Cooperativity of hydrophobic anchor interactions: evidence for epitope selection by MHC class II as a folding process

Selection of vaccine-candidate peptides from Mycobacterium avium subsp. paratuberculosis by in silico prediction, in vitro T-cell line proliferation, and in vivo immunogenicity

Mycobacterium avium subspecies paratuberculosis (MAP) is a global concern in modern livestock production worldwide. The available vaccines against paratuberculosis do not offer optimal protection and interfere with the diagnosis of bovine tuberculosis. The aim of this study was to identify immunogenic MAP-specific peptides that do not interfere with the diagnosis of bovine tuberculosis. Initially, 119 peptides were selected by either (1) identifying unique MAP peptides that were predicted to bind to bovine major histocompatibility complex class II (MHC-predicted peptides) or (2) selecting hydrophobic peptides unique to MAP within proteins previously shown to be immunogenic (hydrophobic peptides). Subsequent testing of peptide-specific CD4+ T-cell lines from MAP-infected, adult goats vaccinated with peptides in cationic liposome adjuvant pointed to 23 peptides as being most immunogenic. These peptides were included in a second vaccine trial where three groups of eight healthy goat kids were vaccinated with 14 MHC-predicted peptides, nine hydrophobic peptides, or no peptides in o/w emulsion adjuvant. The majority of the MHC-predicted (93%) and hydrophobic peptides (67%) induced interferon-gamma (IFN-γ) responses in at least one animal. Similarly, 86% of the MHC-predicted and 89% of the hydrophobic peptides induced antibody responses in at least one goat. The immunization of eight healthy heifers with all 119 peptides formulated in emulsion adjuvant identified more peptides as immunogenic, as peptide specific IFN-γ and antibody responses in at least one heifer was found toward 84% and 24% of the peptides, respectively. No peptide-induced reactivity was found with commercial ELISAs for detecting antibodies against Mycobacterium bovis or MAP or when performing tuberculin skin testing for bovine tuberculosis. The vaccinated animals experienced adverse reactions at the injection site; thus, it is recommend that future studies make improvements to the vaccine formulation. In conclusion, immunogenic MAP-specific peptides that appeared promising for use in a vaccine against paratuberculosis without interfering with surveillance and trade tests for bovine tuberculosis were identified by in silico analysis and ex vivo generation of CD4+ T-cell lines and validated by the immunization of goats and cattle. Future studies should test different peptide combinations in challenge trials to determine their protective effect and identify the most MHC-promiscuous vaccine candidates.

PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements

T-cell specificity to differentiate between self and non-self relies on T-cell receptor (TCR) recognition of peptides presented by the Major Histocompatibility Complex (MHC). Investigations into the three-dimensional (3D) structures of peptide:MHC (pMHC) complexes have provided valuable insights of MHC functions. Given the limited availability of experimental pMHC structures and considerable diversity of peptides and MHC alleles, it calls for the development of efficient and reliable computational approaches for modeling pMHC structures. Here we present an update of PANDORA and the systematic evaluation of its performance in modelling 3D structures of pMHC class II complexes (pMHC-II), which play a key role in the cancer immune response. PANDORA is a modelling software that can build low-energy models in a few minutes by restraining peptide residues inside the MHC-II binding groove. We benchmarked PANDORA on 136 experimentally determined pMHC-II structures covering 44 unique αβ chain pairs. Our pipeline achieves a median backbone Ligand-Root Mean Squared Deviation (L-RMSD) of 0.42 Å on the binding core and 0.88 Å on the whole peptide for the benchmark dataset. We incorporated software improvements to make PANDORA a pan-allele framework and improved the user interface and software quality. Its computational efficiency allows enriching the wealth of pMHC binding affinity and mass spectrometry data with 3D models. These models can be used as a starting point for molecular dynamics simulations or structure-boosted deep learning algorithms to identify MHC-binding peptides. PANDORA is available as a Python package through Conda or as a source installation at https://github.com/X-lab-3D/PANDORA.

