Geometrical characterization of T cell receptor binding modes reveals class-specific binding to maximize access to antigen

The role of peptide conformation presented by MHC in the induction of TCR triggering

A high-resolution crystal structure of stimulatory peptide-major histocompatibility complex (pMHC) ligands bound to T cell receptor (TCR) revealed different conformations of the two peptides at positions P6 and V7 compared to the conformation of the same peptides presented by unliganded MHC. Supercomputer simulations and a well-tempered metadynamics approach revealed several metastable noncanonical TCR-pMHC interactions that depend on the conformation of the MHC-bound peptides. The diversity of metastable states was significantly more represented in the signaling TCR-pMHC complex. These findings suggest that TCR-pMHC recognition can be informed by a conformation of peptide presented by MHC that notably influences the orientation of a TCR-recognizing pMHC ligand. It appears that TCRs bound to stimulatory pMHC possess a significantly higher degree of freedom to assume various metastable TCR orientations, which are distinct from canonical docking. In contrast, TCR interacting with nonstimulatory pMHC ligand revealed markedly less metastable noncanonical interactions and disengaged from the pMHC. This suggests that productive TCR-mediated signaling may depend on noncanonical interactions between TCRs and pMHC, either facilitating early recognition events or providing new contacts for catch-bond formation. Our discovery can inform future attempts to simulate the catch-bond formation mechanism in TCR-pMHC recognition, allowing the formation of new bonds mediating alternative peptide presentation.

TCR3d 2.0: expanding the T cell receptor structure database with new structures, tools and interactions

Recognition of antigens by T cell receptors (TCRs) is a key component of adaptive immunity. Understanding the structures of these TCR interactions provides major insights into immune protection and diseases, and enables design of therapeutics, vaccines and predictive modeling algorithms. Previously, we released TCR3d, a database and resource for structures of TCRs and their recognition. Due to the growth of available structures and categories of complexes, the content of TCR3d has expanded substantially in the past 5 years. This expansion includes new tables dedicated to TCR mimic antibody complex structures, TCR-CD3 complexes and annotated Class I and II peptide-MHC complexes. Additionally, tools are available for users to calculate docking geometries for input TCR and TCR mimic complex structures. The core tables of TCR-peptide-MHC complexes have grown by 50%, and include binding affinity data for experimentally determined structures. These major content and feature updates enhance TCR3d as a resource for immunology, therapeutics and structural biology research, and enable advanced approaches for predictive TCR modeling and design. TCR3d is available at: https://tcr3d.ibbr.umd.edu.

The Evolving T Cell Receptor Recognition Code: The Rules Are More Like Guidelines

αβ T cell receptor (TCR) recognition of peptide-MHC complexes lies at the core of adaptive immunity, balancing specificity and cross-reactivity to facilitate effective antigen discrimination. Early structural studies established basic frameworks helpful for understanding and contextualizing TCR recognition and features such as peptide specificity and MHC restriction. However, the growing TCR structural database and studies launched from structural work continue to reveal exceptions to common assumptions and simplifications derived from earlier work. Here we explore our evolving understanding of TCR recognition, illustrating how structural and biophysical investigations regularly uncover complex phenomena that push against paradigms and expand our understanding of how TCRs bind to and discriminate between peptide/MHC complexes. We discuss the implications of these findings for basic, translational, and predictive immunology, including the challenges in accounting for the inherent adaptability, flexibility, and occasional biophysical sloppiness that characterize TCR recognition.

