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Journal of Virological Methods 177 (2011) 26– 30

Contents lists available at ScienceDirect

Journal of Virological Methods

j ourna l ho me pag e: ww w.elsev ier .com/ locate / jv i romet

dentification of epitopes in Indian human papilloma virus 16 E6: bioinformatics approach

jay Kumar Singha, Srikanta Kumar Rathb, Krishna Misraa,∗

Centre for Biomedical Magnetic Research, SGPGI Campus, Lucknow, IndiaGenotoxicity Laboratory, Toxicology Division, Central Drug Research Institute, Lucknow 226001, India

rticle history:eceived 26 January 2011eceived in revised form 31 May 2011ccepted 7 June 2011vailable online 14 June 2011

eywords:uman papilloma virus 16rotein E6ervical cancer

a b s t r a c t

HPV-16 is reported as the cause of cervical and other related carcinomas. The early expressed proteinE6 in cancer cells is found to be the target for immune therapeutic methods. The sequence of HPV-16 E6(Accession No: ABK32509) from NCBI databank has been taken for this study. Hydrophilicity, flexibility,accessibility, turns, exposed surface, polarity and antigenic propensity scales were used for the B cellepitope prediction. MHC Class I and Class II alleles for the accession were predicted by the MHCPred 2.0Program. The epitope sequences were also found out. Computer-based prediction program results show,A0203 and DRB0101 lower IC50 than other alleles. The best peptide binding affinity was 21HLCTELQTT30of A0203 allele. In DRB0101 allele the peptide found was 39YCKQQLLRR48. Different structural featuresof the protein have also been predicted including glycosylation, kinase C phosphorylation, casein kinase

omputational analysistructure prediction

cell epitopes

II phosphorylation and N-myristylation sites. These computational prediction programs show four glyco-sylation, five kinase C phosphorylation, two casein kinase II phosphorylation, zero N-myristylation sitesand seven disulphide sites. Development and approval of new vaccines are the keys for control of cancer.Epitopes and other structural features of protein prediction could be the best source of information andcan help in molecular and medical studies of viral infection and development of HPV associated cancerdrugs.

. Introduction

Cervical cancer, observed and reported worldwide as the secondost common malignancy in women, is almost invariably associ-

ted with human papilloma virus (HPV) infection (Kaufmann et al.,002; Kanjanavirojkul et al., 2006). In most of the developing coun-ries 25% of the total female cancer patients have cervical cancerHarro et al., 2001).

Human papillomavirus type 16 (HPV-16) has been found to beajor causative factor for the development of cervical carcinomas

Kim et al., 2004). The two major oncogenic proteins E6 and E7 ofPV-16 are consistently expressed in cancer cells and are major

argets for immune therapeutic approaches. It has been found thatPV E6 is responsible for the malignant transformation of HPV-ssociated lesions. Thus, this protein represents an ideal targetor therapeutic HPV vaccine development (Peng et al., 2005). The

arly oncoprotein E6 expression is responsible for the transform-ng ability of the virus (Liu et al., 2002). The previous study wasocused mainly on the immunogenicity of E7 protein, little is known

∗ Corresponding author. Tel.: +91 9415247579; fax: +91 5222668215.E-mail addresses: ajjay2@gmail.com (A.K. Singh), skrath@cdri.res.in (S.K. Rath),

rishnamisra@hotmail.com (K. Misra).

166-0934/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.jviromet.2011.06.006

© 2011 Elsevier B.V. All rights reserved.

presently about E6 (Samorski et al., 2006). The epitopes of IranianHPV 16 E6 protein have been reported (Mohabatkar, 2007). Epitopeidentification by overlapping synthetic peptides is key step for vac-cine development. The present method decreases the possibilitiesof missed epitopes. However, peptides need to be synthesized evenif at high cost. Cell mediated immune responses have also been con-sidered important in the control of HPV infections (Farhat et al.,2009). Immunoinformatics, a new emerging branch of bioinfor-matics, has already become a familiar and useful tool for selectingepitopes from immunologically relevant proteins, as well as for fur-ther development of information about different epitopes. Epitopeprediction with software is cost and labour effective and saves theexpense of synthetic peptides and working time (Bian et al., 2003;Li et al., 2005). The development of an adenoviral vaccine against E6and E7 oncoproteins to prevent growth of human papillomavirushas also been reported (Lee et al., 2008). The antigenic recogni-tion of epitopes by the immune system, either small discrete T-cellepitopes or large conformational epitopes recognized by B cellsand soluble antibodies is the key molecular event of the immuneresponse to pathogenicity (Doytchinova and Flower, 2002).

