In Silico Identification of Supertypes for Class II MHCs

Abstract

The development of epitope-based vaccines, which have wide population coverage, is greatly complicated by MHC polymorphism. The grouping of alleles into supertypes, on the basis of common structural and functional features, addresses this problem directly. In the present study we applied a combined bioinformatics approach, based on analysis of both protein sequence and structure, to identify similarities in the peptide binding sites of 2225 human class II MHC molecules, and thus define supertypes and supertype fingerprints. Two chemometric techniques were used: hierarchical clustering using three-dimensional Comparative Similarity Indices Analysis fields and nonhierarchical k-means clustering using sequence-based z-descriptors. An average consensus of 84% was achieved, i.e., 1872 of 2225 class II molecules were classified in the same supertype by both techniques. Twelve class II supertypes were defined: five DRs, three DQs, and four DPs. The HLA class II supertypes and their fingerprints given in parenthesis are DR1 (Trp9β), DR3 (Glu9β, Gln70β, and Gln/Arg74β), DR4 (Glu9β, Gln/Arg70β, and Glu/Ala74β), DR5 (Glu9β, Asp70β), and DR9 (Lys/Gln9β); DQ1 (Ala/Gly86β), DQ2 (Glu86β, Lys71β), and DQ3 (Glu86β, Thr/Asp71β); DPw1 (Asp84β and Lys69β), DPw2 (Gly/Val84β and Glu69β), DPw4 (Gly/Val84β and Lys69β), and DPw6 (Asp84β and Glu69β). Apart from the good agreement between known binding motifs and our classification, several new supertypes, and corresponding thematic binding motifs, were also defined.

Identification of Functional and Expression Polymorphisms Associated With Risk for Antineutrophil Cytoplasmic Autoantibody–Associated Vasculitis

“…To confirm the haplotypic relatedness of the 3 variants, we sequenced this region in 100 study subjects who were homozygous for the rs141530233 and rs1042169 markers. Our findings confirmed the organization of the 3 variants in 2 haplotype blocks (as shown in Supplementary Figure 6), which is consistent with the findings in prior studies of a dimorphic polymorphism (GGPM versus DEAV) at the corresponding amino acid positions 84–87 of the HLA–DPB chain 22, 26, 27.…”

HLA-associated susceptibility to childhood B-cell precursor ALL: definition and role of HLA-DPB1 supertypes

“…We designated the six supertypes by their position 11-69-84 residues as GEG, GKG, LED, LKD, GED, and GKD, corresponding to dimorphisms in the P6-P4-P1 peptide-binding pockets. Using a modification of the hierarchical supertype clustering system for DP alleles developed by Doytchinova and Flower (2005), we have provisionally called these supertypes DP1 (GKD), DP2 (GEG), DP3 (LKD), DP4 (GKG), DP6 (LED), and DP8 (GED).…”

“…Since different alleles can have overlapping peptide-binding properties, depending on the number of PBP that they share (Southwood et al, 1998), this has permitted DR alleles with the same amino acid polymorphisms lining specific peptidebinding pockets to be clustered into supertypes Southwood et al, 1998;Doytchinova and Flower, 2005). Using a similar approach, Castelli et al (2002) defined three DP supertype clusters with shared amino acid residues in the P1 (b84) and P6 (b11) PBP.…”

HLA‐DP2 binding prediction by molecular dynamics simulations

“…[33][34][35] Originally, this position was not considered as an anchor for DP2 binding 14 but its inclusion as an anchors QM improves the predictions. Hydrophobic amino acids, such as Trp, Tyr, and Phe, are well tolerated at position p7.…”

“…As such models are indeed available for almost all MHCs via homology modelling, 35,38 virtual screening should in turn prove to be a powerful and highly efficient in silico approach to the identification of potentially immunogenic epitopes suitable for inclusion in diagnostics, reagents, and poly-epitope vaccines. Our approach allows us to combine the speed of QM approaches with that most desirable quality of MD: that 100s of experimentally determined binding measurements are not requitred, with all the logistic benefits that affords.…”