Sciences and Technology， Islamabad （44000）， Pakistan

2Shifa College of Pharmaceutical Sciences， Shifa Tameer-e-Millat University， Islamabad

3Foundation University Medical College， Foundation University Islamabad， DHA-I Islamabad （44000）， Pakistan

Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein：An in silico approach

Hamza Dar1， Tahreem Zaheer1， Muhammad Talha Rehman1， Amjad Ali1， Aneela Javed1✉， Gohar Ayub Khan1， Mustafeez Mujtaba Babar2， Yasir Waheed3✉

1Atta-ur-Rahman School of Applied Biosciences （ASAB）， National University of Sciences and Technology， Islamabad （44000）， Pakistan

2Shifa College of Pharmaceutical Sciences， Shifa Tameer-e-Millat University， Islamabad

3Foundation University Medical College， Foundation University Islamabad， DHA-I Islamabad （44000）， Pakistan

ARTICLE INFO

Article history:

Received 15 May 2016

Received in revised form 16 June 2016

Accepted 1 July 2016

Available online 20 September 2016

Zika Virus

B-Cell Epitopes

T- Cell Epitopes

Vaccine

Antigenicity

Objective: To predict immunogenic promiscuous T-cell epitopes from the polyprotein of the Zika virus using a range of bioinformatics tools. To date， no epitope data are available for the Zika virus in the IEDB database. Methods: We retrieved nearly 54 full length polyprotein sequences of the Zika virus from the NCBI database belonging to different outbreaks. A consensus sequence was then used to predict the promiscuous T cell epitopes that bind MHC 1 and MHC II alleles using Propred1 and Propred immunoinformatic algorithms respectively. The antigencity predicted score was also calculated for each predicted epitope using the VaxiJen 2.0 tool. Results: By using ProPred1， 23 antigenic epitopes for HLA class I and 48 antigenic epitopes for HLA class II were predicted from the consensus polyprotein sequence of Zika virus. The greatest number of MHC class I binding epitopes were projected within the NS5 （21%）， followed by Envelope （17%）. For MHC class II， greatest number of predicted epitopes were in NS5 （19%） followed by the Envelope， NS1 and NS2 （17% each）. A variety of epitopes with good binding affi nity， promiscuity and antigenicity were predicted for both the HLA classes. Conclusion: The predicted conserved promiscuous T-cell epitopes examined in this study were reported for the fi rst time and will contribute to the imminent design of Zika virus vaccine candidates， which will be able to induce a broad range of immune responses in a heterogeneous HLA population. However， our results can be verif i ed and employed in future effi cacious vaccine formulations only after successful experimental studies.

1. Introduction

Zika virus is a single stranded RNA virus belonged to Flaviviridae family ［1］. The genome of the virus is 10 794 nucleotides long，which is translated into 3 410 amino acids ［2］. The large polypeptide chain that is encoded by long and single ORF is cleaved into: Envelope， a membrane precursor， a capsid and non-structuralproteins including NS1， NS2A， NS2B， NS3， NS4A， 2K， NS4B， and NS5. The envelope protein of the virus is involved in the process of fusion of the virus with the receptor of host cells and is also involved in the replication cycle of the virus. The NS5 protein has two terminals: N terminus and C terminus， the N terminus has a role in protection of RNA while the C terminus encodes RNA dependant RPA activity ［3］.

During 1947-2006， more than twenty cases of Zika virus infection were reported， but the research on them was not given prime importance because of its geographical spread limited to the countries in Africa and South Asia， and mild clinical signs and symptoms of the Zika virus infection ［4］. After 2006， a sudden outbreak of Zika virus was reported in 2007 in the Yap Island，where 73% of the population was infected with Zika virus ［5］. In 2013 a major outbreak of Zika virus was reported in the French Polynesia ［6］. The infectious Zika virus then started spreading intothe other islands of Pacific Ocean and in 2014 it arrived in Chile and Eastern island of Western Hemisphere ［7］ and in Latin America probably due to infected travellers. The virus is a mosquito borne virus， and mosquito plays a key role in the transmission of the Zika virus infection in humans， which is the primary host of Zika virus. The transmission of Zika virus is carried out by Aedes species that includes Aedes albopictus （Ae. albopictus）， Aedes aegypt （Ae. aegypt）［8］， Aedes luteocephalus （Ae. luteocephalus）， Aedes furcifer （Ae. furcifer），Aedes taylori （Ae. taylori）， Aedes africanus （Ae. africanus）， and monkeys（Rhesus Macaques） ［9］. The studies on the transmission of Zika virus show that the virus can be transmitted through sexual contact ［10］due to its extended persistence in the semen ［11］， and also through blood transfusion ［12］. Viral load is greater than other arboviruses and commences about ten days before the clinical manifestation of the disease ［13］. The acute symptoms of Zika virus infections are arthralgia， maculopapular rash， myalgia， conjunctivitis， emesis，retro-orbital pain and headache； however， 80% of the patients are asymptomatic during the initial stages of infection. Recent reports about the outbreak of Zika virus in Brazil are linked to microcephaly and Guillain-Barre syndrome ［14］. This association poses serious teratogenic and neuropathic risks to the health of fetus. A fatal Zika virus infection has also been reported that shows increased risk of disease and mortality in individual having compromised immune system ［15］.

