TCR-induced alteration of primary MHC peptide anchor residue

Engineered allogeneic T cells decoupling T-cell-receptor and CD3 signalling enhance the antitumour activity of bispecific antibodies

Bispecific antibodies (biAbs) used in cancer immunotherapies rely on functional autologous T cells, which are often damaged and depleted in patients with haematological malignancies and in other immunocompromised patients. The adoptive transfer of allogeneic T cells from healthy donors can enhance the efficacy of biAbs, but donor T cells binding to host-cell antigens cause an unwanted alloreactive response. Here we show that allogeneic T cells engineered with a T-cell receptor that does not convert antigen binding into cluster of differentiation 3 (CD3) signalling decouples antigen-mediated T-cell activation from T-cell cytotoxicity while preserving the surface expression of the T-cell-receptor-CD3 signalling complex as well as biAb-mediated CD3 signalling and T-cell activation. In mice with CD19+ tumour xenografts, treatment with the engineered human cells in combination with blinatumomab (a clinically approved biAb) led to the recognition and clearance of tumour cells in the absence of detectable alloreactivity. Our findings support the development of immunotherapies combining biAbs and 'off-the-shelf' allogeneic T cells.

HLA A*24:02-restricted T cell receptors cross-recognize bacterial and preproinsulin peptides in type 1 diabetes

CD8+ T cells destroy insulin-producing pancreatic β cells in type 1 diabetes through HLA class I-restricted presentation of self-antigens. Combinatorial peptide library screening was used to produce a preferred peptide recognition landscape for a patient-derived T cell receptor (TCR) that recognized the preproinsulin-derived (PPI-derived) peptide sequence LWMRLLPLL in the context of disease risk allele HLA A*24:02. Data were used to generate a strong superagonist peptide, enabling production of an autoimmune HLA A*24:02-peptide-TCR structure by crystal seeding. TCR binding to the PPI epitope was strongly focused on peptide residues Arg4 and Leu5, with more flexibility at other positions, allowing the TCR to strongly engage many peptides derived from pathogenic bacteria. We confirmed an epitope from Klebsiella that was recognized by PPI-reactive T cells from 3 of 3 HLA A*24:02+ patients. Remarkably, the same epitope selected T cells from 7 of 8 HLA A*24+ healthy donors that cross-reacted with PPI, leading to recognition and killing of HLA A*24:02+ cells expressing PPI. These data provide a mechanism by which molecular mimicry between pathogen and self-antigens could have resulted in the breaking of self-tolerance to initiate disease.

Global analysis of T-cell groups reveals immunological features and common antigen targets of digestive tract tumors

BACKGROUND

T cells are key players in the tumor immune microenvironment (TIME), as they can recognize and eliminate cancer cells that express neoantigens derived from somatic mutations. However, the diversity and specificity of T-cell receptors (TCRs) that recognize neoantigens are largely unknown, due to the high variability of TCR sequences among individuals.

METHODS

To address this challenge, we applied GLIPH2, a novel algorithm that groups TCRs based on their predicted antigen specificity and HLA restriction, to cluster the TCR repertoire of 1,702 patients with digestive tract cancer. The patients were divided into five groups based on whether they carried tumor-infiltrating or clonal-expanded TCRs and calculated their TCR diversity. The prognosis, tumor subtype, gene mutation, gene expression, and immune microenvironment of these groups were compared. Viral specificity inference and immunotherapy relevance analysis performed for the TCR groups.

RESULTS

This approach reduced the complexity of TCR sequences to 249 clonally expanded and 150 tumor-infiltrating TCR groups, which revealed distinct patterns of TRBV usage, HLA association, and TCR diversity. In gastric adenocarcinoma (STAD), patients with tumor-infiltrating TCRs (Patients-TI) had significantly worse prognosis than other patients (Patients-nonTI). Patients-TI had richer CD8+ T cells in the immune microenvironment, and their gene expression features were positively correlated with immunotherapy response. We also found that tumor-infiltrating TCR groups were associated with four distinct tumor subtypes, 26 common gene mutations, and 39 gene expression signatures. We discovered that tumor-infiltrating TCRs had cross-reactivity with viral antigens, indicating a possible link between viral infections and tumor immunity.