Strengths and limitations of web servers for the modeling of TCRpMHC complexes

Cellular immunity relies on the ability of a T-cell receptor (TCR) to recognize a peptide (p) presented by a class I major histocompatibility complex (MHC) receptor on the surface of a cell. The TCR-peptide-MHC (TCRpMHC) interaction is a crucial step in activating T-cells, and the structural characteristics of these molecules play a significant role in determining the specificity and affinity of this interaction. Hence, obtaining 3D structures of TCRpMHC complexes offers valuable insights into various aspects of cellular immunity and can facilitate the development of T-cell-based immunotherapies. Here, we aimed to compare three popular web servers for modeling the structures of TCRpMHC complexes, namely ImmuneScape (IS), TCRpMHCmodels, and TCRmodel2, to examine their strengths and limitations. Each method employs a different modeling strategy, including docking, homology modeling, and deep learning. The accuracy of each method was evaluated by reproducing the 3D structures of a dataset of 87 TCRpMHC complexes with experimentally determined crystal structures available on the Protein Data Bank (PDB). All selected structures were limited to human MHC alleles, presenting a diverse set of peptide ligands. A detailed analysis of produced models was conducted using multiple metrics, including Root Mean Square Deviation (RMSD) and standardized assessments from CAPRI and DockQ. Special attention was given to the complementarity-determining region (CDR) loops of the TCRs and to the peptide ligands, which define most of the unique features and specificity of a given TCRpMHC interaction. Our study provides an optimistic view of the current state-of-the-art for TCRpMHC modeling but highlights some remaining challenges that must be addressed in order to support the future application of these tools for TCR engineering and computer-aided design of TCR-based immunotherapies.

The Observed T Cell Receptor Space database enables paired-chain repertoire mining, coherence analysis, and language modeling

T cell activation is governed through T cell receptors (TCRs), heterodimers of two sequence-variable chains (often an α and β chain) that synergistically recognize antigen fragments presented on cell surfaces. Despite this, there only exist repositories dedicated to collecting single-chain, not paired-chain, TCR sequence data. We addressed this gap by creating the Observed TCR Space (OTS) database, a source of consistently processed and annotated, full-length, paired-chain TCR sequences. Currently, OTS contains 5.35 million redundant (1.63 million non-redundant), predominantly human sequences from across 50 studies and at least 75 individuals. Using OTS, we identify pairing biases, public TCRs, and distinct chain coherence patterns relative to antibodies. We also release a paired-chain TCR language model, providing paired embedding representations and a method for residue in-filling conditional on the partner chain. OTS will be updated as a central community resource and is freely downloadable and available as a web application.

Development and characterization of human T-cell receptor (TCR) alpha and beta clones' library as biological standards and resources for TCR sequencing and engineering

Characterization of T-cell receptors (TCRs) repertoire was revolutionized by next-generation sequencing technologies; however, standardization using biological controls to facilitate precision of current alignment and assembly tools remains a challenge. Additionally, availability of TCR libraries for off-the-shelf cloning and engineering TCR-specific T cells is a valuable resource for TCR-based immunotherapies. We established nine human TCR α and β clones that were evaluated using the 5'-rapid amplification of cDNA ends-like RNA-based TCR sequencing on the Illumina platform. TCR sequences were extracted and aligned using MiXCR, TRUST4, and CATT to validate their sensitivity and specificity and to validate library preparation methods. The correlation between actual and expected TCR ratios within libraries confirmed accuracy of the approach. Our findings established the development of biological standards and library of TCR clones to be leveraged in TCR sequencing and engineering. The remaining human TCR clones' libraries for a more diverse biological control will be generated.

Structure, function, and immunomodulation of the CD8 co-receptor

Expressed on the surface of CD8+ T cells, the CD8 co-receptor is a key component of the T cells that contributes to antigen recognition, immune cell maturation, and immune cell signaling. While CD8 is widely recognized as a co-stimulatory molecule for conventional CD8+ αβ T cells, recent reports highlight its multifaceted role in both adaptive and innate immune responses. In this review, we discuss the utility of CD8 in relation to its immunomodulatory properties. We outline the unique structure and function of different CD8 domains (ectodomain, hinge, transmembrane, cytoplasmic tail) in the context of the distinct properties of CD8αα homodimers and CD8αβ heterodimers. We discuss CD8 features commonly used to construct chimeric antigen receptors for immunotherapy. We describe the molecular interactions of CD8 with classical MHC-I, non-classical MHCs, and Lck partners involved in T cell signaling. Engineered and naturally occurring CD8 mutations that alter immune responses are discussed. The applications of anti-CD8 monoclonal antibodies (mABs) that target CD8 are summarized. Finally, we examine the unique structure and function of several CD8/mAB complexes. Collectively, these findings reveal the promising immunomodulatory properties of CD8 and CD8 binding partners, not only to uncover basic immune system function, but to advance efforts towards translational research for targeted immunotherapy.