The infection of Zika virus is fatal and can cause serious health threatening issues， so an antiviral vaccine or antiviral therapy needs to be designed in order to control the disease state. Antiviral therapies need to be designed by targeting enzymes that are involved in post translational packaging of viral protein ［16］ or by targeting enzymes that are essential for the replication of virus ［17］. Development of vaccine for the treatment of Zika virus is extremely important in current situation as the virus has caused a great number of deaths in Brazil and is spreading in the other parts of world. Currently there is no prophylactic or therapeutic vaccine available in the market to curtail this infection.

Though the development of live attenuated YFV vaccine was a milestone but with the new advancements， epitope-based vaccine are gaining more importance， as the live attenuated vaccine may prove fatal in immunocompromised patients ［18］.

Advances in immunoinformatics research found that many conservative and highly immunogenic T/B cell epitopes （antigenic determinants that are recognized by host immune cells and can elicit both a humoral and cellular immune response） on the virus antigen could be used as potential vaccine targets. These epitopes can induce a protective immune response against a wide range of pathogenic microorganisms. After the artificial T-cell epitope is presented via the appropriate MHC molecule on the surface of the target cell to its corresponding T-cell， the epitope is recognized by T cells through TCR recognition， thereby activating the T-cell to proliferate and generate an appropriate immune response. Based on this scenario， the use of dif f erent pathogenic microorganisms and their corresponding T cell epitopes can be used to develop a CD4+T cell epitope vaccine （mostly for exogenous antigens that are degraded in the APCs after phagocytosis， thereafter binding to MHC II molecules， and finally presentation to CD4+T cells） or a CD8+T cell epitope vaccine （mostly for endogenous antigen that are digested following uptake by the APCs， and subsequent presentation to CD8+T cells via MHC-I molecules ［19］.

Epitope vaccine or an epitope based subunit-vaccine has lesser side ef f ects when compared to conventional vaccines， is easier to produce，is cheaper to manufacture， is easier to get rid of in the in vitro restriction cultures when compared to engineered subunit vaccines，does not contain any complete component of the pathogens， allows for the in vitro incorporation of sugar analogs which is difficult to achieve through engineered subunit vaccines and also takes less time to produce along with improved stability， specif i city and sustainability ［20］. However， due to the highly polymorphic nature of the HLA genes in the human population， the epitope specif i c HLA restricted vaccine is not normally expected to cause an immune response in all individuals within a given population. Thus， there is a need for the development of promiscuous epitopes that can bind to multiple HLA alleles within a heterogeneous population thereby catering to the need of a wide range of individuals ［21］.

The present study targets the near full length polyprotein of the Zika virus containing key structural and non-structural proteins， for prediction of promiscuous and antigenic epitopes using a range of online tools for the development of a safe and ef f ective epitope based subunit vaccine.

2. Materials and methods

2.1. Sequence retrieval

54 Zika virus polyprotein sequences derived from 54 different genomes were retrieved from the NIAID Virus Pathogen Database and Analysis Resource （ViPR） through the web site at ［22］ as shown in S1 Table. The sequences were aligned and consensus sequence was generated using the multiple sequence alignment tool，Jalview［23］.

