Four A6-TCR/peptide/HLA-A2 structures that generate very different T cell signals are nearly identical

APE-Gen2.0: Expanding Rapid Class I Peptide-Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries

The recognition of peptides bound to class I major histocompatibility complex (MHC-I) receptors by T-cell receptors (TCRs) is a determinant of triggering the adaptive immune response. While the exact molecular features that drive the TCR recognition are still unknown, studies have suggested that the geometry of the joint peptide-MHC (pMHC) structure plays an important role. As such, there is a definite need for methods and tools that accurately predict the structure of the peptide bound to the MHC-I receptor. In the past few years, many pMHC structural modeling tools have emerged that provide high-quality modeled structures in the general case. However, there are numerous instances of non-canonical cases in the immunopeptidome that the majority of pMHC modeling tools do not attend to, most notably, peptides that exhibit non-standard amino acids and post-translational modifications (PTMs) or peptides that assume non-canonical geometries in the MHC binding cleft. Such chemical and structural properties have been shown to be present in neoantigens; therefore, accurate structural modeling of these instances can be vital for cancer immunotherapy. To this end, we have developed APE-Gen2.0, a tool that improves upon its predecessor and other pMHC modeling tools, both in terms of modeling accuracy and the available modeling range of non-canonical peptide cases. Some of the improvements include (i) the ability to model peptides that have different types of PTMs such as phosphorylation, nitration, and citrullination; (ii) a new and improved anchor identification routine in order to identify and model peptides that exhibit a non-canonical anchor conformation; and (iii) a web server that provides a platform for easy and accessible pMHC modeling. We further show that structures predicted by APE-Gen2.0 can be used to assess the effects that PTMs have in binding affinity in a more accurate manner than just using solely the sequence of the peptide. APE-Gen2.0 is freely available at https://apegen.kavrakilab.org.

Asymmetric framework motion of TCRαβ controls load-dependent peptide discrimination

Mechanical force is critical for the interaction between an αβ T cell receptor (TCR) and a peptide-bound major histocompatibility complex (pMHC) molecule to initiate productive T-cell activation. However, the underlying mechanism remains unclear. We use all-atom molecular dynamics simulations to examine the A6 TCR bound to HLA-A*02:01 presenting agonist or antagonist peptides under different extensions to simulate the effects of applied load on the complex, elucidating their divergent biological responses. We found that TCR α and β chains move asymmetrically, which impacts the interface with pMHC, in particular the peptide-sensing CDR3 loops. For the wild-type agonist, the complex stabilizes in a load-dependent manner while antagonists destabilize it. Simulations of the Cβ FG-loop deletion, which reduces the catch bond response, and simulations with in silico mutant peptides further support the observed behaviors. The present results highlight the combined role of interdomain motion, fluctuating forces, and interfacial contacts in determining the mechanical response and fine peptide discrimination by a TCR, thereby resolving the conundrum of nearly identical crystal structures of TCRαβ-pMHC agonist and antagonist complexes.

Parsing digital or analogue TCR performance through piconewton forces

αβ T-cell receptors (TCRs) recognize aberrant peptides bound to major histocompatibility complex molecules (pMHCs) on unhealthy cells, amplifying specificity and sensitivity through physical load placed on the TCR-pMHC bond during immunosurveillance. To understand this mechanobiology, TCRs stimulated by abundantly and sparsely arrayed epitopes (NP 366-374 /D b and PA 224-233 /D b , respectively) following in vivo influenza A virus infection were studied with optical tweezers. While certain NP repertoire CD8 T lymphocytes require many ligands for activation, others are digital, needing just few. Conversely, all PA TCRs perform digitally, exhibiting pronounced bond lifetime increases through sustained, energizing volleys of structural transitioning. Optimal digital performance is superior in vivo, correlating with ERK phosphorylation, CD3 loss, and activation marker upregulation in vitro . Given neoantigen array paucity, digital TCRs are likely critical for immunotherapies.

One Sentence Summary

Quality of ligand recognition in a T-cell repertoire is revealed through application of physical load on clonal T-cell receptor (TCR)-pMHC bonds.

TAPIR: a T-cell receptor language model for predicting rare and novel targets

T-cell receptors (TCRs) are involved in most human diseases, but linking their sequences with their targets remains an unsolved grand challenge in the field. In this study, we present TAPIR (T-cell receptor and Peptide Interaction Recognizer), a T-cell receptor (TCR) language model that predicts TCR-target interactions, with a focus on novel and rare targets. TAPIR employs deep convolutional neural network (CNN) encoders to process TCR and target sequences across flexible representations (e.g., beta-chain only, unknown MHC allele, etc.) and learns patterns of interactivity via several training tasks. This flexibility allows TAPIR to train on more than 50k either paired (alpha and beta chain) or unpaired TCRs (just alpha or beta chain) from public and proprietary databases against 1933 unique targets. TAPIR demonstrates state-of-the-art performance when predicting TCR interactivity against common benchmark targets and is the first method to demonstrate strong performance when predicting TCR interactivity against novel targets, where no examples are provided in training. TAPIR is also capable of predicting TCR interaction against MHC alleles in the absence of target information. Leveraging these capabilities, we apply TAPIR to cancer patient TCR repertoires and identify and validate a novel and potent anti-cancer T-cell receptor against a shared cancer neoantigen target (PIK3CA H1047L). We further show how TAPIR, when extended with a generative neural network, is capable of directly designing T-cell receptor sequences that interact with a target of interest.

Asymmetric framework motion of TCRαβ controls load-dependent peptide discrimination

Mechanical force is critical for the interaction between an αβT cell receptor (TCR) and a peptide-bound major histocompatibility complex (pMHC) molecule to initiate productive T-cell activation. However, the underlying mechanism remains unclear. We use all-atom molecular dynamics simulations to examine the A6 TCR bound to HLA-A*02:01 presenting agonist or antagonist peptides under different extensions to simulate the effects of applied load on the complex, elucidating their divergent biological responses. We found that TCR α and β chains move asymmetrically, which impacts the interface with pMHC, in particular the peptide-sensing CDR3 loops. For the wild-type agonist, the complex stabilizes in a load-dependent manner while antagonists destabilize it. Simulations of the Cβ FG-loop deletion, which reduces the catch bond response, and simulations with in silico mutant peptides further support the observed behaviors. The present results highlight the combined role of interdomain motion, fluctuating forces, and interfacial contacts in determining the mechanical response and fine peptide discrimination by a TCR, thereby resolving the conundrum of nearly identical crystal structures of TCRαβ-pMHC agonist and antagonist complexes.