CONCLUSION

By applying GLIPH2 to TCR sequences from digestive tract tumors, we uncovered novel insights into the tumor immune landscape and identified potential candidates for shared TCRs and neoantigens.

Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

Targeting of multiple tumor-associated antigens by individual T cell receptors during successful cancer immunotherapy

The T cells of the immune system can target tumors and clear solid cancers following tumor-infiltrating lymphocyte (TIL) therapy. We used combinatorial peptide libraries and a proteomic database to reveal the antigen specificities of persistent cancer-specific T cell receptors (TCRs) following successful TIL therapy for stage IV malignant melanoma. Remarkably, individual TCRs could target multiple different tumor types via the HLA A∗02:01-restricted epitopes EAAGIGILTV, LLLGIGILVL, and NLSALGIFST from Melan A, BST2, and IMP2, respectively. Atomic structures of a TCR bound to all three antigens revealed the importance of the shared x-x-x-A/G-I/L-G-I-x-x-x recognition motif. Multi-epitope targeting allows individual T cells to attack cancer in several ways simultaneously. Such "multipronged" T cells exhibited superior recognition of cancer cells compared with conventional T cell recognition of individual epitopes, making them attractive candidates for the development of future immunotherapies.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

A Novel Cell-based Luciferase Reporter Platform for the Development and Characterization of T-Cell Redirecting Therapies and Vaccine Development

T-cell immunotherapies are promising strategies to generate T-cell responses towards tumor-derived or pathogen-derived antigens. Adoptive transfer of T cells genetically modified to express antigen receptor transgenes has shown promise for the treatment of cancer. However, the development of T-cell redirecting therapies relies on the use of primary immune cells and is hampered by the lack of easy-to-use model systems and sensitive readouts to facilitate candidate screening and development. Particularly, testing T-cell receptor (TCR)-specific responses in primary T cells and immortalized T cells is confounded by the presence of endogenous TCR expression which results in mixed alpha/beta TCR pairings and compresses assay readouts. Herein, we describe the development of a novel cell-based TCR knockout (TCR-KO) reporter assay platform for the development and characterization of T-cell redirecting therapies. CRISPR/Cas9 was used to knockout the endogenous TCR chains in Jurkat cells stably expressing a human interleukin-2 promoter-driven luciferase reporter gene to measure TCR signaling. Reintroduction of a transgenic TCR into the TCR-KO reporter cells results in robust antigen-specific reporter activation compared with parental reporter cells. The further development of CD4/CD8 double-positive and double-negative versions enabled low-avidity and high-avidity TCR screening with or without major histocompatibility complex bias. Furthermore, stable TCR-expressing reporter cells generated from TCR-KO reporter cells exhibit sufficient sensitivity to probe in vitro T-cell immunogenicity of protein and nucleic acid-based vaccines. Therefore, our data demonstrated that TCR-KO reporter cells can be a useful tool for the discovery, characterization, and deployment of T-cell immunotherapy.

Therapeutic high affinity T cell receptor targeting a KRASG12D cancer neoantigen

Neoantigens derived from somatic mutations are specific to cancer cells and are ideal targets for cancer immunotherapy. KRAS is the most frequently mutated oncogene and drives the pathogenesis of several cancers. Here we show the identification and development of an affinity-enhanced T cell receptor (TCR) that recognizes a peptide derived from the most common KRAS mutant, KRASG12D, presented in the context of HLA-A*11:01. The affinity of the engineered TCR is increased by over one million-fold yet fully able to distinguish KRASG12D over KRASWT. While crystal structures reveal few discernible differences in TCR interactions with KRASWT versus KRASG12D, thermodynamic analysis and molecular dynamics simulations reveal that TCR specificity is driven by differences in indirect electrostatic interactions. The affinity enhanced TCR, fused to a humanized anti-CD3 scFv, enables selective killing of cancer cells expressing KRASG12D. Our work thus reveals a molecular mechanism that drives TCR selectivity and describes a soluble bispecific molecule with therapeutic potential against cancers harboring a common shared neoantigen.