2.2. Prediction of T -cell epitopes

To determine the T Cell epitopes， both HLA I and HLA II binding peptide sequences were required. ProPred I （www.imtech.res.in/ raghava/ProPred1/） ［24］was used to predict the HLA class I binding promiscuous epitopes in the consensus sequence. 4% default threshold value was selected and proteasome and immunoproteasome fi lters were enabled at 5% threshold value to maximize the effi ciency of fi nding T Cell epitopes. ProPred I determines epitopes that can bind to 47 HLA class I alleles. To predict epitopes for HLA class II alleles， ProPred ［25］ was used at a cut of f value of 3% threshold. ProPred allows the prediction of antigenic epitopes for 51 HLA class II alleles.

2.3. Antigenic prediction

All the promiscuous T cell epitopes obtained from ProPred and ProPred1 tools were analysed for their antigenic properties using VaxiJen version 2.0 at ［26］.Threshold value of 0.5 antigenic score was kept to fi ler probable non-antigenic sequences. Moreover， 87%accurate results are obtained for viruses at this default threshold. Vaxijen server performs alignment-independent prediction of protective antigens on the basis of their physicochemical properties.

2.4. Class I immunogenicity prediction

All the HLA 1 binding antigenic epitopes were scanned for MHC 1 immunogenicity using IEDB Analysis tool ［27］. Default parameters were selected to perform the immunogenicity prediction. The tool uses amino acid properties as well as their position within the peptide to predict the immunogenicity of a peptide MHC complex.

2.5. Validation of predicted epitopes

The epitopes predicted in our study were submitted to IEDB database to check if they had been tested earlier. The IEDB database contains experimentally conf i rmed data characterizing antibody and T cell epitopes studied in homo sapiens， NHPs， and other animal species.

3. Results

3.1. Prediction of HLA I binding epitopes

By using ProPred1， 23 antigenic epitopes for HLA class I were predicted in the consensus polyprotein sequence of Zika virus （Table 1）. Epitopes were highly conserved across the dif f erent strains of Zika virus. Notably， the promiscuous epitope NS52592-2600was found to bind to 26 of the 47 HLA class I alleles.

Epitope C25-34was predicted to bind to 18 HLA class I alleles. However， its antigenicity score was 0.2 434. Hence， that epitope was not considered for further immunogenicity analysis. Epitope prM211-219was predicted to bind to 7 alleles and its antigenicity score was signif i cant i.e. 1.035 9.

The overall antigenic prediction of epitope E777-785was the highest among the envelope epitope sequences. However， it was predicted to bind to only 7 HLA class I alleles. Epitopes E706-714and E757-765were predicted to bind 12 alleles. However， their antigenicity scores were below 0.5， indicating that they were non-antigenic sequences.

NS1897-905was predicted to bind 18 alleles. However， its antigenicity score was determined to be signif i cantly low i.e. -0.437 5. Similarly，NS11017-1025was predicted to bind 14 alleles but its antigenicity was -0.200 1. NS11059-1067was found to bind to 13 alleles and its antigenicity was signif i cant i.e. 0.822 5. Moreover， this epitope was found to be conserved among all the polyprotein sequences in our study. Hence， NS11059-1067was the most suitable epitope identif i ed in the NS1 of polyprotein.

Similarly， NS2A1339-1347， NS2A1355-1363and NS2A1156-1164were identif i ed as the most signif i cant epitopes in the NS2A. NS2B1402-1410and NS2B1381-1389were predicted to bind 14 and 10 HLA class I alleles respectively and their antigenicity score was found to be signif i cant i.e. 0.85.

Epitopes NS32018-2026， NS31622-1630and NS31688-1696were predicted to bind 20， 9 and 6 number of alleles and their antigenicity scores were found out to be 1.135 1， 1.650 7 and 1.506 4. Remarkably， all these three epitopes were found to be completely conserved among all the polyprotein sequences included in our study.

Similarly， NS4A2199-2207， NS4A2177-2185and NS4A2220-2238were predicted to bind 7， 9 and 8 number of HLA class I alleles and their antigenicity scores were found to be 1.9567， 1.2576 and 0.817 4， respectively. However， the immunogenicity score of epitope NS4A2177-2185was found to be significantly low i.e. -0.007 04.Interestingly， the other two epitopes were found to be completely conserved among all the polyprotein sequences included in the study，indicating that they may have potential evolutionary signif i cance. NS4B2459-2467was predicted to bind 10 HLA class I alleles and its antigenicity score was significant i.e. 0.798 5. Epitopes NS52592-2600and NS52520-2528were predicted to bind 26 and 12 number of alleles respectively and their antigenicity scores were determined to be 0.809 7 and 0.571 0 respectively. However， the immunogenicity score of NS52592-2600was found to be signif i cantly low i.e. -0.012 96. Epitopes NS53065-3073， NS52638-2644and NS52898-2906were predicted to bind 7， 8 and 9 alleles respectively and their antigenic scores were found to be 1.237 8， 1.105 8 and 0.610 7 respectively. Notably，the immunogenic score of epitope NS52638-2644was found to be signif i cant as compared to other epitopes i.e. 0.417 95.

