Abstract
T-cell receptor (TCR) binding to peptide/MHC determines specificity and initiates signaling in antigen-specific cellular immune responses. Structures of TCR–pMHC complexes have provided enormous insight to cellular immune functions, permitted a rational understanding of processes such as pathogen escape, and led to the development of novel approaches for the design of vaccines and other therapeutics. As production, crystallization, and structure determination of TCR–pMHC complexes can be challenging, there is considerable interest in modeling new complexes. Here we describe a rapid approach to TCR–pMHC modeling that takes advantage of structural features conserved in known complexes, such as the restricted TCR binding site and the generally conserved diagonal docking mode. The approach relies on the powerful Rosetta suite and is implemented using the PyRosetta scripting environment. We show how the approach can recapitulate changes in TCR binding angles and other structural details, and highlight areas where careful evaluation of parameters is needed and alternative choices might be made. As TCRs are highly sensitive to subtle structural perturbations, there is room for improvement. Our method nonetheless generates high-quality models that can be foundational for structure-based hypotheses regarding TCR recognition.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Garboczi DN, Ghosh P, Utz U et al (1996) Structure of the complex between human T-cell receptor, viral peptide and HLA-A2. Nature 384:134–141
Garcia KC, Degano M, Stanfield RL et al (1996) An alphabeta T cell receptor structure at 2.5 A and its orientation in the TCR-MHC complex [see comments]. Science 274:209–219
Borbulevych OY, Piepenbrink KH, Baker BM (2011) Conformational melding permits a conserved binding geometry in TCR recognition of foreign and self molecular mimics. J Immunol 186:2950–2958
Cole DK, Yuan F, Rizkallah PJ et al (2009) Germline-governed recognition of a cancer epitope by an immunodominant human T-cell receptor. J Biol Chem 284:27281–27289
Macdonald WA, Chen Z, Gras S et al (2009) T cell allorecognition via molecular mimicry. Immunity 31:897–908
Adams JJ, Narayanan S, Liu B et al (2011) T cell receptor signaling is limited by docking geometry to peptide-major histocompatibility complex. Immunity 35:681–693
Bulek AM, Cole DK, Skowera A et al (2012) Structural basis for the killing of human beta cells by CD8+ T cells in type 1 diabetes. Nat Immunol 13:283–289
Chen J-L, Stewart-Jones G, Bossi G et al (2005) Structural and kinetic basis for heightened immunogenicity of T cell vaccines. J Exp Med 201:1243–1255
Restifo NP, Dudley ME, Rosenberg SA (2012) Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol 12:269–281
Oates J, Jakobsen BK (2013) ImmTACs: novel bi-specific agents for targeted cancer therapy. Oncoimmunology 2:e22891
Van Boxel GI, Stewart-Jones G, Holmes S et al (2009) Some lessons from the systematic production and structural analysis of soluble αβ T-cell receptors. J Immunol Methods 350:14–21
Bulek AM, Madura F, Fuller A et al (2012) TCR/pMHC optimized protein crystallization screen. J Immunol Methods 382:203–210
Cole DK, Pumphrey NJ, Boulter JM et al (2007) Human TCR-binding affinity is governed by MHC class restriction. J Immunol 178:5727–5734
Davis MM, Boniface JJ, Reich Z et al (1998) Ligand recognition by alpha beta T cell receptors. Annu Rev Immunol 16:523–544
Pierce BG, Weng Z (2013) A flexible docking approach for prediction of T cell receptor–peptide–MHC complexes. Protein Sci 22:35–46
Pierce BG, Vreven T, Weng Z (2014) Modeling T cell receptor recognition of CD1-lipid and MR1-metabolite complexes. BMC Bioinformatics 15:319
Xia Z, Chen H, Kang S-G et al (2014) The complex and specific pMHC interactions with diverse HIV-1 TCR clonotypes reveal a structural basis for alterations in CTL function. Sci Rep 4:4087
Michielin O, Luescher I, Karplus M (2000) Modeling of the TCR-MHC-peptide complex1. J Mol Biol 300:1205–1235
De Rosa MC, Giardina B, Bianchi C et al (2010) Modeling the ternary complex TCR-Vβ/collagenII(261–273)/HLA-DR4 associated with rheumatoid arthritis. PLoS One 5:e11550
Liu IH, Lo YS, Yang JM (2013) Genome-wide structural modelling of TCR-pMHC interactions. BMC Genomics 14(Suppl 5):S5
Leimgruber A, Ferber M, Irving M et al (2011) TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires. PLoS One 6:e26301
Klausen MS, Anderson MV, Jespersen MC et al (2015) LYRA, a webserver for lymphocyte receptor structural modeling. Nucleic Acids Res 43:W349