Although the host effective vaccine development is still to be tar-geted, but recently for this purpose the combination of the fowlpoxvirus and HPV 16 were used for cervical carcinoma in rabbits, whichcan lead to human cancer as well (Radaelli et al., 2010). This study

ological Methods 177 (2011) 26– 30 27

w(aEas(oH

2

2

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Table 1Results through ProtParam for the analysis of residue ratio.

% A: 1.9 % C: 8.9 % D: 5.1 % E: 5.7 % F: 3.2% G: 2.5 % H: 3.2 % I: 5.1 % K: 7.0 % L: 10.1% M: 1.9 % N: 2.5 % P: 4.4 % Q: 7.0 % R: 11.4a

% S: 3.8 % T: 5.7 % V: 3.2 % W: 0.6b % Y: 7.0

A.K. Singh et al. / Journal of Vir

as focused on Indian HPV 16 E6 by computer aided prediction ofA) B cell epitopes, (B) major histocompatibility complexes (MHCs)lleles and (C) post translational modifications of Indian HPV-16 E6.arlier, perfect predictions with accuracy of 100% were not achiev-ble (Hansen et al., 1996). The prediction of protein secondarytructure is an important step in assessment of tertiary structureKim and Park, 2003), and because antigenicity of a protein dependsn its secondary structure, in this study the secondary structure ofPV-16 E6 was also predicted.

. Materials and methods

.1. Amino acid sequence

The sequence of Indian HPV-16 E6 was obtained from NCBI data-ank. The accession number is ABK32509. The isolation source ofhe virus was cervical cancer tissue.

.2. B cell epitope prediction

The criteria for all prediction calculations were based on propen-ity scales for each of the 20 amino acids. The moving window wassed for amino acid sequence of each protein. The normalized com-arative profiles were obtained by different methods, whereas theriginal values of each scale were set between +3 and −3. The B-cellpitope prediction was based on hydrophilicity (Parker et al., 1986),exibility (Karplus and Schulz, 1985), accessibility (Emini et al.,985), turns (Pellequer et al., 1993), exposed surface (Kolaskar andongaonkar, 1990), polarity (Janin and Wodak, 1978) and antigenicropensity (Ponnuswamy et al., 1980).

.3. T cell epitope prediction

For the quantitative prediction of MHC binding peptidesHCPred version 2.0 (Guan et al., 2003, 2006) has been used.

his server is available from the URL: http://www.jenner.ac.uk/HCPred. The program runs as a CGI sever, written in Perl, operat-

ng under Microsoft Windows NT.The sequence of a protein was entered and selections of MHC

lleles and affinity threshold were chosen for the run of program.HCPred covers a range of different human MHC allele pep-

ides specificity models. These analyse Class I alleles (HLA-A*0101,LA-A*0201, HLAA*0202, HLA-A*0203, HLA-A*0206, HLAA*0301,LA-A*1101, HLA-A*3301, HLA5A*6801, HLA-A*6802 and HLA-*3501) and Class II alleles (HLA-DRB*0401, HLADRB*0401 andLADRB*0701).

.4. Prediction of post-translational modifications

Different parameters were used to predict glycosylation, N-yristoylation, protein kinase C phosphorylation, casein kinase

I phosphorylation sites and disulphide sites (Vullo and Frasconi,004; Bairoch et al., 1997; Hubbard and Ivatt, 1981; Bause, 1983).

Fig. 1. Sequence of E6 protein of Indian

a Maximum percentage residue R (arginine).b Minimum percentage residue W (tryptophan).

N-glycosylation sites are identified as Asn-Ø-Thr or Asn-Ø-Sersequences, where Ø is any residue.

2.5. Secondary structure prediction

A scale of secondary structure, which was based on the predic-tion of turns and loops obtained from statistical analysis of proteinsof known structure, was considered for secondary structure predic-tion (Garnier et al., 1978).

3. Results

The amino acid sequence of HPV 16 E6 protein with 158 residuesis shown in Fig. 1. Percentage of different amino acids in this pro-tein was calculated (Table 1). HPV 16 E6 protein sequence consistsof mostly arginine (18 residues), followed by leucine (16 residues)and cysteine (14 residues) respectively. Minimum amino acidswere histidine, phenylalanine, valine followed by alanine, methio-nine and tryptophan. Hydrophilicity, flexibility, accessibility, turns,exposed surface, polarity and antigenic propensity parameterswere used to predict B cell epitopes. The results of B cell epitopeprediction have been shown in Table 2.