CD8 T cell function and cross-reactivity explored by stepwise increased peptide-HLA versus TCR affinity

Recruitment and activation of CD8 T cells occur through specific triggering of T cell receptor (TCR) by peptide-bound human leucocyte antigen (HLA) ligands. Within the generated trimeric TCR-peptide:HLA complex, the molecular binding affinities between peptide and HLA, and between TCR and peptide:HLA both impact T cell functional outcomes. However, how their individual and combined effects modulate immunogenicity and overall T cell responsiveness has not been investigated systematically. Here, we established two panels of human tumor peptide variants differing in their affinity to HLA. For precise characterization, we developed the “blue peptide assay”, an upgraded cell-based approach to measure the peptide:HLA affinity. These peptide variants were then used to investigate the cross-reactivity of tumor antigen-specific CD8 T cell clonotypes derived from blood of cancer patients after vaccination with either the native or an affinity-optimized Melan-A/MART-1 epitope, or isolated from tumor infiltrated lymph nodes (TILNs). Vaccines containing the native tumor epitope generated T cells with better functionality, and superior cross-reactivity against potential low affinity escape epitopes, as compared to T cells induced by vaccines containing an HLA affinity-optimized epitope. Comparatively, Melan-A/MART-1-specific TILN cells displayed functional and cross-reactive profiles that were heterogeneous and clonotype-dependent. Finally, we took advantage of a collection of T cells expressing affinity-optimized NY-ESO-1-specific TCRs to interrogate the individual and combined impact of peptide:HLA and TCR-pHLA affinities on overall CD8 T cell responses. We found profound and distinct effects of both biophysical parameters, with additive contributions and absence of hierarchical dominance. Altogether, the biological impact of peptide:HLA and TCR-pHLA affinities on T cell responses was carefully dissected in two antigenic systems, frequently targeted in human cancer immunotherapy. Our technology and stepwise comparison open new insights into the rational design and selection of vaccine-associated tumor-specific epitopes and highlight the functional and cross-reactivity profiles that endow T cells with best tumor control capacity.

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.

Structure-guided stabilization of pathogen-derived peptide-HLA-E complexes using non-natural amino acids conserves native TCR recognition

The nonpolymorphic class Ib molecule, HLA-E, primarily presents peptides from HLA class Ia leader peptides, providing an inhibitory signal to NK cells via CD94/NKG2 interactions. Although peptides of pathogenic origin can also be presented by HLA-E to T cells, the molecular basis underpinning their role in antigen surveillance is largely unknown. Here, we solved a co-complex crystal structure of a TCR with an HLA-E presented peptide (pHLA-E) from bacterial (Mycobacterium tuberculosis) origin, and the first TCR-pHLA-E complex with a noncanonically presented peptide from viral (HIV) origin. The structures provided a molecular foundation to develop a novel method to introduce cysteine traps using non-natural amino acid chemistry that stabilized pHLA-E complexes while maintaining native interface contacts between the TCRs and different pHLA-E complexes. These pHLA-E monomers could be used to isolate pHLA-E-specific T cells, with obvious utility for studying pHLA-E restricted T cells, and for the identification of putative therapeutic TCRs.