Structural Framework for Analysis of CD4+ T-Cell Epitope Dominance in Viral Fusion Proteins

Antigen conformation shapes CD4+ T-cell specificity through mechanisms of antigen processing, and the consequences for immunity may rival those from conformational effects on antibody specificity. CD4+ T cells initiate and control immunity to pathogens and cancer and are at least partly responsible for immunopathology associated with infection, autoimmunity, and allergy. The primary trigger for CD4+ T-cell maturation is the presentation of an epitope peptide in the MHC class II antigen-presenting protein (MHCII), most commonly on an activated dendritic cell, and then the T-cell responses are recalled by subsequent presentations of the epitope peptide by the same or other antigen-presenting cells. Peptide presentation depends on the proteolytic fragmentation of the antigen in an endosomal/lysosomal compartment and concomitant loading of the fragments into the MHCII, a multistep mechanism called antigen processing and presentation. Although the role of peptide affinity for MHCII has been well studied, the role of proteolytic fragmentation has received less attention. In this Perspective, we will briefly summarize evidence that antigen resistance to unfolding and proteolytic fragmentation shapes the specificity of the CD4+ T-cell response to selected viral envelope proteins, identify several remarkable examples in which the immunodominant CD4+ epitopes most likely depend on the interaction of processing machinery with antigen conformation, and outline how knowledge of antigen conformation can inform future efforts to design vaccines.

Evolution of SARS-CoV-2-specific CD4+ T cell epitopes

Vaccination clearly decreases coronavirus disease 2019 (COVID-19) mortality; however, they also impose selection pressure on the virus, which promotes the evolution of immune escape variants. For example, despite the high vaccination level in especially Western countries, the Omicron variant caused millions of breakthrough infections, suggesting that the highly mutated spike protein in the Omicron variant can escape antibody immunity much more efficiently than the other variants of concern (VOCs). In this study, we investigated the resistance/susceptibility of T helper cell responses that are necessary for generating efficient long-lasting antibody immunity, in several VOCs. By predicting T helper cell epitopes on the spike protein for most common HLA-DRB1 alleles worldwide, we found that although most of high frequency HLA-DRB1 alleles have several potential T helper cell epitopes, few alleles like HLA-DRB1 13:01 and 11:01 are not predicted to have any significant T helper cell responses after vaccination. Using these predictions, a population based on realistic human leukocyte antigen-II (HLA-II) frequencies were simulated to visualize the T helper cell immunity on the population level. While a small fraction of this population had alarmingly little predicted CD4 T cell epitopes, the majority had several epitopes that should be enough to generate efficient B cell responses. Moreover, we show that VOC spike mutations hardly affect T helper epitopes and mainly occur in other residues of the spike protein. These results suggest that lack of long-lasting antibody responses is not likely due to loss of T helper cell epitopes in new VOCs.

Loading dynamics of one SARS-CoV-2-derived peptide into MHC-II revealed by kinetic models

Major histocompatibility complex class II (MHC-II) plays an indispensable role in activating CD4+ T cell immune responses by presenting antigenic peptides on the cell surface for recognition by T cell receptors. The assembly of MHC-II and antigenic peptide is therefore a prerequisite for the antigen presentation. To date, however, the atomic-level mechanism underlying the peptide-loading dynamics for MHC-II is still elusive. Here, by constructing Markov state models based on extensive all-atom molecular dynamics simulations, we reveal the complete peptide-loading dynamics into MHC-II for one SARS-CoV-2 S-protein-derived antigenic peptide (235ITRFQTLLALHRSYL249). Our Markov state model identifies six metastable states (S1-S6) during the peptide-loading process and determines two dominant loading pathways. The peptide could potentially approach the antigen-binding groove via either its N- or C-terminus. Then, the consecutive insertion of several anchor residues into the binding pockets profoundly dictates the peptide-loading dynamics. Notably, the MHC-II αA52-E55 motif could guide the peptide loading into the antigen-binding groove via forming β-sheets conformation with the incoming peptide. The rate-limiting step, namely S5→S6, is mainly attributed to a considerable desolvation penalty triggered by the binding of the peptide C-terminus. Moreover, we further examined the conformational changes associated with the peptide exchange process catalyzed by the chaperon protein HLA-DM. A flipped-out conformation of MHC-II αW43 captured in S1-S3 is considered a critical anchor point for HLA-DM to modulate the structural dynamics. Our work provides deep structural insights into the key regulatory factors in MHC-II responsible for peptide recognition and guides future design for peptide vaccines against SARS-CoV-2.

