title: Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes.
abstract: The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.
authors.affiliation: Edward Jenner Institute for Vaccine Research-Compton, High Street, Berkshire, Compton RG20 7NN, United Kingdom.
authors.forename: Irini A
authors.initials: IA
authors.lastname: Doytchinova
authors.forename: Valerie A
authors.initials: VA
authors.lastname: Walshe
authors.forename: Nicola A
authors.initials: NA
authors.lastname: Jones
authors.forename: Simone E
authors.initials: SE
authors.lastname: Gloster
authors.forename: Persephone
authors.initials: P
authors.lastname: Borrow
authors.forename: Darren R
authors.initials: DR
authors.lastname: Flower
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods; D015195:Drug Design; D018604:Epitope Mapping; D015234:HLA-A Antigens / Q000378:metabolism*; D015789:HLA-A2 Antigen; D006649:Histocompatibility Antigens / Q000378:metabolism*; D006801:Humans; D009842:Oligopeptides / Q000378:metabolism*; D010455:Peptides; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D013329:Structure-Activity Relationship
chemical_list: D015234:HLA-A Antigens; C435939:HLA-A*02:01 antigen; D015789:HLA-A2 Antigen; D006649:Histocompatibility Antigens; D009842:Oligopeptides; D010455:Peptides