Machine-Learning-Assisted Analysis of TCR Profiling Data Unveils Cross-Reactivity between SARS-CoV-2 and a Wide Spectrum of Pathogens and Other Diseases

During the last two years, the emergence of SARS-CoV-2 has led to millions of deaths worldwide, with a devastating socio-economic impact on a global scale. The scientific community's focus has recently shifted towards the association of the T cell immunological repertoire with COVID-19 progression and severity, by utilising T cell receptor sequencing (TCR-Seq) assays. The Multiplexed Identification of T cell Receptor Antigen (MIRA) dataset, which is a subset of the immunoACCESS study, provides thousands of TCRs that can specifically recognise SARS-CoV-2 epitopes. Our study proposes a novel Machine Learning (ML)-assisted approach for analysing TCR-Seq data from the antigens' point of view, with the ability to unveil key antigens that can accurately distinguish between MIRA COVID-19-convalescent and healthy individuals based on differences in the triggered immune response. Some SARS-CoV-2 antigens were found to exhibit equal levels of recognition by MIRA TCRs in both convalescent and healthy cohorts, leading to the assumption of putative cross-reactivity between SARS-CoV-2 and other infectious agents. This hypothesis was tested by combining MIRA with other public TCR profiling repositories that host assays and sequencing data concerning a plethora of pathogens. Our study provides evidence regarding putative cross-reactivity between SARS-CoV-2 and a wide spectrum of pathogens and diseases, with M. tuberculosis and Influenza virus exhibiting the highest levels of cross-reactivity. These results can potentially shift the emphasis of immunological studies towards an increased application of TCR profiling assays that have the potential to uncover key mechanisms of cell-mediated immune response against pathogens and diseases.

Structural aspects of chemical modifications in the MHC-restricted immunopeptidome; Implications for immune recognition

Significant advances in mass-spectroscopy (MS) have made it possible to investigate the cellular immunopeptidome, a large collection of MHC-associated epitopes presented on the surface of healthy, stressed and infected cells. These approaches have hitherto allowed the unambiguous identification of large cohorts of epitope sequences that are restricted to specific MHC class I and II molecules, enhancing our understanding of the quantities, qualities and origins of these peptide populations. Most importantly these analyses provide essential information about the immunopeptidome in responses to pathogens, autoimmunity and cancer, and will hopefully allow for future tailored individual therapies. Protein post-translational modifications (PTM) play a key role in cellular functions, and are essential for both maintaining cellular homeostasis and increasing the diversity of the proteome. A significant proportion of proteins is post-translationally modified, and thus a deeper understanding of the importance of PTM epitopes in immunopeptidomes is essential for a thorough and stringent understanding of these peptide populations. The aim of the present review is to provide a structural insight into the impact of PTM peptides on stability of MHC/peptide complexes, and how these may alter/modulate immune responses.

Proteome-Scale Screening to Identify High-Expression Signal Peptides with Minimal N-Terminus Biases via Yeast Display

Signal peptides are critical for the efficient expression and routing of extracellular and secreted proteins. Most protein production and screening technologies rely upon a relatively small set of signal peptides. Despite their central role in biotechnology, there are limited studies comprehensively examining the interplay between signal peptides and expressed protein sequences. Here, we describe a high-throughput method to screen novel signal peptides that maintain a high degree of surface expression across a range of protein scaffolds with highly variable N-termini. We find that the canonical signal peptide used in yeast surface display, derived from Aga2p, fails to achieve high surface expression for 42.5% of constructs containing diverse N-termini. To circumvent this, we have identified two novel signal peptides derived from endogenous yeast proteins, SRL1 and KISH, which are highly tolerant to diverse N-terminal sequences. This pipeline can be used to expand our understanding of signal peptide function, identify improved signal peptides for protein expression, and refine the computational tools used for signal peptide prediction.

Unconventional modes of peptide-HLA-I presentation change the rules of TCR engagement

The intracellular proteome of virtually every nucleated cell in the body is continuously presented at the cell surface via the human leukocyte antigen class I (HLA-I) antigen processing pathway. This pathway classically involves proteasomal degradation of intracellular proteins into short peptides that can be presented by HLA-I molecules for interrogation by T-cell receptors (TCRs) expressed on the surface of CD8+ T cells. During the initiation of a T-cell immune response, the TCR acts as the T cell's primary sensor, using flexible loops to mould around the surface of the pHLA-I molecule to identify foreign or dysregulated antigens. Recent findings demonstrate that pHLA-I molecules can also be highly flexible and dynamic, altering their shape according to minor polymorphisms between different HLA-I alleles, or interactions with different peptides. These flexible presentation modes have important biological consequences that can, for example, explain why some HLA-I alleles offer greater protection against HIV, or why some cancer vaccine approaches have been ineffective. This review explores how these recent findings redefine the rules for peptide presentation by HLA-I molecules and extend our understanding of the molecular mechanisms that govern TCR-mediated antigen discrimination.

Engineering the T cell receptor for fun and profit: Uncovering complex biology, interrogating the immune system, and targeting disease

T cell receptors (TCRs) orchestrate cellular immunity by recognizing peptide antigens bound and presented by major histocompatibility complex (MHC) proteins. Due to the TCR's central role in immunity and tight connection with human health, there has been significant interest in modulating TCR properties through protein engineering methods. Complicating these efforts is the complexity and vast diversity of TCR-peptide/MHC interfaces, the interdependency between TCR affinity, specificity, and cross-reactivity, and the sophisticated relationships between TCR binding properties and T cell function, many aspects of which are not well understood. Here we review TCR engineering, starting with a brief historical overview followed by discussions of more recent developments, including new efforts and opportunities to engineer TCR affinity, modulate specificity, and develop novel TCR-based constructs.

Fluctuations in T cell receptor and pMHC interactions regulate T cell activation

Adaptive immune responses depend on interactions between T cell receptors (TCRs) and peptide major histocompatibility complex (pMHC) ligands located on the surface of T cells and antigen presenting cells (APCs), respectively. As TCRs and pMHCs are often only present at low copy numbers their interactions are inherently stochastic, yet the role of stochastic fluctuations on T cell function is unclear. Here, we introduce a minimal stochastic model of T cell activation that accounts for serial TCR-pMHC engagement, reversible TCR conformational change and TCR aggregation. Analysis of this model indicates that it is not the strength of binding between the T cell and the APC cell per se that elicits an immune response, but rather the information imparted to the T cell from the encounter, as assessed by the entropy rate of the TCR-pMHC binding dynamics. This view provides an information-theoretic interpretation of T cell activation that explains a range of experimental observations. Based on this analysis, we propose that effective T cell therapeutics may be enhanced by optimizing the inherent stochasticity of TCR-pMHC binding dynamics.