SILVI, an open-source pipeline for T-cell epitope selection

High-throughput screening of available genomic data and identification of potential antigenic candidates have promoted the development of epitope-based vaccines and therapeutics. Several immunoinformatic tools are available to predict potential epitopes and other immunogenicity-related features, yet it is still challenging and time-consuming to compare and integrate results from different algorithms. We developed the R script SILVI (short for: from in silico to in vivo), to assist in the selection of the potentially most immunogenic T-cell epitopes from Human Leukocyte Antigen (HLA)-binding prediction data. SILVI merges and compares data from available HLA-binding prediction servers, and integrates additional relevant information of predicted epitopes, namely BLASTp alignments with host proteins and physical-chemical properties. The two default criteria applied by SILVI and additional filtering allow the fast selection of the most conserved, promiscuous, strong binding T-cell epitopes. Users may adapt the script at their discretion as it is written in open-source R language. To demonstrate the workflow and present selection options, SILVI was used to integrate HLA-binding prediction results of three example proteins, from viral, bacterial and parasitic microorganisms, containing validated epitopes included in the Immune Epitope Database (IEDB), plus the Human Papillomavirus (HPV) proteome. Applying different filters on predicted IC50, hydrophobicity and mismatches with host proteins allows to significantly reduce the epitope lists with favourable sensitivity and specificity to select immunogenic epitopes. We contemplate SILVI will assist T-cell epitope selections and can be continuously refined in a community-driven manner, helping the improvement and design of peptide-based vaccines or immunotherapies. SILVI development version is available at: github.com/JoanaPissarra/SILVI2020 and https://doi.org/10.5281/zenodo.6865909.

Computational mining of MHC class II epitopes for the development of universal immunogenic proteins

The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.

Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation

Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment.

HLA-DRB1 Alleles Associated with Lower Leishmaniasis Susceptibility Share Common Amino Acid Polymorphisms and Epitope Binding Repertoires

Susceptibility for leishmaniasis is largely dependent on host genetic and immune factors. Despite the previously described association of human leukocyte antigen (HLA) gene cluster variants as genetic susceptibility factors for leishmaniasis, little is known regarding the mechanisms that underpin these associations. To better understand this underlying functionality, we first collected all known leishmaniasis-associated HLA variants in a thorough literature review. Next, we aligned and compared the protection- and risk-associated HLA-DRB1 allele sequences. This identified several amino acid polymorphisms that distinguish protection- from risk-associated HLA-DRB1 alleles. Subsequently, T cell epitope binding predictions were carried out across these alleles to map the impact of these polymorphisms on the epitope binding repertoires. For these predictions, we used epitopes derived from entire proteomes of multiple Leishmania species. Epitopes binding to protection-associated HLA-DRB1 alleles shared common binding core motifs, mapping to the identified HLA-DRB1 amino acid polymorphisms. These results strongly suggest that HLA polymorphism, resulting in differential antigen presentation, affects the association between HLA and leishmaniasis disease development. Finally, we established a valuable open-access resource of putative epitopes. A set of 14 HLA-unrestricted strong-binding epitopes, conserved across species, was prioritized for further epitope discovery in the search for novel subunit-based vaccines.

Comparison of HLA ligand elution data and binding predictions reveals varying prediction performance for the multiple motifs recognized by HLA-DQ2.5