Assessing the immunogenicity risk of salmon calcitonin peptide impurities using in silico and in vitro methods

Advances in synthetic peptide synthesis have enabled rapid and cost-effective peptide drug manufacturing. For this reason, peptide drugs that were first produced using recombinant DNA (rDNA) technology are now being produced using solid- and liquid-phase peptide synthesis. While peptide synthesis has some advantages over rDNA expression methods, new peptide-related impurities that differ from the active pharmaceutical ingredient (API) may be generated during synthesis. These impurity byproducts of the original peptide sequence feature amino acid insertions, deletions, and side-chain modifications that may alter the immunogenicity risk profile of the drug product. Impurities resulting from synthesis have become the special focus of regulatory review and approval for human use, as outlined in the FDA's Center for Drug Evaluation and Research guidance document, "ANDAs for Certain Highly Purified Synthetic Peptide Drug Products That Refer to Listed Drugs of rDNA Origin," published in 2021. This case study illustrates how in silico and in vitro methods can be applied to assess the immunogenicity risk of impurities that may be present in synthetic generic versions of the salmon calcitonin (SCT) drug product. Sponsors of generic drug abbreviated new drug applications (ANDAs) should consider careful control of these impurities (for example, keeping the concentration of the immunogenic impurities below the cut-off recommended by FDA regulators). Twenty example SCT impurities were analyzed using in silico tools and assessed as having slightly more or less immunogenic risk potential relative to the SCT API peptide. Class II human leukocyte antigen (HLA)-binding assays provided independent confirmation that a 9-mer sequence present in the C-terminus of SCT binds promiscuously to multiple HLA DR alleles, while T-cell assays confirmed the expected T-cell responses to SCT and selected impurities. In silico analysis combined with in vitro assays that directly compare the API to each individual impurity peptide may be a useful approach for assessing the potential immunogenic risk posed by peptide impurities that are present in generic drug products.

A structure-guided approach to predict MHC-I restriction of T cell receptors for public antigens

Peptides presented by class I major histocompatibility complex (MHC-I) proteins provide biomarkers for therapeutic targeting using T cell receptors (TCRs), TCR-mimicking antibodies (TMAs), or other engineered protein binders. Despite the extreme sequence diversity of the Human Leucocyte Antigen (HLA, the human MHC), a given TCR or TMA is restricted to recognize epitopic peptides in the context of a limited set of different HLA allotypes. Here, guided by our analysis of 96 TCR:pHLA complex structures in the Protein Data Bank (PDB), we identify TCR contact residues and classify 148 common HLA allotypes into T-cell cross-reactivity groups (T-CREGs) on the basis of their interaction surface features. Insights from our work have actionable value for resolving MHC-I restriction of TCRs, guiding therapeutic expansion of existing therapies, and informing the selection of peptide targets for forthcoming immunotherapy modalities.

