Prediction of Promiscuous Epitopes in the E6 Protein of Three High Risk Human Papilloma Viruses: A Computational Approach

Subramanian Nirmala,Chinnappan Sudandiradoss

doi:10.7314/apjcp.2013.14.7.4167

Subramanian Nirmala, Chinnappan Sudandiradoss

Open Access

https://doi.org/10.7314/apjcp.2013.14.7.4167

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Abstract

A najor current challenge and constraint in cervical cancer research is the development of vaccines against human papilloma virus (HPV) epitopes. Although many studies are done on epitope identification on HPVs, no computational work has been carried out for high risk forms which are considered to cause cervical cancer. Of all the high risk HPVs, HPV 16, HPV 18 and HPV 45 are responsible for 94% of cervical cancers in women worldwide. In this work, we computationally predicted the promiscuous epitopes among the E6 proteins of high risk HPVs. We identified the conserved residues, HLA class I, HLA class II and B-cell epitopes along with their corresponding secondary structure conformations. We used extremely precise bioinformatics tools like ClustalW2, MAPPP, NetMHC, EpiJen, EpiTop 1.0, ABCpred, BCpred and PSIPred for achieving this task. Our study identified specific regions 'FAFR(K)DL' followed by 'KLPD(Q)LCTEL' fragments which proved to be promiscuous epitopes present in both human leukocyte antigen (HLA) class I, class II molecules and B cells as well. These fragments also follow every suitable character to be considered as promiscuous epitopes with supporting evidences of previously reported experimental results. Thus, we conclude that these regions should be considered as the important for design of specific therapeutic vaccines for cervical cancer.

Highlights

500,000 women worldwide develop cervical cancer and it is the most common cancer among women in underdeveloped countries (Soliman et al, 2004) with 274,000 deaths each year due to this disease
A najor current challenge and constraint in cervical cancer research is the development of vaccines against KXPDQ SDSLOORPD YLUXV +39 HSLWRSHV$OWKRXJK PDQ\ VWXGLHV DUH GRQH RQ HSLWRSH LGHQWLÀFDWLRQ RQ +39V
We followed Unweighted Pair of Group Method with Arithmetic Mean (UPGMA) (Khan et al, 2008) which is embedded in MEGA4 (Koichiro et al, 2007) program for calculating the evolutionary distance. This program evaluates the evolutionary distance by following the Maximum Composite Likelihood (MCL) feature (Khan et al, 2008) and provides the evolutionary distance for all pairs of sequences simultaneously. By following this MCL feature, we reduced the errors obtained by the Independent Estimation (IE) (Whelan et al, 2001) approach considerably and reported the phylogenics with more accuracy (Koichiro et al, 2007)

Summary

Introduction

500,000 women worldwide develop cervical cancer and it is the most common cancer among women in underdeveloped countries (Soliman et al, 2004) with 274,000 deaths each year due to this disease. HPV infection is known to be one of the important causes for the development of cervical cancer in women, which forms a major risk factor for the development of anal, penile, and vulvar FDQFHUV3DSLOORPD9LUXVHVDUHQRWFODVVLÀHGE\VHURW\SH but by genotype, and to date, approximately 151 HPV W\SHV KDYH EHHQ LGHQWLÀHG LQ KXPDQV DORQH %HUQDUG HW al., 2010) with a circular genome of approximately 8 kbp. It is expected that the JHQHUDWLRQ RI FHUYL[ FDQFHU YDFFLQHV ZLOO VSHFLÀFDOO\ include each of the eight HPV types. Of these the most common high-risk subtypes of HPV are 16, 18, and 45. Bioinformatics Division, School of Biosciences and Technology, VIT University, Vellore, India *For correspondence: csudandiradoss@ vit.ac.in

Subramanian Nirmala and Chinnappan Sudandiradoss

Prediction of HLA class

LTEVFEFAFKDLFVVYRDS PYKLPDLCTELNTSLQDIEI

Findings

Integrating in silico and in vitro analysis of peptide binding