Binding prediction tools are commonly used to identify peptides presented on MHC class II molecules. Recently, a wealth of data in the form of naturally eluted ligands has become available and discrepancies between ligand elution data and binding predictions have been reported. Quantitative metrics for such comparisons are currently lacking. In this study, we assessed how efficiently MHC class II binding predictions can identify naturally eluted peptides, and investigated instances with discrepancies between the two methods in detail. We found that, in general, MHC class II eluted ligands are predicted to bind to their reported restriction element with high affinity. But, for several studies reporting an increased number of ligands that were not predicted to bind, we found that the reported MHC restriction was ambiguous. Additional analyses determined that most of the ligands predicted to not bind, are predicted to bind other co‐expressed MHC class II molecules. For selected alleles, we addressed discrepancies between elution data and binding predictions by experimental measurements and found that predicted and measured affinities correlate well. For DQA1*05:01/DQB1*02:01 (DQ2.5) however, binding predictions did miss several peptides that were determined experimentally to be binders. For these peptides and several known DQ2.5 binders, we determined key residues for conferring DQ2.5 binding capacity, which revealed that DQ2.5 utilizes two different binding motifs, of which only one is predicted effectively. These findings have important implications for the interpretation of ligand elution data and for the improvement of MHC class II binding predictions.

Role of ultraviolet mutational signature versus tumor mutation burden in predicting response to immunotherapy

Hydrophobic neoantigens are more immunogenic because they are better presented by the major histocompatibility complex and better recognized by T cells. Tumor cells can evade the immune response by expressing checkpoints such as programmed death ligand 1. Checkpoint blockade reactivates immune recognition and can be effective in diseases such as melanoma, which harbors a high tumor mutational burden (TMB). Cancers presenting low or intermediate TMB can also respond to checkpoint blockade, albeit less frequently, suggesting the need for biological markers predicting response. We calculated the hydrophobicity of neopeptides produced by probabilistic in silico simulation of the genomic UV exposure mutational signature. We also computed the hydrophobicity of potential neopeptides and extent of UV exposure based on the UV mutational signature enrichment (UVMSE) score in The Cancer Genome Atlas (TCGA; N = 3543 tumors), and in our cohort of 151 immunotherapy‐treated patients. In silico simulation showed that UV exposure significantly increased hydrophobicity of neopeptides, especially over multiple mutagenic cycles. There was also a strong correlation (R² = 0.953) between weighted UVMSE and hydrophobicity of neopeptides in TCGA melanoma patients. Importantly, UVMSE was able to predict better response (P = 0.0026), progression‐free survival (P = 0.036), and overall survival (P = 0.052) after immunotherapy in patients with low/intermediate TMB, but not in patients with high TMB. We show that higher UVMSE scores could be a useful predictor of better immunotherapy outcome, especially in patients with low/intermediate TMB, likely due to increased hydrophobicity (and hence immunogenicity) of neopeptides.

Rapid Detection of Avian Influenza Virus by Fluorescent Diagnostic Assay using an Epitope-Derived Peptide

Currently, the point of care testing (POCT) is not fully developed for subtype-specific avian influenza virus detection. In this study, an H5N1 hemaglutinin 1 (HA1) epitope (P0: KPNDAINF) and three modified peptides (P1: KPNTAINF, P2: KPNGAINF, P3: KPNDAINDAINF) were evaluated as POCT elements for rapid detection of avian influenza virus. Based on modeling predictions by Autodock Vina, binding affinity varied depending on alteration of one amino acid in these peptides. The binding energy of P2 indicated its potential for a strong interaction with HA. Fluorescence-linked immunosorbent assay experimentally demonstrated the interaction between these peptides and virus. The four peptides interacted with HA1 of H5N3 with different binding affinities with P2 showing the strongest binding affinity. When P0 and P2 peptides were used in rapid fluorescent immunochromatographic test (FICT) as detection elements, the inter-assay coefficients of variation (CV) indicated that P2-linked FICT was more acceptable than the P0-linked FICT in the presence of human specimens. Antibody pair-linked FICT was influenced by clinical samples more than the P2-linked FICT assay, which showed a 4-fold improvement in the detection limit of H5N3 and maintained H5 subtype-specificity. Compared to the rapid diagnostic test (RDT) which is not specific for influenza subtypes, P2-linked FICT could increase virus detection. In conclusion, results of this study suggest that HA epitope-derived peptides can be used as alternatives to antibodies for a rapid fluorescent diagnostic assay to detect avian influenza virus.