Table 1T-cell Class I MHC-Specif i c Predicted Epitopes of the Zika virus polyprotein and their number of alleles， antigenicity prediction score and immunogenicity score.

3.2. Prediction of HLA II binding epitopes:

By using ProPred， 48 antigenic epitopes for HLA class II were predicted in the consensus polyprotein sequence of zika virus （Table 2）. Epitopes were found to be conserved among the sequences to a large extent.

Epitope C91-100was predicted to bind to 9 HLA class II alleles andits antigenicity score was found to be signif i cantly high i.e. 0.6639. It was predicted that prM158-166will bind with 22 HLA class II alleles and its antigenicity score was found to be high i.e. 1.606 5. Epitope prM158-166has been identif i ed as an important epitope in the prM region of the consensus sequence.

Table 2T-cell Class II MHC-specif i c predicted epitopes of the Zika virus polyprotein and their number of alleles and antigenicity prediction score.

Seven important promiscuous HLA class II binding epitopes were detected in the envelope of the consensus sequence. E403-411was predicted to bind 25 HLA II alleles and its antigenic score was found to be 1.239 7. It was predicted that E764-772will bind 10 alleles but its antigenic score was signif i cantly high as compared to E403-411i.e. 2.627 7.

NS11004-1012was predicted to bind 21 HLA class II alleles and its antigenic score was found to be 1.0216. NS11124-1132and NS1965-973were predicted to bind 12 and 11 alleles but their antigenic score were found to be 2.435 7 and 1.690 8， respectively.

Seven important promiscuous HLA II binding epitopes were detected in the NS2A of the consensus sequence. It was predicted that NS2A1157-1169will bind 25 HLA II alleles and its antigenic score is 0.630 7. NS2A1241-1249and NS2A1326-1334were predicted to bind 11 and 10 alleles but their antigenic score were found to be 2.763 3 and 2.007 1， comparatively. Out of the seven promiscuous epitopes identif i ed in NS2A region， none was completely conserved among all the polyprotein sequences.

NS2B1383-1391and NS2B1411-1419were predicted to bind 14 and 12 HLA class II alleles but their antigenic score was found to be 0.911 0 and 1.086 6 respectively. Moreover， both epitopes were completely conserved among all the polyprotein sequences included in the study. It was predicted that NS31597-1605and NS31762-1770will bind 34 and 25 HLA class II alleles and their antigenic scores were determined to be 0.539 2 and 0.629 9 respectively. Moreover， both NS31597-1605and NS31762-1770were conserved in all the 54 polyprotein sequences of our study. NS31663-1671and NS32034-2042were predicted to bind 13 and 10 HLA II alleles but their antigenic scores were found to be 1.129 5 and 1.106 5 respectively.

NS4A2185-2200was predicted to bind 23 alleles while its antigenic score was found to be 0.758 7. NS4A2174-2182was predicted to bind to 17 HLA class II alleles while its antigenic score was found to be 1.005 8. Moreover， this epitope was conserved in all the polyproteins included in the study.

NS4B2364-2372was predicted to bind 22 HLA class II alleles and its antigenic score was found to be 1.066 3. NS4B2442-2451was predicted to bind 26 alleles but its antigenic score was less comparatively i.e. 0.538 8.

NS52924-2932and NS52701-2709were predicted to bind 28 and 26 HLA class II alleles and their antigenic scores were determined to be 1.142 8 and 0.750 1， respectively. In comparison， NS53372-3380and NS53238-3246were predicted to bind 12 and 13 alleles while their antigenic scores were found to be 1.527 5 and 1.282 8， respectively. Remarkably， NS52924-2932epitope was found to be conserved among all the 54 polyprotein sequences included in our study.

Moreover it was concluded that none of the epitopes predicted in this study have been studied previously.