Molecular basis for antibody recognition of multiple drug-peptide/MHC complexes

The HapImmuneTM platform exploits covalent inhibitors as haptens for creating major histocompatibility complex (MHC)-presented tumor-specific neoantigens by design, combining targeted therapies with immunotherapy for the treatment of drug-resistant cancers. A HapImmune antibody, R023, recognizes multiple sotorasib-conjugated KRAS(G12C) peptides presented by different human leukocyte antigens (HLAs). This high specificity to sotorasib, coupled with broad HLA-binding capability, enables such antibodies, when reformatted as T cell engagers, to potently and selectively kill sotorasib-resistant KRAS(G12C) cancer cells expressing different HLAs upon sotorasib treatment. The loosening of HLA restriction could increase the patient population that can benefit from this therapeutic approach. To understand the molecular basis for its unconventional binding capability, we used single-particle cryogenic electron microscopy to determine the structures of R023 bound to multiple sotorasib-peptide conjugates presented by different HLAs. R023 forms a pocket for sotorasib between the VH and VL domains, binds HLAs in an unconventional, angled way, with VL making most contacts with them, and makes few contacts with the peptide moieties. This binding mode enables the antibody to accommodate different hapten-peptide conjugates and to adjust its conformation to different HLAs presenting hapten-peptides. Deep mutational scanning validated the structures and revealed distinct levels of mutation tolerance by sotorasib- and HLA-binding residues. Together, our structural information and sequence landscape analysis reveal key features for achieving MHC-restricted recognition of multiple hapten-peptide antigens, which will inform the development of next-generation therapeutic antibodies.

Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?

T cells are essential immune cells responsible for identifying and eliminating pathogens. Through interactions between their T-cell antigen receptors (TCRs) and antigens presented by major histocompatibility complex molecules (MHCs) or MHC-like molecules, T cells discriminate foreign and self peptides. Determining the fundamental principles that govern these interactions has important implications in numerous medical contexts. However, reconstructing a map between T cells and their antagonist antigens remains an open challenge for the field of immunology, and success of in silico reconstructions of this relationship has remained incremental. In this Perspective, we discuss the role that new state-of-the-art deep-learning models for predicting protein structure may play in resolving some of the unanswered questions the field faces linking TCR and peptide-MHC properties to T-cell specificity. We provide a comprehensive overview of structural databases and the evolution of predictive models, and highlight the breakthrough AlphaFold provided the field.

T-cell virtuosity in ''knowing thyself"

Major Histocompatibility Complex (MHC) I and II and the αβ T-cell antigen receptor (TCRαβ) govern fundamental traits of adaptive immunity. They form a membrane-borne ligand-receptor system weighing host proteome integrity to detect contamination by nonself proteins. MHC-I and -II exhibit the "MHC-fold", which is able to bind a large assortment of short peptides as proxies for self and nonself proteins. The ensuing varying surfaces are mandatory ligands for Ig-like TCRαβ highly mutable binding sites. Conserved molecular signatures guide TCRαβ ligand binding sites to focus on the MHC-fold (MHC-restriction) while leaving many opportunities for its most hypervariable determinants to contact the peptide. This riveting molecular strategy affords many options for binding energy compatible with specific recognition and signalling aimed to eradicated microbial pathogens and cancer cells. While the molecular foundations of αβ T-cell adaptive immunity are largely understood, uncertainty persists on how peptide-MHC binding induces the TCRαβ signals that instruct cell-fate decisions. Solving this mystery is another milestone for understanding αβ T-cells' self/nonself discrimination. Recent developments revealing the innermost links between TCRαβ structural dynamics and signalling modality should help dissipate this long-sought-after enigma.

TCR sequencing: applications in immuno-oncology research

•T-cell receptor (TCR) interaction with major histocompatibility complex-antigen complexes leads to antitumour responses.•TCR sequencing analysis allows characterisation of T cells that recognise tumour neoantigens.•T-cell clonal revival and clonal replacement potentially underpin immunotherapy responses.