In-silico design of peptides for inhibition of HLA-A*03-KLIETYFSK complex as a new drug design for treatment of multiples sclerosis disease

Multiple sclerosis is recognized as a chronic inflammatory disease. Human leukocyte antigen (HLA) plays an important role in initiating adaptive immune responses. HLA class I is present in almost all nucleated cells and presents the cleaved endogenous peptide antigens to cytotoxic T cells. HLA-A*03 is one of the HLA class I alleles, which is reported as substantially related HLA to MS disease. In 2011, the structure of the HLA-A*03 in complex was identified with an immunodominant proteolipid protein (PLP) epitope (KLIETYFSK). This complex has been reported as an important autoantigen-presenting complex in MS pathogenesis. In this study, new peptides were designed to bind to this complex that may prevent specific pathogenic cytotoxic T cell binding to this autoantigen-presenting complex and CNS demyelination. Herein, 14 new helical peptides containing 19 amino acids were designed and their structures were predicted using the PEP-FOLD server. The binding of each designed peptide to the mentioned complex was then performed. A mutation approach was used by the BeAtMuSiC server to improve the binding affinity of the designed peptide. In each position, amino acid substitutions leading to an increase in the binding affinity of the peptide to the mentioned complex were determined. Finally, the resulting complexes were simulated for 40 ns using AMBER18 software. The results revealed that out of 14 designed peptides, "WRYWWKDWAKQFRQFYRWF" peptide exhibited the highest affinity for binding to the mentioned complex. This peptide can be considered as a potential drug to control multiple sclerosis disease in patients carrying the HLA-A*03 allele.

Recent progress on MHC-I epitope prediction in tumor immunotherapy

Tumor immunotherapy has now become one of the most potential therapy for those intractable cancer diseases. The antigens on the cancer cell surfaces are the keys for the immune system to recognize and eliminate them. As reported, the immunogenicity of the tumor antigens could be determined by the binding between the key epitope peptides and MHC molecules. In recent years, the approaches to anticipate the peptides from the candidate epitopes have gradually changed into more efficient methods. Including the improved conventional methods, more diverse methods were coming into view. Here we review the anticipated methods of the tumor associated epitopes that specifically bind with major histocompatibility complex (MHC) class I molecules, and the recent advances and applications of those epitope prediction methods.

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 KD ∼ 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.

Genetic Bias, Diversity Indices, Physiochemical Properties and CDR3 Motifs Divide Auto-Reactive from Allo-Reactive T-Cell Repertoires

The distinct properties of allo-reactive T-cell repertoires are not well understood. To investigate whether auto-reactive and allo-reactive T-cell repertoires encoded distinct properties, we used dextramer enumeration, enrichment, single-cell T-cell receptor (TCR) sequencing and multiparameter analysis. We found auto-reactive and allo-reactive T-cells differed in mean ex vivo frequency which was antigen dependent. Allo-reactive T-cells showed clear differences in TCR architecture, with enriched usage of specific T-cell receptor variable (TRBJ) genes and broader use of T-cell receptor variable joining (TRBJ) genes. Auto-reactive T-cell repertoires exhibited complementary determining regions three (CDR3) lengths using a Gaussian distribution whereas allo-reactive T-cell repertoires exhibited distorted patterns in CDR3 length. CDR3 loops from allo-reactive T-cells showed distinct physical-chemical properties, tending to encode loops that were more acidic in charge. Allo-reactive T-cell repertoires differed in diversity metrics, tending to show increased overall diversity and increased homogeneity between repertoires. Motif analysis of CDR3 loops showed allo-reactive T-cell repertoires differed in motif preference which included broader motif use. Collectively, these data conclude that allo-reactive T-cell repertoires are indeed different to auto-reactive repertoires and provide tangible metrics for further investigations and validation. Given that the antigens studied here are overexpressed on multiple cancers and that allo-reactive TCRs often show increased ligand affinity, this new TCR bank also has translational potential for adoptive cell therapy, soluble TCR-based therapy and rational TCR design.

In silico approach of modified melanoma peptides and their immunotherapeutic potential

Melanoma is a type of skin cancer with increasing incidence worldwide and high lethality. Conventional forms of treatment are not effective in advanced cancer stages. Hence, immunotherapeutic approaches have been tested to modulate immune response against tumor cells. Some vaccine models using tumor-associated antigens (TAAs) such as glycoprotein 100 (gp100) have been studied, but their expected effectiveness has not been shown until now. Antigen immunogenicity is a crucial point to improve the immune response, and therefore mutations are inserted in peptide sequences. It is possible to understand the interactions which occur between peptides and immune system molecules through computer simulation, and this is essential in order to guide efficient vaccine models. In this work, we have calculated the interaction binding energies of crystallographic data based on modified gp100 peptides and HLA-A*0201 using density functional theory (DFT) and the molecular fractionation with conjugated caps (MFCC) approach. Our results show the most relevant residue-residue interactions, the impact of three mutations in their binding sites, and the main HLA-A*0201 amino acids for peptide-HLA binding.