4. Discussion

Zika virus is mainly spread by the Aedes aegypti mosquito， and has been lately making its presence known throughout Central America and Latin America， but there are chances that it might spread to tropical and subtropical regions too ［28］. Currently there is no FDA approved vaccine. Even more， there is no specif i c treatment apart from the recommended use of aspirin and acetaminophen to counteract the fever and muscle pain and preventive measures against mosquito bites ［29］.

The Genus Flavivirus consists of diverse and complex group of pathogens which are antigenically related. The genomes of these viruses comprise of total 10 proteins and the role of each of the protein in viral pathogenesis is not yet completely elucidated. Effective immunization treatment for some members exists while due to some immunobiology complexities， vaccines for other members are still to be made. Most of animal models are either immune to Flavivirus or they do not completely represent all manifestations of disease. Some human data of Flavivirus do exist； however， it does not represent all forms of disease and its global variation in populations ［30］.

Epitope based vaccines are already showing hopeful results. This promising vaccine technology has allowed for the prevention and treatment of cancer， viral， bacterial and other diseases ［31-36］. Numerous immune-bioinformatics methods and tools have now been developed to assist in the search for T-cell MHC binding epitopes. Design and development of a vaccine using T cell specif i c epitopes is considerably more favourable because they evoke a longterm immune response and dodge antigenic drift whereas antigen can effortlessly evade the antibody memory response ［21］. Both the CD4+and CD8+T cells have essential role in antiviral immune response as well as clonal expansion of B cell. In this study， we used the full-length polyprotein sequence of the Zika virus in order to increase the coverage of the genome and to search for promiscuous epitopes in both the structural and non-structural proteins of this virus. At the time of writing， no Zika virus T or B-cell epitopes have been uploaded to the Immune Epitope Database Analysis Resource （IEDB）； a manually curated repository of experimentally characterized immune epitopes. The IEDB can be used by scientists to help in the identif i cation， characterization， mapping and evaluation of likely targets for vaccine， therapeutic and diagnostic nominees，and moreover to give us a broader knowledge of the pathogenesis and immunobiology of any new disease or epidemic. The current study is a fi rst attempt which intended to screen novel and highly probable immunogenic epitopes for T cells across all the major proteins of ZIKV. Furthermore， these crucial data can be unif i ed with data from supplementary databases （Pharmacogenomics， genomic，proteomic， or genomic）， in doing so increasing the usefulness and wide-ranging scope of the analyses.

In our study， a greater number of epitopes were projected for MHC class II when compared to MHC class I. The results of this study are in conformity with a meta-analysis study that enumerated a greater number of Class II epitopes in the Flavivirus genus ［37］. Out of 23 identif i ed MHC 1 binding antigenic epitopes， 12 epitopes i.e. E462-470，E640-648，NS11059-1067， NS2A1156-1164， NS2A1355-1363， NS2B1381-1389，NS31622-1630， NS31688-1696， NS32018-2026， NS4A2177-2185， NS4A2220-2238and NS52520-2528， were completely conserved in intact form among all the polyprotein sequences included in the study. Epitope E640-648was predicted to bind to 11 HLA class I alleles and its antigenicity score was signif i cant i.e. 1.033 4. Moreover， its sequence was completely conserved in all the polyprotein sequences included in our study. Hence， E640-648was identif i ed as the best envelope HLA 1 epitope in our study. Epitopes NS32018-2026was predicted to bind 20 HLA Class 1 alleles and its antigenicity score were found out to be 1.135 1. Amazingly， it was found to be completely conserved among all the polyprotein sequences included in our study， indicating that these epitopes can be important for developing universally applicable vaccines. Notably， the immunogenicity score of NS4A2220-2238was found to be the highest （i.e. 0.560 3） among all the HLA class I binding epitopes determined in our study.

Out of 48 predicted HLA II epitopes， 18 epitopes were found to be completely conserved in all of the polyprotein sequences included in the study. These epitopes are C92-99， E470-478， E588-596， NS1878-886， NS1878-891，NS11124-1132， NS2B1383-1391， NS2B1411-1419， NS31597-1605， NS31762-1770，NS32046-2054， NS4A2174-2182， NS4A2229-2240， NS4B2331-2339， NS4B2496-2504，NS52536-2544， NS52750-2758and NS52924-2932. Notably， the antigenic epitope NS31597-1605has been predicted to bind 34 out of 51 HLA class II alleles. Epitope C92-99was predicted to bind to 25 HLA class II alleles and its antigenicity score was found to be significantly high i.e. 1.801 1. Moreover， as discussed， this epitope was found to be completely conserved among all the polyprotein sequences included in our study. This indicates that this epitope can serve as an important part of universally applicable vaccines. NS11124-1132was completely conserved among all the polyprotein sequences，indicating that this epitope can be useful for developing a universally applicable vaccine， especially considering its signif i cant antigenic prediction.