Above-mentioned parameters have been correlated with thelocation of continuous epitopes. As a result, 6 regions were pre-dicted to be B-cell epitopes. The shortest epitope was epitopenumber 6 (7 residues), and the longest one was epitope number2 (35 residues) (Table 3). A0101, A0201, A0202, A0203, A0206,A0301, A1101, A3101, A6801, A6802, B3501, DRB0101, DRB0401and DRB0701 were the alleles chosen for this computation anal-ysis. Peptides with the lowest predicted IC50, corresponding tothe best predicted binding affinities are shown in Table 3. Accord-ing to this computer-based prediction the results from A0203 andDRB0101 reveal lower IC50 than other alleles. For A0203 allele, thethree peptides with the best binding affinities are 21HLCTELQTT29(IC50 = 2.81), 25ELQTTIHDI33 (IC50 = 2.88) and 48SSRTRRETL157(IC50 = 4.74), respectively. For DRB0101 allele, the three peptideswith the best binding affinities are 39YCKQQLLRR47 (IC50 = 1.03),99YNKPLCDLL107 (IC50 = 1.07) and 91YGTTLEQQY99 (IC50 = 1.69),respectively.

Results of computer-assisted prediction of the number of gly-cosylation, phosphorylation, myristoylation, and disulphide sites

are shown in Table 4. According to this analysis no asparagineswere predicted to be glycosylated. However, number of glycosy-lated residues was four. Results have also predicted five residuesas kinase C phosphorylated, two residues as casein kinase II phos-

human papillomavirus type 16.

28 A.K. Singh et al. / Journal of Virological Methods 177 (2011) 26– 30

Table 2Prediction of B-cell epitope by Kolaskar and Tongaonkar antigenicity method through IEDB (Immuno Epitope Database Analysis Resources).

No. Start position End position Peptide Peptide length

1 18 26 KLPHLCTEL 92 28 62 TTIHDIILECVYCKQQLLRREVYDFAFRDLCIVYR 35a

3 66 80 PYAVCDKCLKFYSKI 154 82 93 EYRYYCYSVYGT 125 100 120 NKPLCDLLIRCINCQKPLCPE 216 143 149 CMSCCRS 7b

a Largest peptide.b Smallest peptide.

Table 3Peptides of Indian HPV-16 E6 with the best predicted binding affinity for each allele.

S. no. Alleles Amino acid groups Predicted IC50 (nM) Confidence of prediction (Max = 1)

1 A0101 82YRYYCYSVY91 45.81 12 A0201 89YNKPLCDLL98 38.9 0.893 A0202 10DPQERPRKL19 25.35 0.674 A0203 21HLCTELQTT30 2.81 0.895 A0206 37KQQLLRREV46 8.22 0.896 A0301 99LIRCINCQK107 25.41 0.897 A1101 93TTLEQQYNK101 8.32 18 A3101 105PLCPEEKQR113 83.75 0.679 A6801 49FAFRDLCIV57 6.89 0.56

10 A6802 29TTIHDIILE37 11.19 0.6711 B3501 49FAFRDLCIV57 177.83a 112 DRB0101 39YCKQQLLRR47 1.03b 0.8913 DRB0401 38VYCKQQLLR46 74.99 0.7814 DRB0701 37KQQLLRREV46 15.38 1

a Highest IC50 (nm) value.b Lowest IC50 (nm) value.

Table 4Molecular characterization of Indian HPV-16 E6.

Character Gly sites PKC sites CK2 site Myr sitesb Dis sitea

Number 4 5 2 0 7

pptNoM

rta

4

ttsHn

TP

a Highest no. of disulphide bond.b Lowest no. of myristylation site.

horylated and seven residues as disulphide sites and none wasredicted to be myristoylated. This computational study predictedhat Threonine was kinase C phosphorylated (site number 140).one of the putative epitopes were predicted to be myristoylatedr glycosylated. This computational study predicted that neitherHC-I nor MHC-II epitopes were myristoylated.The result of this analyses for Indian HPV-16 E6 predicts that 73

egions are a-helix and 7 regions are b-turns (Table 5). Accordingo this analysis 46.20%, 4.43% and 32.28% of the protein was in the-helix, b-turns and random coil forms respectively.

