title: Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR) binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1.
  
  
  CONCLUSIONS
  A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology.
authors: The Jenner Institute, University of Oxford, Compton, Berkshire, United Kingdom.
authors: Valerie A
authors: VA
authors: Walshe
authors: Channa K
authors: CK
authors: Hattotuwagama
authors: Irini A
authors: IA
authors: Doytchinova
authors: Mailee
authors: M
authors: Wong
authors: Isabel K
authors: IK
authors: Macdonald
authors: Arend
authors: A
authors: Mulder
authors: Frans H J
authors: FH
authors: Claas
authors: Pierre
authors: P
authors: Pellegrino
authors: Jo
authors: J
authors: Turner
authors: Ian
authors: I
authors: Williams
authors: Emma L
authors: EL
authors: Turnbull
authors: Persephone
authors: P
authors: Borrow
authors: Darren R
authors: DR
authors: Flower
mesh_terms: D000483:Alleles; D020816:Amino Acid Motifs; D019295:Computational Biology / Q000379:methods*; D004492:Edetic Acid / Q000737:chemistry; D000939:Epitopes / Q000737:chemistry*; D015497:HIV-1 / Q000378:metabolism; D015236:HLA-C Antigens / Q000737:chemistry*; D015395:Histocompatibility Antigens Class I / Q000737:chemistry; D006801:Humans; D066298:In Vitro Techniques; D007963:Leukocytes, Mononuclear / Q000378:metabolism; D008285:Major Histocompatibility Complex; D015233:Models, Statistical; D010455:Peptides / Q000737:chemistry*; D011485:Protein Binding; D017434:Protein Structure, Tertiary
chemical_list: D000939:Epitopes; D015236:HLA-C Antigens; C403228:HLA-C*01:02 antigen; D015395:Histocompatibility Antigens Class I; D010455:Peptides; D004492:Edetic Acid