Structures of all ten of fl avivirus genus viral proteins are reported，though complete data of all the 10 proteins for a single virus have not been reported yet. The best overall epitope distribution is available for WNV and DENV （ten out of ten for both） and the highest number of epitopes for the whole genus have been obtained from NS3 and E proteins. The human epitope data collected from the patients of Japanese encephalitis， dengue hemorrhagic fever， dengue fever， yellow fever and West Nile fever indicates the presence of both B-cell and T-cell epitopes. ［37］.

According to a 2010 Meta-analysis study of all immune data in the Flavivirus genus ［37］， 1 200 epitopes were identif i ed in that study and most of the epitopes belonged to the dengue virus group followed by WNV and YFW. The higher percentage of epitopes identif i ed for dengue virus， WNV and YFW indicate their worldwide impact on mortality and morbidity in human population while smaller number of epitopes recognized for other viruses indicates the presence of established prophylaxes or their less dreadful impact on human population. All the epitopes reported up to date are peptidic in nature and there is objectively even scattering of B-cell and T-cell epitopes in the genus as a whole. T-cell epitopes have been recognized in six out of nine Flavivirus and the largest numbers of T-cell epitopes reported are in WNV DENV and YFW. Both CD4 and CD8 epitopes are defined for Flavivirus but it was observed that DENV viruses have predominantly CD8+T-cell epitopes while other viruses （WNV and JEV） mostly have CD4 T-cell epitopes.

Not surprisingly the data on host distribution of epitope reactivity ’s indicates that most of the flavivirus epitopes are def i ned in either humans or mice. A large number of DENV epitopes were def i ned in humans， as expected but surprisingly very low numbers of epitopes for WNV， YFW and complete absence of epitopes for JEV. Speculation is that low number of epitopes for JEV is due to availability of JEV vaccine. Identification of epitopes in NHP still remains of great interest despite the fact that they are quite expensive and have limited availability but they can be used as natural hosts and have biological and immunological similarities with humans ［37， 38］. Due to lack of a suitable animal model， very small numbers of protective epitopes are reported for Flavivirus: DENV， JEV， and TBEV ［37-41］. Many animal models are used to study diverse characteristics of fl avivirus infection but， the standard model used is murine model. Although mice natural resistance to infection caused by certain Flavivirus is problematic as it causes hindrance in measuring protective immunity of animal， Humanized or susceptible mouse models are being developed which can mimic disease symptoms more closely related to humans. However， until then we mostly have to rely on extrapolation of clinical studies ［37， 42］.

A large number of epitopes （both larger and smaller） are identif i ed in humans for the period of the natural course of infection for Dengue， West Nile， and Japanese Encephalitis viruses respectively. However， the numbers of epitopes were higher for DENV ［37］. The contemporary data available is， however， inadequate and cannot provide a solution to the questions related to the immunopathological aspects of these viruses. However， we can extrapolate the epitope fi ndings of other members of the fl avivirus genus to the ZIKV ［43， 44］. One downside of our study is the lack of invitro and invivo studies to test whether these peptidic epitopes will elicit a strong and protective immune response in Humans. Since these epitopes were predicted using an in-silico approach， experimental studies are a must before such epitopes are used in vaccine formulations.

Conflict of interest statement

The author declares that there is no conf l ict of interest.

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10.1016/j.apjtm.2016.07.004

Hamza Dar， Atta-ur-Rahman School of Applied Biosciences （ASAB），National University of Sciences and Technology， Islamabad （44000）， Pakistan.

Tel: +92-311-9212768

Fax: +92-51-90856102

E-mail: darhamza000@gmail.com

✉Corresponding author: Yasir Waheed， PhD， Foundation University Medical College，Foundation University Islamabad， DHA-I Islamabad （44000）， Pakistan.

E-mail: yasir_waheed_199@hotmail.com

Aneela Javed， PhD， Atta-ur-Rahman School of Applied Biosciences （ASAB），National University of Sciences and Technology， Islamabad （44000）， Pakistan.

E-mail:javedaneela@gmail.com