Immunological Mechanisms of Metal Allergies and the Nickel-Specific TCR-pMHC Interface

Besides having physiological functions and general toxic effects, many metal ions can cause allergic reactions in humans. We here review the immune events involved in the mediation of metal allergies. We focus on nickel (Ni), cobalt (Co) and palladium (Pd), because these allergens are among the most prevalent sensitizers (Ni, Co) and immediate neighbors in the periodic table of the chemical elements. Co-sensitization between Ni and the other two metals is frequent while the knowledge on a possible immunological cross-reactivity using in vivo and in vitro approaches remains limited. At the center of an allergic reaction lies the capability of a metal allergen to form T cell epitopes that are recognized by specific T cell receptors (TCR). Technological advances such as activation-induced marker assays and TCR high-throughput sequencing recently provided new insights into the interaction of Ni2+ with the αβ TCR-peptide-major histocompatibility complex (pMHC) interface. Ni2+ functionally binds to the TCR gene segment TRAV9-2 or a histidine in the complementarity determining region 3 (CDR3), the main antigen binding region. Thus, we overview known, newly identified and hypothesized mechanisms of metal-specific T cell activation and discuss current knowledge on cross-reactivity.

The discriminatory power of the T cell receptor

T cells use their T cell receptors (TCRs) to discriminate between lower-affinity self and higher-affinity non-self peptides presented on major histocompatibility complex (pMHC) antigens. Although the discriminatory power of the TCR is widely believed to be near-perfect, technical difficulties have hampered efforts to precisely quantify it. Here, we describe a method for measuring very low TCR/pMHC affinities and use it to measure the discriminatory power of the TCR and the factors affecting it. We find that TCR discrimination, although enhanced compared with conventional cell-surface receptors, is imperfect: primary human T cells can respond to pMHC with affinities as low as K_D ∼ 1 mM. The kinetic proofreading mechanism fit our data, providing the first estimates of both the time delay (2.8 s) and number of biochemical steps (2.67) that are consistent with the extraordinary sensitivity of antigen recognition. Our findings explain why self pMHC frequently induce autoimmune diseases and anti-tumour responses, and suggest ways to modify TCR discrimination.

Characterization of amino acid residues of T-cell receptors interacting with HLA-A*02-restricted antigen peptides

Background

The present study aimed to explore residues’ properties interacting with HLA-A*02-restricted peptides on T-cell receptors (TCRs) and their effects on bond types of interaction and binding free energy.

Methods

We searched the crystal structures of HLA-A*02-restricted peptide-TCR complexes from the Protein Data Bank (PDB) database and subsequently collected relevant parameters. We then employed Schrodinger to analyze the bond types of interaction and Gromacs 2019 to evaluate the TCR-antigen peptide complex’s molecular dynamics simulation. Finally, we compared the changes of bond types of interaction and binding free energy before and after residue substitution to ensure consistency of the conditions before and after residue substitution.

Results

The main sites on the antigen peptides that formed the intermolecular interaction [hydrogen bond (HB) and pi stack] with TCRs were P4, P8, P2, and P6. The hydrophobicity of the amino acids inside or outside the disulfide bond of TCRs may be related to the intermolecular interaction and binding free energy between TCRs and peptides. Residues located outside the disulfide bond of TCR α or β chains and forming pi stack force played favorable roles in the complex intermolecular interaction and binding free energy. The residues of the TCR α or β chains that interacted with peptides were replaced by alanine (Ala) or glycine (Gly), and their intermolecular binding free energy of the complex had been improved. However, it had nothing to do with the formation of HB.

Conclusions

The findings of this study suggest that the hydrophobic nature of the amino acids inside or outside the disulfide bonds on the TCR may be associated with the intermolecular interaction and binding between the TCR and polypeptide. The residues located outside the TCR α or β single-chain disulfide bond and forming the pi-stack force showed a beneficial effect on the intermolecular interaction and binding of the complex. In addition, the part of the residues on the TCR α or β single chain that produced bond types of interaction with the polypeptide after being replaced by Ala or Gly, the intermolecular binding free energy of the complex was increased, regardless of whether HB was formed.

A Simplified Amino Acidic Alphabet to Unveil the T-Cells Receptors Antigens: A Computational Perspective

The exposure to pathogens triggers the activation of adaptive immune responses through antigens bound to surface receptors of antigen presenting cells (APCs). T cell receptors (TCR) are responsible for initiating the immune response through their physical direct interaction with antigen-bound receptors on the APCs surface. The study of T cell interactions with antigens is considered of crucial importance for the comprehension of the role of immune responses in cancer growth and for the subsequent design of immunomodulating anticancer drugs. RNA sequencing experiments performed on T cells represented a major breakthrough for this branch of experimental molecular biology. Apart from the gene expression levels, the hypervariable CDR3α/β sequences of the TCR loops can now be easily determined and modelled in the three dimensions, being the portions of TCR mainly responsible for the interaction with APC receptors. The most direct experimental method for the investigation of antigens would be based on peptide libraries, but their huge combinatorial nature, size, cost, and the difficulty of experimental fine tuning makes this approach complicated time consuming, and costly. We have implemented in silico methodology with the aim of moving from CDR3α/β sequences to a library of potentially antigenic peptides that can be used in immunologically oriented experiments to study T cells’ reactivity. To reduce the size of the library, we have verified the reproducibility of experimental benchmarks using the permutation of only six residues that can be considered representative of all ensembles of 20 natural amino acids. Such a simplified alphabet is able to correctly find the poses and chemical nature of original antigens within a small subset of ligands of potential interest. The newly generated library would have the advantage of leading to potentially antigenic ligands that would contribute to a better understanding of the chemical nature of TCR-antigen interactions. This step is crucial in the design of immunomodulators targeted towards T-cells response as well as in understanding the first principles of an immune response in several diseases, from cancer to autoimmune disorders.

Peptide-MHC Binding Reveals Conserved Allosteric Sites in MHC Class I- and Class II-Restricted T Cell Receptors (TCRs)

T cells are vital for adaptive immune responses that protect against pathogens and cancers. The T cell receptor (TCR)-CD3 complex comprises a diverse αβ TCR heterodimer in noncovalent association with three invariant CD3 dimers. The TCR is responsible for recognizing antigenic peptides bound to MHC molecules (pMHC), while the CD3 dimers relay activation signals to the T cell. However, the mechanisms by which TCR engagement by pMHC is transmitted to CD3 remain mysterious, although there is growing evidence that mechanosensing and allostery both play a role. Here, we carried out NMR analysis of a human autoimmune TCR (MS2-3C8) that recognizes a self-peptide from myelin basic protein presented by the MHC class II molecule HLA-DR4. We observed pMHC-induced NMR signal perturbations in MS2-3C8 that indicate long-range effects on TCR β chain conformation and dynamics. Our results demonstrate that, in addition to expected changes in the NMR resonances of pMHC-contacting residues, perturbations extend to the Vβ/Vα, Vβ/Cβ, and Cβ/Cα interfacial regions. Moreover, the pattern of long-range perturbations is similar to that detected previously in the β chains of two MHC class I-restricted TCRs, thereby revealing a common allosteric pathway among three unrelated TCRs. Molecular dynamics (MD) simulations predict similar pMHC-induced effects. Taken together, our results demonstrate that pMHC binding induces long-range allosteric changes in the TCR β chain at conserved sites in both representative MHC class I- and class II-restricted TCRs, and that these sites may play a role in the transmission of signaling information.