Peptide Binding to HLA-E Molecules in Humans, Nonhuman Primates, and Mice Reveals Unique Binding Peptides but Remarkably Conserved Anchor Residues

Ag presentation via the nonclassical MHC class Ib molecule HLA-E, with nearly complete identity between the two alleles expressed in humans, HLA-E*01:01 and HLA-E*01:03, can lead to the activation of unconventional T cells in humans. Despite this virtual genetic monomorphism, differences in peptide repertoires binding to the two allelic variants have been reported. To further dissect and compare peptide binding to HLA-E*01:01 and HLA-E*01:03, we used an UV-mediated peptide exchange binding assay and an HPLC-based competition binding assay. In addition, we investigated binding of these same peptides to Mamu-E, the nonhuman primate homologue of human HLA-E, and to the HLA-E-like molecule Qa-1b in mice. We next exploited the differences and homologies in the peptide binding pockets of these four molecules to identify allele specific as well as common features of peptide binding motifs across species. Our results reveal differences in peptide binding preferences and intensities for each human HLA-E variant compared with Mamu-E and Qa-1b Using extended peptide libraries, we identified and refined the peptide binding motifs for each of the four molecules and found that they share main anchor positions, evidenced by conserved amino acid preferences across the four HLA-E molecules studied. In addition, we also identified differences in peptide binding motifs, which could explain the observed variations in peptide binding preferences and affinities for each of the four HLA-E-like molecules. Our results could help with guiding the selection of candidate pathogen-derived peptides with the capacity to target HLA-E-restricted T cells that could be mobilized in vaccination and immunotherapeutic strategies.

Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy

Immuno-oncology approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Additionally, we performed molecular dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiological binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addition of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive analysis of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.

T cell receptor interactions with human leukocyte antigen govern indirect peptide selectivity for the cancer testis antigen MAGE-A4

T cell-mediated immunity is governed primarily by T cell receptor (TCR) recognition of peptide-human leukocyte antigen (pHLA) complexes and is essential for immunosurveillance and disease control. This interaction is generally stabilized by interactions between the HLA surface and TCR germline-encoded complementarity-determining region (CDR) loops 1 and 2, whereas peptide selectivity is guided by direct interactions with the TCR CDR3 loops. Here, we solved the structure of a newly identified TCR in complex with a clinically relevant peptide derived from the cancer testis antigen melanoma antigen-A4 (MAGE-A4). The TCR bound pHLA in a position shifted toward the peptide's N terminus. This enabled the TCR to achieve peptide selectivity via an indirect mechanism, whereby the TCR sensed the first residue of the peptide through HLA residue Trp-167, which acted as a tunable gateway. Amino acid substitutions at peptide position 1 predicted to alter the HLA Trp-167 side-chain conformation abrogated TCR binding, indicating that this indirect binding mechanism is essential for peptide recognition. These findings extend our understanding of the molecular rules that underpin antigen recognition by TCRs and have important implications for the development of TCR-based therapies.

