Prediction and Conservancy Analysis of Multiepitope Based PeptideVaccine Against Merkel Cell Polyomavirus: An ImmunoinformaticsApproach

Abstract

Merkel cell Polyomavirus is non-enveloped, dsDNA virus belonging to Polyomaviridae family linked to an uncommon aggressive skin malignancy. The poor prognosis and limited understanding of disease pathogenesis warrants innovative treatment. In this current study we aim to predict TB cell immunogenic epitopes from the VP1 protein of all merkel cell polyomavirus strain which will aid in effective epitope based vaccine design using immuoinformatics approaches. We retrieved 423 full-length VP1 protein sequences of merkel cell polyomaviruse virus species from the NCBI database. These sequences were analyzed to determine the conserved region and were used to predict the epitopes using the IEDB immunoinformatics algorithms. For B cell three epitope were predicted as peptide vaccine (QEKTVY, KTVYPK, and QEKTVYP). For T cell the predicted Class-I peptides (SLFSNLMPK, LQMWEAISV and LLVKGGVEV) were found to cover the maximum number of MHC I alleles. The highest scoring Class II MHC binding peptides were (IELYLNPRM, ISSLINVHY and INSLFSNLM). Further experiments will need to be undertaken to confirm the potential of these predicted epitopes in a future efficacious vaccine development.