Molecular mechanism of the recognition of bacterially cleaved immunoglobulin by the immune regulatory receptor LILRA2

Human leukocyte immunoglobulin-like receptors (LILRs) typically regulate immune activation by binding to the human leukocyte antigen class I molecules. LILRA2, a member of the LILR family, was recently reported to bind to other unique ligands, the bacterially degraded Igs (N-truncated Igs), for the activation of immune cells. Therefore, LILRA2 is currently attracting significant attention as a novel innate immune receptor. However, the detailed recognition mechanisms required for this interaction remain unclear. In this study, using several biophysical techniques, we uncovered the molecular mechanism of N-truncated Ig recognition by LILRA2. Surface plasmon resonance analysis disclosed that LILRA2 specifically binds to N-truncated Ig with weak affinity (K_d = 4.8 μm) and fast kinetics. However, immobilized LILRA2 exhibited a significantly enhanced interaction with N-truncated Ig due to avidity effects. This suggests that cell surface-bound LILRA2 rapidly monitors and identifies bi- or multivalent abnormal N-truncated Igs through specific cross-linking to induce immune activation. Van't Hoff analysis revealed that this interaction is enthalpy-driven, with a small entropy loss, and results from differential scanning calorimetry indicated the instability of the putative LILRA2-binding site, the Fab region of the N-truncated Ig. Atomic force microscopy revealed that N truncation does not cause significant structural changes in Ig. Furthermore, mutagenesis analysis identified the hydrophobic region of LILRA2 domain 2 as the N-truncated Ig-binding site, representing a novel ligand-binding site for the LILR family. These results provide detailed insights into the molecular regulation of LILR-mediated immune responses targeting ligands that have been modified by bacteria.

Identification of the Targets of T-cell Receptor Therapeutic Agents and Cells by Use of a High-Throughput Genetic Platform

T-cell receptor (TCR)-based therapeutic cells and agents have emerged as a new class of effective cancer therapies. These therapies work on cells that express intracellular cancer-associated proteins by targeting peptides displayed on MHC receptors. However, cross-reactivities of these agents to off-target cells and tissues have resulted in serious, sometimes fatal, adverse events. We have developed a high-throughput genetic platform (termed "PresentER") that encodes MHC-I peptide minigenes for functional immunologic assays and determines the reactivities of TCR-like therapeutic agents against large libraries of MHC-I ligands. In this article, we demonstrated that PresentER could be used to identify the on-and-off targets of T cells and TCR-mimic (TCRm) antibodies using in vitro coculture assays or binding assays. We found dozens of MHC-I ligands that were cross-reactive with two TCRm antibodies and two native TCRs and that were not easily predictable by other methods.

Structural understanding of T cell receptor triggering

The T cell receptor (TCR) is one of the most complicated receptors in mammalian cells, and its triggering mechanism remains mysterious. As an octamer complex, TCR comprises an antigen-binding subunit (TCRαβ) and three CD3 signaling subunits (CD3ζζ, CD3δε, and CD3γε). Engagement of TCRαβ with an antigen peptide presented on the MHC leads to tyrosine phosphorylation of the immunoreceptor tyrosine-based activation motif (ITAM) in CD3 cytoplasmic domains (CDs), thus translating extracellular binding kinetics to intracellular signaling events. Whether conformational change plays an important role in the transmembrane signal transduction of TCR is under debate. Attracted by the complexity and functional importance of TCR, many groups have been studying TCR structure and triggering for decades using diverse biochemical and biophysical tools. Here, we synthesize these structural studies and discuss the relevance of the conformational change model in TCR triggering.

The structural basis of T-cell receptor (TCR) activation: An enduring enigma

T cells are critical for protective immune responses to pathogens and tumors. The T-cell receptor (TCR)-CD3 complex is composed of a diverse αβ TCR heterodimer noncovalently associated with the invariant CD3 dimers CD3ϵγ, CD3ϵδ, and CD3ζζ. The TCR mediates recognition of antigenic peptides bound to MHC molecules (pMHC), whereas the CD3 molecules transduce activation signals to the T cell. Whereas much is known about downstream T-cell signaling pathways, the mechanism whereby TCR engagement by pMHC is first communicated to the CD3 signaling apparatus, a process termed early T-cell activation, remains largely a mystery. In this review, we examine the molecular basis for TCR activation in light of the recently determined cryoEM structure of a complete TCR-CD3 complex. This structure provides an unprecedented opportunity to assess various signaling models that have been proposed for the TCR. We review evidence from single-molecule and structural studies for force-induced conformational changes in the TCR-CD3 complex, for dynamically-driven TCR allostery, and for pMHC-induced structural changes in the transmembrane and cytoplasmic regions of CD3 subunits. We identify major knowledge gaps that must be filled in order to arrive at a comprehensive model of TCR activation that explains, at the molecular level, how pMHC-specific information is transmitted across the T-cell membrane to initiate intracellular signaling. An in-depth understanding of this process will accelerate the rational design of immunotherapeutic agents targeting the TCR-CD3 complex.

Structure Based Prediction of Neoantigen Immunogenicity

The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8+ T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

The 3A6-TCR/superagonist/HLA-DR2a complex shows similar interface and reduced flexibility compared to the complex with self-peptide

T-cell receptor (TCR) recognition of the myelin basic protein (MBP) peptide presented by major histocompatibility complex (MHC) protein HLA-DR2a, one of the MHC class II alleles associated with multiple sclerosis, is highly variable. Interactions in the trimolecular complex between the TCR of the MBP83-99-specific T cell clone 3A6 with the MBP-peptide/HLA-DR2a (abbreviated TCR/pMHC) lead to substantially different proliferative responses when comparing the wild-type decapeptide MBP90-99 and a superagonist peptide, which differs mainly in the residues that point toward the TCR. Here, we investigate the influence of the peptide sequence on the interface and intrinsic plasticity of the TCR/pMHC trimolecular and pMHC bimolecular complexes by molecular dynamics simulations. The intermolecular contacts at the TCR/pMHC interface are similar for the complexes with the superagonist and the MBP self-peptide. The orientation angle between TCR and pMHC fluctuates less in the complex with the superagonist peptide. Thus, the higher structural stability of the TCR/pMHC tripartite complex with the superagonist peptide, rather than a major difference in binding mode with respect to the self-peptide, seems to be responsible for the stronger proliferative response.

