HLA Class I Supertype Classification Based on Structural Similarity

被引:9
作者
Shen, Yue [1 ]
Parks, Jerry M. [2 ]
Smith, Jeremy C. [1 ,3 ,4 ]
机构
[1] Univ Tennessee, Grad Sch Genome Sci & Technol, UT ORNL, Knoxville, TN USA
[2] Oak Ridge Natl Lab, Biosci Div, Oak Ridge, TN USA
[3] Univ Tennessee, Dept Biochem & Cellular & Mol Biol, Knoxville, TN USA
[4] Oak Ridge Natl Lab, Ctr Mol Biophys, POB 2008, Oak Ridge, TN 37831 USA
关键词
MHC CLASS-I; T-CELL EPITOPES; PEPTIDE-BINDING; ANTIGEN PRESENTATION; PROTEIN HLA-DR1; IDENTIFICATION; COMPLEX; DEFINITION; ALLELES; SPECIFICITY;
D O I
10.4049/jimmunol.2200685
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
HLA class I proteins, a critical component in adaptive immunity, bind and present intracellular Ags to CD8+ T cells. The extreme polymorphism of HLA genes and associated peptide binding specificities leads to challenges in various endeavors, including neoantigen vaccine development, disease association studies, and HLA typing. Supertype classification, defined by clustering functionally similar HLA alleles, has proven helpful in reducing the complexity of distinguishing alleles. However, determining supertypes via experiments is impractical, and current in silico classification methods exhibit limitations in stability and functional relevance. In this study, by incorporating three-dimensional structures we present a method for classifying HLA class I molecules with improved breadth, accuracy, stability, and flexibility. Critical for these advances is our finding that structural similarity highly correlates with peptide binding specificity. The new classification should be broadly useful in peptide-based vaccine development and HLA-disease association studies. The Journal of Immunology, 2023, 210: 103-114.
引用
收藏
页码:103 / 114
页数:13
相关论文
共 107 条
  • [1] Comparing Single-SNP, Multi-SNP, and Haplotype-Based Approaches in Association Studies for Major Traits in Barley
    Abed, Amino
    Belzile, Francois
    [J]. PLANT GENOME, 2019, 12 (03):
  • [2] The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design
    Alford, Rebecca F.
    Leaver-Fay, Andrew
    Jeliazkov, Jeliazko R.
    O'Meara, Matthew J.
    DiMaio, Frank P.
    Park, Hahnbeom
    Shapovalov, Maxim V.
    Renfrew, P. Douglas
    Mulligan, Vikram K.
    Kappel, Kalli
    Labonte, Jason W.
    Pacella, Michael S.
    Bonneau, Richard
    Bradley, Philip
    Dunbrack, Roland L., Jr.
    Das, Rhiju
    Baker, David
    Kuhlman, Brian
    Kortemme, Tanja
    Gray, Jeffrey J.
    [J]. JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2017, 13 (06) : 3031 - 3048
  • [3] Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide-MHC Binding Predictions
    Aranha, Michelle P.
    Jewel, Yead S. M.
    Beckman, Robert A.
    Weiner, Louis M.
    Mitchell, Julie C.
    Parks, Jerry M.
    Smith, Jeremy C.
    [J]. JOURNAL OF IMMUNOLOGY, 2020, 205 (07) : 1962 - +
  • [4] HLA Heterozygote Advantage against HIV-1 Is Driven by Quantitative and Qualitative Differences in HLA Allele-Specific Peptide Presentation
    Arora, Jatin
    Pierini, Federica
    McLaren, Paul J.
    Carrington, Mary
    Fellay, Jacques
    Lenz, Tobias L.
    [J]. MOLECULAR BIOLOGY AND EVOLUTION, 2020, 37 (03) : 639 - 650
  • [5] The inter-locus recombinant HLA-B*4601 has high selectivity in peptide binding and functions characteristic of HLA-C
    Barber, LD
    Percival, L
    Valiante, NM
    Chen, L
    Lee, C
    Gumperz, JE
    Phillips, JH
    Lanier, LL
    Bigge, JC
    Parekh, RB
    Parham, P
    [J]. JOURNAL OF EXPERIMENTAL MEDICINE, 1996, 184 (02) : 735 - 740
  • [6] Antigen presentation - Advantages to being different
    Bird, L
    [J]. NATURE REVIEWS IMMUNOLOGY, 2004, 4 (08) : 577 - 577
  • [7] Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC-Peptide Binding Data Set
    Bonsack, Maria
    Hoppe, Stephanie
    Winter, Jan
    Tichy, Diana
    Zeller, Christine
    Kuepper, Marius D.
    Schitter, Eva C.
    Blatnik, Renata
    Riemer, Angelika B.
    [J]. CANCER IMMUNOLOGY RESEARCH, 2019, 7 (05) : 719 - 736
  • [8] Predicting population coverage of T-cell epitope-based diagnostics and vaccines
    Bui, Huynh-Hoa
    Sidney, John
    Dinh, Kenny
    Southwood, Scott
    Newman, Mark J.
    Sette, Alessandro
    [J]. BMC BIOINFORMATICS, 2006, 7 (1)
  • [9] A geometric study of the amino acid sequence of class I HLA molecules
    Cano, P
    Bo, F
    Stass, S
    [J]. IMMUNOGENETICS, 1998, 48 (05) : 324 - 334
  • [10] Carlsson G, 2010, J MACH LEARN RES, V11, P1425