Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes

Valerie A. Walshe, Channa K. Hattotuwagama, Irini A. Doytchinova, MaiLee Wong, Isabel K. Macdonald, Arend Mulder, Frans H.J. Claas, Pierre Pellegrino, Jo Turner, Ian Williams, Emma L. Turnbull, Persephone Borrow, Darren R Flower

Research output: Contribution to journalArticle

Abstract

Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.
Original languageEnglish
Article numbere8095
Number of pages11
JournalPLoS ONE
Volume4
Issue number11
DOIs
Publication statusPublished - 2009

Bibliographical note

© 2009 Walshe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Keywords

  • alleles
  • amino acid motifs
  • computational biology
  • edetic acid
  • epitopes
  • HIV-1
  • HLA-C antigens
  • histocompatibility antigens class I
  • humans
  • mononuclear leukocytes
  • major histocompatibility complex
  • statistical models
  • peptides
  • protein binding
  • tertiary protein structure

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  • Cite this

    Walshe, V. A., Hattotuwagama, C. K., Doytchinova, I. A., Wong, M., Macdonald, I. K., Mulder, A., Claas, F. H. J., Pellegrino, P., Turner, J., Williams, I., Turnbull, E. L., Borrow, P., & Flower, D. R. (2009). Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes. PLoS ONE, 4(11), [e8095]. https://doi.org/10.1371/journal.pone.0008095