Breaking tolerance with engineered class I antigen-presenting molecules

Successful efforts to activate T cells capable of recognizing weak cancer-associated self-antigens have employed altered peptide antigens to activate T cell responses capable of cross-reacting on native tumor-associated self. A limitation of this approach is the requirement for detailed knowledge about the altered self-peptide ligands used in these vaccines. In the current study we considered allorecognition as an approach for activating CTL capable of recognizing weak or self-antigens in the context of self-MHC. Nonself antigen-presenting molecules typically contain polymorphisms that influence interactions with the bound peptide and TCR interface. Recognition of these nonself structures results in peptide-dependent alloimmunity. Alloreactive T cells target their inducing alloantigens as well as third-party alloantigens but generally fail to target self-antigens. Certain residues located on the alpha-1/2 domains of class I antigen-presenting molecules primarily interface with TCR. These residues are more conserved within and across species than are residues that determine peptide antigen binding properties. Class I variants designed with amino acid substitutions at key positions within the conserved helical structures are shown to provide strong activating signals to alloreactive CD8 T cells while avoiding changes in naturally bound peptide ligands. Importantly, CTL activated in this manner can break self-tolerance by reacting to self-peptides presented by native MHC. The ability to activate self-tolerant T cells capable of cross-reacting on self-peptide-MHC in vivo represents an approach for inducing autoimmunity, with possible application in cancer vaccines.

Integrating Experiment and Theory to Understand TCR-pMHC Dynamics

The conformational dynamism of proteins is well established. Rather than having a single structure, proteins are more accurately described as a conformational ensemble that exists across a rugged energy landscape, where different conformational sub-states interconvert. The interaction between αβ T cell receptors (TCR) and cognate peptide-MHC (pMHC) is no exception, and is a dynamic process that involves substantial conformational change. This review focuses on technological advances that have begun to establish the role of conformational dynamics and dynamic allostery in TCR recognition of the pMHC and the early stages of signaling. We discuss how the marriage of molecular dynamics (MD) simulations with experimental techniques provides us with new ways to dissect and interpret the process of TCR ligation. Notably, application of simulation techniques lags behind other fields, but is predicted to make substantial contributions. Finally, we highlight integrated approaches that are being used to shed light on some of the key outstanding questions in the early events leading to TCR signaling.

Peptide-MHC (pMHC) binding to a human antiviral T cell receptor induces long-range allosteric communication between pMHC- and CD3-binding sites

T cells generate adaptive immune responses mediated by the T cell receptor (TCR)-CD3 complex comprising an αβ TCR heterodimer noncovalently associated with three CD3 dimers. In early T cell activation, αβ TCR engagement by peptide-major histocompatibility complex (pMHC) is first communicated to the CD3 signaling apparatus of the TCR-CD3 complex, but the underlying mechanism is incompletely understood. It is possible that pMHC binding induces allosteric changes in TCR conformation or dynamics that are then relayed to CD3. Here, we carried out NMR analysis and molecular dynamics (MD) simulations of both the α and β chains of a human antiviral TCR (A6) that recognizes the Tax antigen from human T cell lymphotropic virus-1 bound to the MHC class I molecule HLA-A2. We observed pMHC-induced NMR signal perturbations in the TCR variable (V) domains that propagated to three distinct sites in the constant (C) domains: 1) the Cβ FG loop projecting from the Vβ/Cβ interface; 2) a cluster of Cβ residues near the Cβ αA helix, a region involved in interactions with CD3; and 3) the Cα AB loop at the membrane-proximal base of the TCR. A biological role for each of these allosteric sites is supported by previous mutational and functional studies of TCR signaling. Moreover, the pattern of long-range, ligand-induced changes in TCR A6 revealed by NMR was broadly similar to that predicted by the MD simulations. We propose that the unique structure of the TCR β chain enables allosteric communication between the TCR-binding sites for pMHC and CD3.

Selection of Tumor-Specific Cytotoxic T Lymphocytes in Acute Myeloid Leukemia Patients Through the Identification of T-Cells Capable to Establish Stable Interactions With the Leukemic Cells: "Doublet Technology"

The relevance of the immune system in cancer has long been studied. Autologous adoptive T cell therapies, based on the use of tumor infiltrating lymphocytes (TILs), have made great progress in recent years for the treatment of solid tumors, especially melanoma. However, further work is needed to isolate tumor-reactive T cells among patients diagnosed with hematologic malignancies. The dynamics of the interaction between T cells and antigen presenting cells (APC) dictate the quality of the immune responses. While stable joints between target cells and T lymphocytes lead to the induction of T cell activation and immune response, brief contacts contribute to the induction of immune-tolerance. Taking advantage of the strong interaction between target cell and activated T-cells, we show the feasibility to identify and isolate tumor-specific cytotoxic T lymphocytes (CTLs) from acute myeloid leukemia (AML) patients by flow cytometry. Using this technology, CTLs bound through T cell receptor (TCR) to tumor cells can be identified in peripheral blood and bone marrow and subsequently selected and isolated by FACS-based cell sorting. These CTLs display higher percentage of effector cells and marked cytotoxic activity against AML blasts. In conclusion, we have developed a new procedure to identify and select specific cytotoxic T cells in patients diagnosed with acute myeloid leukemia.

Isolation of a Structural Mechanism for Uncoupling T Cell Receptor Signaling from Peptide-MHC Binding

TCR-signaling strength generally correlates with peptide-MHC binding affinity; however, exceptions exist. We find high-affinity, yet non-stimulatory, interactions occur with high frequency in the human T cell repertoire. Here, we studied human TCRs that are refractory to activation by pMHC ligands despite robust binding. Analysis of 3D affinity, 2D dwell time, and crystal structures of stimulatory versus non-stimulatory TCR-pMHC interactions failed to account for their different signaling outcomes. Using yeast pMHC display, we identified peptide agonists of a formerly non-responsive TCR. Single-molecule force measurements demonstrated the emergence of catch bonds in the activating TCR-pMHC interactions, correlating with exclusion of CD45 from the TCR-APC contact site. Molecular dynamics simulations of TCR-pMHC disengagement distinguished agonist from non-agonist ligands based on the acquisition of catch bonds within the TCR-pMHC interface. The isolation of catch bonds as a parameter mediating the coupling of TCR binding and signaling has important implications for TCR and antigen engineering for immunotherapy.