A class-mismatched TCR bypasses MHC restriction via an unorthodox but fully functional binding geometry

MHC restriction, which describes the binding of TCRs from CD4⁺ T cells to class II MHC proteins and TCRs from CD8⁺ T cells to class I MHC proteins, is a hallmark of immunology. Seemingly rare TCRs that break this paradigm exist, but mechanistic insight into their behavior is lacking. TIL1383I is a prototypical class-mismatched TCR, cloned from a CD4⁺ T cell but recognizing the tyrosinase tumor antigen presented by the class I MHC HLA-A2 in a fully functional manner. Here we find that TIL1383I binds this class I target with a highly atypical geometry. Despite unorthodox binding, TCR signaling, antigen specificity, and the ability to use CD8 are maintained. Structurally, a key feature of TIL1383I is an exceptionally long CDR3β loop that mediates functions that are traditionally performed separately by hypervariable and germline loops in canonical TCR structures. Our findings thus expand the range of known TCR binding geometries compatible with normal function and specificity, provide insight into the determinants of MHC restriction, and may help guide TCR selection and engineering for immunotherapy.

Structure of a fully assembled tumor-specific T cell receptor ligated by pMHC

The T cell receptor (TCR) expressed by T lymphocytes initiates protective immune responses to pathogens and tumors. To explore the structural basis of how TCR signaling is initiated when the receptor binds to peptide-loaded major histocompatibility complex (pMHC) molecules, we used cryogenic electron microscopy to determine the structure of a tumor-reactive TCRαβ/CD3δγε2ζ2 complex bound to a melanoma-specific human class I pMHC at 3.08 Å resolution. The antigen-bound complex comprises 11 subunits stabilized by multivalent interactions across three structural layers, with clustered membrane-proximal cystines stabilizing the CD3-εδ and CD3-εγ heterodimers. Extra density sandwiched between transmembrane helices reveals the involvement of sterol lipids in TCR assembly. The geometry of the pMHC/TCR complex suggests that efficient TCR scanning of pMHC requires accurate pre-positioning of T cell and antigen-presenting cell membranes. Comparisons of the ligand-bound and unliganded receptors, along with molecular dynamics simulations, indicate that TCRs can be triggered in the absence of spontaneous structural rearrangements.

Validation and promise of a TCR mimic antibody for cancer immunotherapy of hepatocellular carcinoma

Monoclonal antibodies are at the vanguard of the most promising cancer treatments. Whereas traditional therapeutic antibodies have been limited to extracellular antigens, T cell receptor mimic (TCRm) antibodies can target intracellular antigens presented by cell surface major histocompatibility complex (MHC) proteins. TCRm antibodies can therefore target a repertoire of otherwise undruggable cancer antigens. However, the consequences of off-target peptide/MHC recognition with engineered T cell therapies are severe, and thus there are significant safety concerns with TCRm antibodies. Here we explored the specificity and safety profile of a new TCRm-based T cell therapy for hepatocellular carcinoma (HCC), a solid tumor for which no effective treatment exists. We targeted an alpha-fetoprotein peptide presented by HLA-A*02 with a highly specific TCRm, which crystallographic structural analysis showed binds directly over the HLA protein and interfaces with the full length of the peptide. We fused the TCRm to the γ and δ subunits of a TCR, producing a signaling AbTCR construct. This was combined with an scFv/CD28 co-stimulatory molecule targeting glypican-3 for increased efficacy towards tumor cells. This AbTCR + co-stimulatory T cell therapy showed potent activity against AFP-positive cancer cell lines in vitro and an in an in vivo model and undetectable activity against AFP-negative cells. In an in-human safety assessment, no significant adverse events or cytokine release syndrome were observed and evidence of efficacy was seen. Remarkably, one patient with metastatic HCC achieved a complete remission after nine months and ultimately qualified for a liver transplant.

