Elsevier

Human Immunology

Volume 68, Issue 1, January 2007, Pages 12-25
Human Immunology

HLAMatchmaker: A Molecularly Based Algorithm for Histocompatibility Determination. V. Eplet Matching for HLA-DR, HLA-DQ, and HLA-DP

https://doi.org/10.1016/j.humimm.2006.10.003Get rights and content

Abstract

This report describes the design of the eplet version of HLAMatchmaker to determine class II compatibility at the structural level. This matching algorithm is based on the hypothesis, developed from molecular modeling of crystallized antigen-antibody complexes, that functional epitopes are represented by patches of surface-exposed nonself-amino acid residues surrounded by residues within a 3-Å radius. Patch determinations with a molecular viewer of crystalline structural models downloaded from the Entrez Molecular Modeling Database Web site led to the identification of 44 DRB, 33DQB, 29 DQA, 20 DPB, and 9 DPA unique combinations of polymorphic positions. The residue compositions of these patches were then determined from amino acid sequences. This analysis resulted in a repertoire of 146 DRB, 74 DQB, 58 DQA, 45 DPB, and 19 DPA eplets. In many eplets, the residues are in short linear sequences, but many other eplets have discontinuous sequences of residues that cluster on or near the molecular surface. This analysis has also shown that all serologically defined DR and DQ antigens detectable by monospecific antibodies have unique eplets. Other eplets are present in groups of class II antigens, many of which appear as cross-reacting. The eplet version of HLAMatchmaker should be considered as a hypothetical model for the structural assessment of donor-recipient compatibility and the determination of mismatch acceptability for sensitized patients. This computer algorith can be downloaded from the HLA Matchmaker Webside at http://tpis.upmc.edu.

Introduction

Class II human leukocyte antigens (HLA) play an important role in determining donor-recipient compatibility in solid organ and stem cell transplantation. Class II mismatching elicits strong alloimmune responses that impair transplant success. Preformed donor-specific anti-class II antibodies increase the risk of transplant failure [1, 2, 3, 4, 5], and the posttransplant development of anti-class II antibodies is associated with a higher incidence of acute and chronic rejection [6, 7].

Current class II matching strategies in kidney transplantation consider only the serologically defined HLA-DR antigens controlled by the DRB1 locus, although mismatching for HLA-DQ and HLA-DP appears associated with lower graft survivals [8, 9, 10, 11, 12, 13] and the development of clinically relevant alloantibodies in transplant recipients [14]. Moreover, molecular typing has revealed a high degree of heterogeneity of HLA-DR antigens. Newer serum screening methods, such as enzyme-linked immunosorbent assay, flow cytometry, and Luminex, have greatly enhanced the detection and specificity analysis of anti-class II antibodies in sensitized patients.

The evaluation of HLA compatibility and the characterization of anti-HLA antibodies require a better understanding of the HLA epitope repertoire. HLAMatchmaker is a structurally based matching program that considers each HLA antigen as a string of epitopes represented by short sequences (originally referred to as triplets) involving polymorphic amino acid residues in antibody-accessible positions [15]. HLAMatchmaker determines which triplets are different between donor and recipient, and this algorithm is clinically useful for matching purposes [16, 17, 18, 19, 20] and in determining HLA mismatch acceptability for sensitized patients [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]. Although many triplets correspond to serologically defined private and public epitopes, they provide an incomplete description of the HLA epitope repertoire.

A recent study has led to a new version of HLAMatchmaker that considers the hypothesis, developed from molecular modeling of crystallized antigen-antibody complexes, that functional epitopes are represented by patches of surface-exposed nonself-amino acid residues surrounded by residues within a 3-Å radius [32]. These patches are referred to as “eplets,” and many of them are short linear sequences common to triplets, but others have residues in discontinuous sequence positions that cluster together on the molecular surface. The eplet version of HLAMatchmaker therefore considers a more complete repertoire of structurally defined epitopes.

This report describes how eplets are assigned in determining HLA-DR, -DQ, and -DP compatibility at the humoral immune level. This analysis considers 4-digit alleles encoded by not only DRB1 and DQB1, but also DRB3, DRB4, DRB5, DQA1, DPA1, and DPB1, because all of them have antigenic determinants that can induce specific antibodies. This paper will show how eplets correspond to serologically defined class II antigens and how the eplet version of HLAMatchmaker can be used to determine structurally based class II compatibility at the humoral immune level.

Section snippets

Topography of Polymorphic Amino Acid Residues

The construction of the eplet repertoire is based on polymorphic amino acid residues on the HLA molecular surface. Their locations are easily determined with three-dimensional models of class II molecules. The Entrez Molecular Modeling Database of the National Center for Biotechnology Information stores on its Web site (http://www.ncbi.nlm.nih.gov/Structure) an extensive collection of crystallographic structures of HLA molecules that can be viewed with the Cn3D structure and sequence alignment

Discussion

This report describes the design of the eplet-based class II version of HLAMatchmaker and how this algorithm can be used to determine structural compatibility for antigens encoded by HLA-DR, HLA-DQ, and HLA-DP. For each of these loci, an eplet repertoire has been developed from patches of residues within a 3-Å radius of each polymorphic residue exposed on the molecular surface. In many eplets, the residues are in short linear sequences, but many other eplets have discontinuous sequences of

Acknowledgment

This study is supported by grant AI-55933 from the National Institutes of Health.

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