Altered Peptide Ligands Impact the Diversity of Polyfunctional Phenotypes in T Cell Receptor Gene-Modified T Cells

The use of T cell receptor (TCR) gene-modified T cells in adoptive cell transfer has had promising clinical success, but often, simple preclinical evaluation does not necessarily accurately predict treatment efficacy or safety. Preclinical studies generally evaluate one or a limited number of type 1 cytokines to assess antigen recognition. However, recent studies have implicated other "typed" T cells in effective anti-tumor/viral immunity, and limited functional evaluations may underestimate cross-reactivity. In this study, we use an altered peptide ligand (APL) model and multi-dimensional flow cytometry to evaluate polyfunctionality of TCR gene-modified T cells. Evaluating six cytokines and the lytic marker CD107a on a per cell basis revealed remarkably diverse polyfunctional phenotypes within a single T cell culture and among peripheral blood lymphocyte (PBL) donors. This polyfunctional assessment identified unexpected phenotypes, including cells producing both type 1 and type 2 cytokines, and highlighted interferon γ^neg (IFNγ^neg) antigen-reactive populations overlooked in our previous studies. Additionally, APLs skewed functional phenotypes to be less polyfunctional, which was not necessarily related to changes in TCR-peptide-major histocompatibility complex (pMHC) affinity. A better understanding of gene-modified T cell functional diversity may help identify optimal therapeutic phenotypes, predict clinical responses, anticipate off-target recognition, and improve the design and delivery of TCR gene-modified T cells.

Reciprocal TCR-CD3 and CD4 Engagement of a Nucleating pMHCII Stabilizes a Functional Receptor Macrocomplex

CD4+ T cells convert the time that T cell receptors (TCRs) interact with peptides embedded within class II major histocompatibility complex molecules (pMHCII) into signals that direct cell-fate decisions. In principle, TCRs relay information to intracellular signaling motifs of the associated CD3 subunits, while CD4 recruits the kinase Lck to those motifs upon coincident detection of pMHCII. But the mechanics by which this occurs remain enigmatic. In one model, the TCR and CD4 bind pMHCII independently, while in another, CD4 interacts with a composite surface formed by the TCR-CD3 complex bound to pMHCII. Here, we report that the duration of TCR-pMHCII interactions impact CD4 binding to MHCII. In turn, CD4 increases TCR confinement to pMHCII via reciprocal interactions involving membrane distal and proximal CD4 ectodomains. The data suggest that a precisely assembled macrocomplex functions to reliably convert TCR-pMHCII confinement into reproducible signals that orchestrate adaptive immunity.

Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes

T cell specificity emerges from a myriad of processes, ranging from the biological pathways that control T cell signaling to the structural and physical mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and physical studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophysical principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunology.

MFPred: Rapid and accurate prediction of protein-peptide recognition multispecificity using self-consistent mean field theory

Multispecificity-the ability of a single receptor protein molecule to interact with multiple substrates-is a hallmark of molecular recognition at protein-protein and protein-peptide interfaces, including enzyme-substrate complexes. The ability to perform structure-based prediction of multispecificity would aid in the identification of novel enzyme substrates, protein interaction partners, and enable design of novel enzymes targeted towards alternative substrates. The relatively slow speed of current biophysical, structure-based methods limits their use for prediction and, especially, design of multispecificity. Here, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors: protease and kinase enzymes, and protein recognition modules including SH2, SH3, MHC Class I and PDZ domains. We observe robust recapitulation of known specificities for all receptor-peptide complexes, and comparison with other methods shows that MFPred results in equivalent or better prediction accuracy with a ~10-1000-fold decrease in computational expense. We find that modeling bound peptide backbone flexibility is key to the observed accuracy of the method. We used MFPred for predicting with high accuracy the impact of receptor-side mutations on experimentally determined multispecificity of a protease enzyme. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities.

DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles

Background

T cell receptor (TCR) molecules are involved in the adaptive immune response as they distinguish between self- and foreign-peptides, presented in major histocompatibility complex molecules (pMHC). Former studies showed that the association angles of the TCR variable domains (Vα/Vβ) can differ significantly and change upon binding to the pMHC complex. These changes can be described as a rotation of the domains around a general Center of Rotation, characterized by the interaction of two highly conserved glutamine residues.

Methods

We developed a computational method, DynaDom, for the prediction of TCR Vα/Vβ inter-domain and TCR/pMHC orientations in TCRpMHC complexes, which allows predicting the orientation of multiple protein-domains. In addition, we implemented a new approach to predict the correct orientation of the carboxamide endgroups in glutamine and asparagine residues, which can also be used as an external, independent tool.

Results

The approach was evaluated for the remodeling of 75 and 53 experimental structures of TCR and TCRpMHC (class I) complexes, respectively. We show that the DynaDom method predicts the correct orientation of the TCR Vα/Vβ angles in 96 and 89% of the cases, for the poses with the best RMSD and best interaction energy, respectively. For the concurrent prediction of the TCR Vα/Vβ and pMHC orientations, the respective rates reached 74 and 72%. Through an exhaustive analysis, we could show that the pMHC placement can be further improved by a straightforward, yet very time intensive extension of the current approach.

Conclusions

The results obtained in the present remodeling study prove the suitability of our approach for interdomain-angle optimization. In addition, the high prediction rate obtained specifically for the energetically highest ranked poses further demonstrates that our method is a powerful candidate for blind prediction. Therefore it should be well suited as part of any accurate atomistic modeling pipeline for TCRpMHC complexes and potentially other large molecular assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12900-016-0071-7) contains supplementary material, which is available to authorized users.

An Engineered Switch in T Cell Receptor Specificity Leads to an Unusual but Functional Binding Geometry

Utilizing a diverse binding site, T cell receptors (TCRs) specifically recognize a composite ligand comprised of a foreign peptide and a major histocompatibility complex protein (MHC). To help understand the determinants of TCR specificity, we studied a parental and engineered receptor whose peptide specificity had been switched via molecular evolution. Altered specificity was associated with a significant change in TCR-binding geometry, but this did not impact the ability of the TCR to signal in an antigen-specific manner. The determinants of binding and specificity were distributed among contact and non-contact residues in germline and hypervariable loops, and included disruption of key TCR-MHC interactions that bias αβ TCRs toward particular binding modes. Sequence-fitness landscapes identified additional mutations that further enhanced specificity. Our results demonstrate that TCR specificity arises from the distributed action of numerous sites throughout the interface, with significant implications for engineering therapeutic TCRs with novel and functional recognition properties.

Hotspot autoimmune T cell receptor binding underlies pathogen and insulin peptide cross-reactivity

The cross-reactivity of T cells with pathogen- and self-derived peptides has been implicated as a pathway involved in the development of autoimmunity. However, the mechanisms that allow the clonal T cell antigen receptor (TCR) to functionally engage multiple peptide–major histocompatibility complexes (pMHC) are unclear. Here, we studied multiligand discrimination by a human, preproinsulin reactive, MHC class-I–restricted CD8⁺ T cell clone (1E6) that can recognize over 1 million different peptides. We generated high-resolution structures of the 1E6 TCR bound to 7 altered peptide ligands, including a pathogen-derived peptide that was an order of magnitude more potent than the natural self-peptide. Evaluation of these structures demonstrated that binding was stabilized through a conserved lock-and-key–like minimal binding footprint that enables 1E6 TCR to tolerate vast numbers of substitutions outside of this so-called hotspot. Highly potent antigens of the 1E6 TCR engaged with a strong antipathogen-like binding affinity; this engagement was governed though an energetic switch from an enthalpically to entropically driven interaction compared with the natural autoimmune ligand. Together, these data highlight how T cell cross-reactivity with pathogen-derived antigens might break self-tolerance to induce autoimmune disease.