Synthesis and Biological Evaluation of Hapten-Clicked Analogues of The Antigenic Peptide Melan-A/MART-126(27L)-35

A click-chemistry-based approach was implemented to prepare peptidomimetics designed in silico and made from aromatic azides and a propargylated GIGI-mimicking platform derived from the altered Melan-A/MART-126(27L)-35 antigenic peptide ELAGIGILTV. The CuI -catalyzed Huisgen cycloaddition was carried out on solid support to generate rapidly a first series of peptidomimetics, which were evaluated for their capacity to dock at the interface between the major histocompatibility complex class-I (MHC-I) human leucocyte antigen (HLA)-A2 and T-cell receptors (TCRs). Despite being a weak HLA-A2 ligand, one of these 11 first synthetic compounds bearing a p-nitrobenzyl-triazole side chain was recognized by the receptor proteins of Melan-A/MART-1-specific T-cells. After modification of the N and C termini of this agonist, which was intended to enhance HLA-A2 binding, one of the resulting seven additional compounds triggered significant T-cell responses. Thus, these results highlight the capacity of naturally circulating human TCRs that are specific for the native Melan-A/MART-126-35 peptide to cross-react with peptidomimetics bearing organic motifs structurally different from the native central amino acids.

Peptide cargo tunes a network of correlated motions in human leucocyte antigens

Most biomolecular interactions are typically thought to increase the (local) rigidity of a complex, for example, in drug‐target binding. However, detailed analysis of specific biomolecular complexes can reveal a more subtle interplay between binding and rigidity. Here, we focussed on the human leucocyte antigen (HLA), which plays a crucial role in the adaptive immune system by presenting peptides for recognition by the αβ T‐cell receptor (TCR). The role that the peptide plays in tuning HLA flexibility during TCR recognition is potentially crucial in determining the functional outcome of an immune response, with obvious relevance to the growing list of immunotherapies that target the T‐cell compartment. We have applied high‐pressure/temperature perturbation experiments, combined with molecular dynamics simulations, to explore the drivers that affect molecular flexibility for a series of different peptide–HLA complexes. We find that different peptide sequences affect peptide–HLA flexibility in different ways, with the peptide cargo tuning a network of correlated motions throughout the pHLA complex, including in areas remote from the peptide‐binding interface, in a manner that could influence T‐cell antigen discrimination.

GPU-Accelerated Discovery of Pathogen-Derived Molecular Mimics of a T-Cell Insulin Epitope

The strong links between (Human Leukocyte Antigen) HLA, infection and autoimmunity combine to implicate T-cells as primary triggers of autoimmune disease (AD). T-cell crossreactivity between microbially-derived peptides and self-peptides has been shown to break tolerance and trigger AD in experimental animal models. Detailed examination of the potential for T-cell crossreactivity to trigger human AD will require means of predicting which peptides might be recognised by autoimmune T-cell receptors (TCRs). Recent developments in high throughput sequencing and bioinformatics mean that it is now possible to link individual TCRs to specific pathologies for the first time. Deconvolution of TCR function requires knowledge of TCR specificity. Positional Scanning Combinatorial Peptide Libraries (PS-CPLs) can be used to predict HLA-restriction and define antigenic peptides derived from self and pathogen proteins. In silico search of the known terrestrial proteome with a prediction algorithm that ranks potential antigens in order of recognition likelihood requires complex, large-scale computations over several days that are infeasible on a personal computer. We decreased the time required for peptide searching to under 30 min using multiple blocks on graphics processing units (GPUs). This time-efficient, cost-effective hardware accelerator was used to screen bacterial and fungal human pathogens for peptide sequences predicted to activate a T-cell clone, InsB4, that was isolated from a patient with type 1 diabetes and recognised the insulin B-derived epitope HLVEALYLV in the context of disease-risk allele HLA A*0201. InsB4 was shown to kill HLA A*0201⁺ human insulin producing β-cells demonstrating that T-cells with this specificity might contribute to disease. The GPU-accelerated algorithm and multispecies pathogen proteomic databases were validated to discover pathogen-derived peptide sequences that acted as super-agonists for the InsB4 T-cell clone. Peptide-MHC tetramer binding and surface plasmon resonance were used to confirm that the InsB4 TCR bound to the highest-ranked peptide agonists derived from infectious bacteria and fungi. Adoption of GPU-accelerated prediction of T-cell agonists has the capacity to revolutionise our understanding of AD by identifying potential targets for autoimmune T-cells. This approach has further potential for dissecting T-cell responses to infectious disease and cancer.