. Discussion

The investigation was targeted to apply bioinformatics approacho the study of B and T cell epitopic sites, mainly the B cell epi-

ope due to its major significance in the HPV infections. Some othertructural properties of Indian HPV-16 E6 have also been studied.PV-16 is the most frequently associated virus with cervical carci-oma in humans. E6 and E7 oncoproteins appears to be good targets

able 5redictions of secondary structure and accessibility type of Indian HPV-16 E6.

No. of alpha helix No. of beta turns Alpha helixa Stran

73 7 46.20 17.09

a Percentage Value of different secondary structure and accessibility in Indian HPV 16E

for vaccine-induced cytotoxic T lymphocytes (Bourgault Villadaet al., 2000) for the treatment and prevention of carcinoma.

PKC sites are the number of protein kinase C phosphorylationsites, CK2 sites are the number of casein kinase II phosphorylationsites, Myr sites are the number of N-myristoylation sites. HPV vari-ants are also an important factor (Giannoudis and Herrington, 2001)in the development of cervical neoplasia. These differ in biolog-ical and chemical properties and pathogenicity (Conrad-Stöppleret al., 1996; Veress et al., 1999). Geographical and ethnic ori-gin of population is affected by the specificity of oncogenic HPVvariants. Intratypic sequence variation has been found in the E2,E4, E5, E6, and E7 genes of HPV-16, and this variation can be offunctional significance. Screening strategies, effective therapeuticand preventive vaccines are also developing that have the poten-tial to contribute significantly to the control and prevention ofcervical cancer (Burd, 2003). There is no experimentally deter-mined structural information, specifically, regarding Indian HPV-16E6, therefore the present investigation has been conducted. Anti-genic determinants lie in regions, which are hydrophilic, exposedand polar. Accessibility and flexibility of these segments are highin protein. This has led to the rules that would allow the posi-tion of B-cell epitopes to be predicted from these features of theprotein sequence (Pellequer et al., 1991; Mohabatkar and Kar,

2004). Cell-mediated immune response needed to be understoodfor the structural and immunological basis for the formulationof therapeutic vaccines (Sarkar et al., 2005). Although the accu-rate bioinformatics prediction of T-cell epitopes can to a great

da Turnsa Coilsa Accessibility typea

Buried Exposed

4.43 32.28 48.10 51.89

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A.K. Singh et al. / Journal of Vir

xtent reduce the experimental cost in candidate epitope identi-cation, however in the present case B-cell epitope was studiedue to its enhanced significance. In the present study MHCPredrogram has been used to predict MHC Class I and Class II alle-

es of Indian HPV 16 E6, and it gives information to design newxperiments (Chen et al., 2006). A number of studies show theffects of modifications of amino acid residues on the functionsf proteins. For example, in Alzheimer disease, through studyf effects of phosphorylation of epitopes investigators found outhat epitopes require the phosphorylation of some residues toe effective (Goedert et al., 1994). This computational study pre-icted that best binding affinity of alleles can be 12 and 4. Oneesearch group on breast cancer (Schuman et al., 2003) has dis-ussed about the possible roles that peptide epitope secondarytructure and glycosylation state may play in mucin tumormmunogenicity.

In proteins, turns are found on the surface; these parts are acces-ible and hydrophilic. In contrast, the core is mostly devoid of waterolecules (Pellequer et al., 1991). In case of herpes simplex virus

ype I, it has been shown that the secondary structure is impor-ant to antibody binding and even a minor modification of theecondary structure can affect the immune identification of anti-ens (Schlosser et al., 2003). Like any other protein, prediction ofecondary structure of Indian HPV-16 E6 can provide us importantnformation about the interactions and functions of this protein.ince the residue composition of any protein is important, in theresent investigation the residue composition for Indian HPV-16 E6rotein has been calculated. Earlier epitope prediction by MHCPredas reported in Iranian HPV16 E6 (Mohabatkar, 2007). In one of therevious studies on HPV-6 E7, it was shown that single amino acidubstitutions in lowrisk – HPV enhanced features of the high-riskPV E7 oncoproteins (Sang and Barbosa, 1992).

In conclusion it can be said that identification of epitopes isrucial in understanding the rules of B and T cell activation andesigning of synthetic vaccines. Identification of these epitopesas paved a way towards cancer immunotherapy and identifica-ion of many other infectious diseases. These kinds of studies canelp in developing experimental methodologies, by avoiding non-

unctional sequences.

cknowledgements

One of the author (AKS) gratefully acknowledges CBMR,GPGIMS campus, Lucknow, India and CDRI, Lucknow, India forroviding facilities to carry out this work.

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