The Dynamics of the Human Leukocyte Antigen Head Domain Modulates Its Recognition by the T-Cell Receptor

Generating the immune response requires the discrimination of peptides presented by the human leukocyte antigen complex (HLA) through the T-cell receptor (TCR). However, how a single amino acid substitution in the antigen bonded to HLA affects the response of T cells remains uncertain. Hence, we used molecular dynamics computations to analyze the molecular interactions between peptides, HLA and TCR. We compared immunologically reactive complexes with non-reactive and weakly reactive complexes. MD trajectories were produced to simulate the behavior of isolated components of the various p-HLA-TCR complexes. Analysis of the fluctuations showed that p-HLA binding barely restrains TCR motions, and mainly affects the CDR3 loops. Conversely, inactive p-HLA complexes displayed significant drop in their dynamics when compared with its free versus ternary forms (p-HLA-TCR). In agreement, the free non-reactive p-HLA complexes showed a lower amount of salt bridges than the responsive ones. This resulted in differences between the electrostatic potentials of reactive and inactive p-HLA species and larger vibrational entropies in non-elicitor complexes. Analysis of the ternary p-HLA-TCR complexes also revealed a larger number of salt bridges in the responsive complexes. To summarize, our computations indicate that the affinity of each p-HLA complex towards TCR is intimately linked to both, the dynamics of its free species and its ability to form specific intermolecular salt-bridges in the ternary complexes. Of outstanding interest is the emerging concept of antigen reactivity involving its interplay with the HLA head sidechain dynamics by rearranging its salt-bridges.

Differential utilization of binding loop flexibility in T cell receptor ligand selection and cross-reactivity

Complementarity determining region (CDR) loop flexibility has been suggested to play an important role in the selection and binding of ligands by T cell receptors (TCRs) of the cellular immune system. However, questions remain regarding the role of loop motion in TCR binding, and crystallographic structures have raised questions about the extent to which generalizations can be made. Here we studied the flexibility of two structurally well characterized αβ TCRs, A6 and DMF5. We found that the two receptors utilize loop motion very differently in ligand binding and cross-reactivity. While the loops of A6 move rapidly in an uncorrelated fashion, those of DMF5 are substantially less mobile. Accordingly, the mechanisms of binding and cross-reactivity are very different between the two TCRs: whereas A6 relies on conformational selection to select and bind different ligands, DMF5 uses a more rigid, permissive architecture with greater reliance on slower motions or induced-fit. In addition to binding site flexibility, we also explored whether ligand-binding resulted in common dynamical changes in A6 and DMF5 that could contribute to TCR triggering. Although binding-linked motional changes propagated throughout both receptors, no common features were observed, suggesting that changes in nanosecond-level TCR structural dynamics do not contribute to T cell signaling.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

How structural adaptability exists alongside HLA-A2 bias in the human αβ TCR repertoire

How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining αβ TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged "hot-spot" region that is almost exclusive to the α1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Vα and Vβ genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs.

Atomic Coordination Reflects Peptide Immunogenicity

We demonstrated that the immunological identity of variant peptides may be accurately predicted on the basis of atomic coordination of both unprotonated and protonated tertiary structures, provided that the structure of the native peptide (index) is known. The metric which was discovered to account for this discrimination is the coordination difference between the variant and the index; we also showed that increasing coordination difference in respect to the index was correlated to a correspondingly weakening immunological outcome of the variant. Additionally, we established that this metric quickly seizes to operate beyond the peptide scale, e.g., within a coordination shell inclusive of atoms up to a distance of 7 Å away from the peptide or over the entire pMHC-TCR complex. Analysis of molecular orbital interactions for a range of formal charges further revealed that the N-terminus of the agonists was always able to sustain a stable ammonium (NH3+) group which was consistently absent in antagonists. We deem that the presence of NH3+ constitutes a secondary observable with a biological consequence, signifying a change in T cell activation. While our analysis of protonated structures relied on the quantum chemical relaxation of the H species, the results were consistent across a wide range of peptide charge and spin polarization conditions.

Structure of a TCR-Mimic Antibody with Target Predicts Pharmacogenetics

Antibody therapies currently target only extracellular antigens. A strategy to recognize intracellular antigens is to target peptides presented by immune HLA receptors. ESK1 is a human, T-cell receptor (TCR)-mimic antibody that binds with subnanomolar affinity to the RMF peptide from the intracellular Wilms tumor oncoprotein WT1 in complex with HLA-A*02:01. ESK1 is therapeutically effective in mouse models of WT1(+) human cancers. TCR-based therapies have been presumed to be restricted to one HLA subtype. The mechanism for the specificity and high affinity of ESK1 is unknown. We show in a crystal structure that ESK1 Fab binds to RMF/HLA-A*02:01 in a mode different from that of TCRs. From the structure, we predict and then experimentally confirm high-affinity binding with multiple other HLA-A*02 subtypes, broadening the potential patient pool for ESK1 therapy. Using the crystal structure, we also predict potential off-target binding that we experimentally confirm. Our results demonstrate how protein structure information can contribute to personalized immunotherapy.

Computational Modeling of T Cell Receptor Complexes

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.

Structural interplay between germline interactions and adaptive recognition determines the bandwidth of TCR-peptide-MHC cross-reactivity

The T cell antigen receptor (TCR)-peptide-major histocompatibility complex (MHC) interface is composed of conserved and diverse regions, yet the relative contribution of each in shaping recognition by T cells remains unclear. Here we isolated cross-reactive peptides with limited homology, which allowed us to compare the structural properties of nine peptides for a single TCR-MHC pair. The TCR's cross-reactivity was rooted in highly similar recognition of an apical 'hot-spot' position in the peptide with tolerance of sequence variation at ancillary positions. Furthermore, we found a striking structural convergence onto a germline-mediated interaction between the TCR CDR1α region and the MHC α2 helix in twelve TCR-peptide-MHC complexes. Our studies suggest that TCR-MHC germline-mediated constraints, together with a focus on a small peptide hot spot, might place limits on peptide antigen cross-reactivity.

