Immunoinformatics Aided Prediction of Cytotoxic T Cell Epitope of Respiratory Syncytial Virus

Authors

  • Md Nur Ahad Shah Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh
  • Payal Barua Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh
  • Md Kawsar Khan Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh

Keywords:

epitope based vaccine, RSV-F protein, CTL epitope, human respiratory syncytial virus, immunoinformatics

Abstract

The Respiratory Syncytial Virus (RSV) poses the threat of lower respiratory tract infection to the infants as well as elderlies. As there is no licensed vaccine, alternative vaccine candidates like Epitope-based vaccines can be considered as a potential candidate. Being conserved among strains and reported to elicit cytotoxic T cell (CTL) response, the fusion glycoprotein of RSV (RSV-FP) is a first-rate target for epitope based vaccine designing. As RSV specific CD8+ CTLs are the central cell of viral clearance, the epitopes capable to generate CTL response are desirable. In this study, available immunoinformatics tools are utilized with a target to predict epitopes on the RSV-FP that elicit strong (CTL) responses. We report seven nine-mer peptides that bind strongly with 17 different HLA, have 100% sequence conservancy and is projected to provide 76.03% population coverage worldwide.

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Published

28-07-2022

How to Cite

Shah, M. N. A., Barua, P., & Khan, M. K. (2022). Immunoinformatics Aided Prediction of Cytotoxic T Cell Epitope of Respiratory Syncytial Virus. Bioresearch Communications - (BRC), 1(2), 99–104. Retrieved from https://www.bioresearchcommunications.com/index.php/brc/article/view/157

Issue

Vol. 1 No. 2 (2015)

Section

Original Article

License

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