Ding YH, Baker BM, Garboczi DN et al (1999) Four A6-TCR/peptide/HLA-A2 structures that generate very different T cell signals are nearly identical. Immunity 11:45–56
Borbulevych OY, Santhanagopolan SM, Hossain M et al (2011) TCRs used in cancer gene therapy cross-react with MART-1/melan-a tumor antigens via distinct mechanisms. J Immunol 187:2453–2463
Gagnon SJ, Borbulevych OY, Davis-Harrison RL et al (2006) T cell receptor recognition via cooperative conformational plasticity. J Mol Biol 363:228–243
Borbulevych OY, Piepenbrink KH, Gloor BE et al (2009) T cell receptor cross-reactivity directed by antigen-dependent tuning of peptide-MHC molecular flexibility. Immunity 31:885–896
Piepenbrink KH, Borbulevych OY, Sommese RF et al (2009) Fluorine substitutions in an antigenic peptide selectively modulate T-cell receptor binding in a minimally perturbing manner. Biochem J 423:353–361
Scott DR, Borbulevych OY, Piepenbrink KH et al (2011) Disparate degrees of hypervariable loop flexibility control T-cell receptor cross-reactivity, specificity, and binding mechanism. J Mol Biol 414:385–400
Khan AR, Baker BM, Ghosh P et al (2000) The structure and stability of an HLA-A*0201/octameric tax peptide complex with an empty conserved peptide-N-terminal binding site. J Immunol 164:6398–6405
Utz U, Banks D, Jacobson S et al (1996) Analysis of the T-cell receptor repertoire of human T-cell leukemia virus type 1 (HTLV-1) Tax-specific CD8+ cytotoxic T lymphocytes from patients with HTLV-1-associated disease: evidence for oligoclonal expansion. J Virol 70:843–851
Johnson LA, Heemskerk B, Powell DJ Jr et al (2006) Gene transfer of tumor-reactive TCR confers both high avidity and tumor reactivity to nonreactive peripheral blood mononuclear cells and tumor-infiltrating lymphocytes. J Immunol 177:6548–6559
Kaufmann KW, Lemmon GH, Deluca SL et al (2010) Practically useful: what the Rosetta protein modeling suite can do for you. Biochemistry 49:2987–2998
Chaudhury S, Lyskov S, Gray JJ (2010) PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta. Bioinformatics 26:689–691
Rudolph MG, Stanfield RL, Wilson IA (2006) How TCRs bind MHCs, peptides, and coreceptors. Annu Rev Immunol 24:419–466
Miles JJ, Mccluskey J, Rossjohn J et al (2015) Understanding the complexity and malleability of T-cell recognition. Immunol Cell Biol 93:433–441
Chaudhury S, Gray JJ (2008) Conformer selection and induced fit in flexible backbone protein–protein docking using computational and NMR ensembles. J Mol Biol 381:1068–1087
Gray JJ, Moughon S, Wang C et al (2003) Protein–protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. J Mol Biol 331:281–299
Mandell DJ, Coutsias EA, Kortemme T (2009) Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling. Nat Methods 6:551–552
Park M-S, Park SY, Miller KR et al (2013) Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens. Mol Immunol 56:81–90
Schueler-Furman O, Elber R, Margalit H (1998) Knowledge-based structure prediction of MHC class I bound peptides: a study of 23 complexes. Fold Des 3:549–564
Fagerberg T, Cerottini J-C, Michielin O (2006) Structural prediction of peptides bound to MHC class I. J Mol Biol 356:521–546
Yanover C, Bradley P (2011) Large-scale characterization of peptide-MHC binding landscapes with structural simulations. Proc Natl Acad Sci 108:6981–6986
Borbulevych OY, Insaidoo FK, Baxter TK et al (2007) Structures of MART-1(26/27-35) peptide/HLA-A2 complexes reveal a remarkable disconnect between antigen structural homology and T cell recognition. J Mol Biol 372:1123–1136
Robinson J, Mistry K, Mcwilliam H et al (2011) The IMGT/HLA database. Nucleic Acids Res 39:D1171–D1176
Acknowledgements
Computational structural immunology in the authors’ laboratories is supported by NIH grants R01GM103773 and R01GM067079 and an award from the Carole and Ray Neag Comprehensive Cancer Center at the University of Connecticut. TPR is supported by a fellowship from the Indiana CTSI, funded in part by NIH grant UL1TR001108.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Riley, T.P., Singh, N.K., Pierce, B.G., Weng, Z., Baker, B.M. (2016). Computational Modeling of T Cell Receptor Complexes. In: Stoddard, B. (eds) Computational Design of Ligand Binding Proteins. Methods in Molecular Biology, vol 1414. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3569-7_19
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3569-7_19
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3567-3
Online ISBN: 978-1-4939-3569-7
eBook Packages: Springer Protocols