Immunogenicity and therapeutic targeting of a public neoantigen derived from mutated PIK3CA

Public neoantigens (NeoAgs) represent an elite class of shared cancer-specific epitopes derived from recurrently mutated driver genes. Here we describe a high-throughput platform combining single-cell transcriptomic and T cell receptor (TCR) sequencing to establish whether mutant PIK3CA, among the most frequently genomically altered driver oncogenes, generates an immunogenic public NeoAg. Using this strategy, we developed a panel of TCRs that recognize an endogenously processed neopeptide encompassing a common PIK3CA hotspot mutation restricted by the prevalent human leukocyte antigen (HLA)-A*03:01 allele. Mechanistically, immunogenicity to this public NeoAg arises from enhanced neopeptide/HLA complex stability caused by a preferred HLA anchor substitution. Structural studies indicated that the HLA-bound neopeptide presents a comparatively 'featureless' surface dominated by the peptide's backbone. To bind this epitope with high specificity and affinity, we discovered that a lead TCR clinical candidate engages the neopeptide through an extended interface facilitated by an unusually long CDR3β loop. In patients with diverse malignancies, we observed NeoAg clonal conservation and spontaneous immunogenicity to the neoepitope. Finally, adoptive transfer of TCR-engineered T cells led to tumor regression in vivo in mice bearing PIK3CA-mutant tumors but not wild-type PIK3CA tumors. Together, these findings establish the immunogenicity and therapeutic potential of a mutant PIK3CA-derived public NeoAg.

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.

Application of T cell receptor (TCR) repertoire analysis for the advancement of cancer immunotherapy

T cell receptor (TCR) sequencing has emerged as a powerful new technology in analysis of the host-tumour interaction. The advances in NextGen sequencing technologies, coupled with powerful novel bioinformatic tools, allow quantitative and reproducible characterisation of repertoires from tumour and blood samples from an increasing number of patients with a variety of solid cancers. In this review, we consider how global metrics such as T cell clonality and diversity can be extracted from these repertoires and used to give insight into the mechanism of action of immune checkpoint blockade. Furthermore, we explore how the analysis of TCR overlap between repertories can help define spatial and temporal heterogeneity of the anti-tumoural immune response. Finally, we review how analysis of TCR sequence and structure, either of individual TCRs or from sets of related TCRs can be used to annotate the antigenic specificity, with important implications for the development of personalised adoptive cellular immunotherapies.

Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes

The physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets.

An Engineered T Cell Receptor Variant Realizes the Limits of Functional Binding Modes

T cell receptors (TCRs) orchestrate cellular immunity by recognizing peptides presented by a range of major histocompatibility complex (MHC) proteins. Naturally occurring TCRs bind the composite peptide/MHC surface, recognizing peptides that are structurally and chemically compatible with the TCR binding site. Here we describe a molecularly evolved TCR variant that binds the human class I MHC protein HLA-A2 independent of the bound peptide, achieved by a drastic perturbation of the TCR binding geometry that places the molecule far from the peptide binding groove. This unique geometry is unsupportive of normal T cell signaling. A substantial divergence between affinity measurements in solution and in two dimensions between proximal cell membranes leads us to attribute the lack of signaling to steric hindrance that limits binding in the confines of a cell-cell interface. Our results provide an example of how receptor binding geometry can impact T cell function and provide further support for the view that germline-encoded residues in TCR binding loops evolved to drive productive TCR recognition and signaling.

Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen

Adoptive cell therapy (ACT) with tumor-specific T cells can mediate cancer regression. The main target of tumor-specific T cells are neoantigens arising from mutations in self-proteins. Although the majority of cancer neoantigens are unique to each patient, and therefore not broadly useful for ACT, some are shared. We studied oligoclonal T-cell receptors (TCRs) that recognize a shared neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by HLA-A2. Here we report structures of wild-type and mutant p53-HLA-A2 ligands, as well as structures of three tumor-specific TCRs bound to p53R175H-HLA-A2. These structures reveal how a driver mutation in p53 rendered a self-peptide visible to T cells. The TCRs employ structurally distinct strategies that are highly focused on the mutation to discriminate between mutant and wild-type p53. The TCR-p53R175H-HLA-A2 complexes provide a framework for designing TCRs to improve potency for ACT without sacrificing specificity.