The coordination of unprotonated peptide tertiary structure as a metric of pMHC-TCR functional avidity

The coordination difference between the unprotonated tertiary structures of a native (Tax) peptide and a number of its variants – all peptides presented by HLA-A201 and bound to the human A6 T cell receptor-was discovered to constitute a metric of pMHC–TCR functional avidity. Moreover, increasing coordination deviations from the index were found to flag correspondingly weakening immunological outcomes of the variant peptides. The prognostic utility of the coordination difference of unprotonated tertiary structure was established to operate strictly on the peptide scale, seizing to be of relevance either to the immediate peptide environment (i.e. within the realm of peptide short range order, within 7 Å of any peptide atom) or over the entirety of the pMHC–TCR complex. Additionally, the imprint of peptide immunological identity was expressed both by the total coordination as well as by its C–C partial.

Quantitative Analysis of the Association Angle between T-cell Receptor Vα/Vβ Domains Reveals Important Features for Epitope Recognition

T-cell receptors (TCR) play an important role in the adaptive immune system as they recognize pathogen- or cancer-based epitopes and thus initiate the cell-mediated immune response. Therefore there exists a growing interest in the optimization of TCRs for medical purposes like adoptive T-cell therapy. However, the molecular mechanisms behind T-cell signaling are still predominantly unknown. For small sets of TCRs it was observed that the angle between their Vα- and Vβ-domains, which bind the epitope, can vary and might be important for epitope recognition. Here we present a comprehensive, quantitative study of the variation in the Vα/Vβ interdomain-angle and its influence on epitope recognition, performing a systematic bioinformatics analysis based on a representative set of experimental TCR structures. For this purpose we developed a new, cuboid-based superpositioning method, which allows a unique, quantitative analysis of the Vα/Vβ-angles. Angle-based clustering led to six significantly different clusters. Analysis of these clusters revealed the unexpected result that the angle is predominantly influenced by the TCR-clonotype, whereas the bound epitope has only a minor influence. Furthermore we could identify a previously unknown center of rotation (CoR), which is shared by all TCRs. All TCR geometries can be obtained by rotation around this center, rendering it a new, common TCR feature with the potential of improving the accuracy of TCR structure prediction considerably. The importance of Vα/Vβ rotation for signaling was confirmed as we observed larger variances in the Vα/Vβ-angles in unbound TCRs compared to epitope-bound TCRs. Our results strongly support a two-step mechanism for TCR-epitope: First, preformation of a flexible TCR geometry in the unbound state and second, locking of the Vα/Vβ-angle in a TCR-type specific geometry upon epitope-MHC association, the latter being driven by rotation around the unique center of rotation.

The recognition of antigenic peptides by cytotoxic T-cells is one of the crucial steps during the adaptive immune response. Thus a detailed understanding of this process is not only important for elucidating the mechanism behind T-cell signaling, but also for various emerging new medical applications like T-cell based immunotherapies and designed bio-therapeutics. However, despite the fast growing interest in this field, the mechanistic basis of the immune response is still largely unknown. Previous qualitative studies suggested that the T-cell receptor (TCR) Vα/Vβ-interdomain angle plays a crucial role in epitope recognition as it predetermines the relative position of its antigen-recognizing CDR1-3 loops and thus TCR specificity. In the manuscript we present a systematic bioinformatic analysis of the structural characteristics of bound and unbound TCR molecules focusing on the Vα/Vβ-angle. Our results demonstrate the importance of this angle for signaling, as several distinct Vα/Vβ-angle based structural clusters could be observed and larger angle flexibilities exist for unbound TCRs than for bound TCRs, providing quantitative proof for a two-step locking mechanism upon epitope recognition. In this context, we could identify a unique rotational point, which allows a quantitative, yet intuitive description of all observed angle variations and the structural changes upon epitope binding.

Soluble T-cell receptors produced in human cells for targeted delivery

Recently, technology has become available to generate soluble T-cell receptors (sTCRs) that contain the antigen recognition part. In contrast to antibodies, sTCRs recognize intracellular in addition to extracellular epitopes, potentially increasing the number of applications as reagents for target detection and immunotherapy. Moreover, recent data show that they can be used for identification of their natural peptide ligands in disease. Here we describe a new and simplified expression method for sTCRs in human cells and show that these sTCRs can be used for antigen-specific labeling and elimination of human target cells. Four different TCRs were solubilized by expression of constructs encoding the TCR alpha (α) and beta (β) chains lacking the transmembrane and intracellular domains, linked by a ribosomal skipping 2A sequence that facilitates equimolar production of the chains. Cell supernatants containing sTCRs labeled target cells directly in a peptide (p)-human leukocyte antigen (HLA)-specific manner. We demonstrated that a MART-1p/HLA-A*02:01-specific sTCR fused to a fluorescent protein, or multimerized onto magnetic nanoparticles, could be internalized. Moreover, we showed that this sTCR and two sTCRs recognizing CD20p/HLA-A*02:01 could mediate selective elimination of target cells expressing the relevant pHLA complex when tetramerized to streptavidin-conjugated toxin, demonstrating the potential for specific delivery of cargo. This simple and efficient method can be utilized to generate a wide range of minimally modified sTCRs from the naturally occurring TCR repertoire for antigen-specific detection and targeting.

The quantum chemical causality of pMHC-TCR biological avidity: Peptide atomic coordination data and the electronic state of agonist N termini

The quantum state of functional avidity of the synapse formed between a peptide-Major Histocompatibility Complex (pMHC) and a T cell receptor (TCR) is a subject not previously touched upon. Here we present atomic pair correlation meta-data based on crystalized tertiary structures of the Tax (HTLV-1) peptide along with three artificially altered variants, all of which were presented by the (Class I) HLA-A201 protein in complexation with the human (CD8(+)) A6TCR. The meta-data reveal the existence of a direct relationship between pMHC-TCR functional avidity (agonist/antagonist) and peptide pair distribution function (PDF). In this context, antagonist peptides are consistently under-coordinated in respect to Tax. Moreover, Density Functional Theory (DFT) datasets in the BLYP/TZ2P level of theory resulting from relaxation of the H species on peptide tertiary structures reveal that the coordination requirement of agonist peptides is also expressed as a physical observable of the protonation state of their N termini: agonistic peptides are always found to retain a stable ammonium (NH3 (+)) terminal group while antagonist peptides are not.

Quantum chemical calculations predict biological function: the case of T cell receptor interaction with a peptide/MHC class I

A combination of atomic correlation statistics and quantum chemical calculations are shown to predict biological function. In the present study, various antigenic peptide-Major Histocompatibility Complex (pMHC) ligands with near-identical stereochemistries, in complexation with the same T cell receptor (TCR), were found to consistently induce distinctly different quantum chemical behavior, directly dependent on the peptide's electron spin density and intrinsically expressed by the protonation state of the peptide's N-terminus. Furthermore, the cumulative coordination difference of any variant in respect to the native peptide was found to accurately reflect peptide biological function and immerges as the physical observable which is directly related to the immunological end-effect of pMHC-TCR interaction.