Enhanced Detection of Antigen-Specific CD4+ T Cells Using Altered Peptide Flanking Residue Peptide-MHC Class II Multimers

Fluorochrome-conjugated peptide-MHC (pMHC) class I multimers are staple components of the immunologist's toolbox, enabling reliable quantification and analysis of Ag-specific CD8(+) T cells irrespective of functional outputs. In contrast, widespread use of the equivalent pMHC class II (pMHC-II) reagents has been hindered by intrinsically weaker TCR affinities for pMHC-II, a lack of cooperative binding between the TCR and CD4 coreceptor, and a low frequency of Ag-specific CD4(+) T cell populations in the peripheral blood. In this study, we show that peptide flanking regions, extending beyond the central nonamer core of MHC-II-bound peptides, can enhance TCR-pMHC-II binding and T cell activation without loss of specificity. Consistent with these findings, pMHC-II multimers incorporating peptide flanking residue modifications proved superior for the ex vivo detection, characterization, and manipulation of Ag-specific CD4(+) T cells, highlighting an unappreciated feature of TCR-pMHC-II interactions.

The Thermodynamic Mechanism of Peptide-MHC Class II Complex Formation Is a Determinant of Susceptibility to HLA-DM

Peptides bind MHC class II molecules through a thermodynamically nonadditive process consequent to the flexibility of the reactants. Currently, how the specific outcome of this binding process affects the ensuing epitope selection needs resolution. Calorimetric assessment of binding thermodynamics for hemagglutinin 306-319 peptide variants to the human MHC class II HLA-DR1 (DR1) and a mutant DR1 reveals that peptide/DR1 complexes can be formed with different enthalpic and entropic contributions. Complexes formed with a smaller entropic penalty feature circular dichroism spectra consistent with a non-compact form, and molecular dynamics simulation shows a more flexible structure. The opposite binding mode, compact and less flexible, is associated with greater entropic penalty. These structural variations are associated with rearrangements of residues known to be involved in HLA-DR (DM) binding, affinity of DM for the complex, and complex susceptibility to DM-mediated peptide exchange. Thus, the thermodynamic mechanism of peptide binding to DR1 correlates with the structural rigidity of the complex, and DM mediates peptide exchange by "sensing" flexible complexes in which the aforementioned residues are rearranged at a higher frequency than in more rigid ones.

Susceptibility to HLA-DM protein is determined by a dynamic conformation of major histocompatibility complex class II molecule bound with peptide

HLA-DM mediates the exchange of peptides loaded onto MHCII molecules during antigen presentation by a mechanism that remains unclear and controversial. Here, we investigated the sequence and structural determinants of HLA-DM interaction. Peptides interacting nonoptimally in the P1 pocket exhibited low MHCII binding affinity and kinetic instability and were highly susceptible to HLA-DM-mediated peptide exchange. These changes were accompanied by conformational alterations detected by surface plasmon resonance, SDS resistance assay, antibody binding assay, gel filtration, dynamic light scattering, small angle x-ray scattering, and NMR spectroscopy. Surprisingly, all of those changes could be reversed by substitution of the P9 pocket anchor residue. Moreover, MHCII mutations outside the P1 pocket and the HLA-DM interaction site increased HLA-DM susceptibility. These results indicate that a dynamic MHCII conformational determinant rather than P1 pocket occupancy is the key factor determining susceptibility to HLA-DM-mediated peptide exchange and provide a molecular mechanism for HLA-DM to efficiently target unstable MHCII-peptide complexes for editing and exchange those for more stable ones.

An unstable Th epitope of P. falciparum fosters central memory T cells and anti-CS antibody responses

Malaria is transmitted by Plasmodium-infected anopheles mosquitoes. Widespread resistance of mosquitoes to insecticides and resistance of parasites to drugs highlight the urgent need for malaria vaccines. The most advanced malaria vaccines target sporozoites, the infective form of the parasite. A major target of the antibody response to sporozoites are the repeat epitopes of the circumsporozoite (CS) protein, which span almost one half of the protein. Antibodies to these repeats can neutralize sporozoite infectivity. Generation of protective antibody responses to the CS protein (anti-CS Ab) requires help by CD4 T cells. A CD4 T cell epitope from the CS protein designated T* was previously identified by screening T cells from volunteers immunized with irradiated P. falciparum sporozoites. The T* sequence spans twenty amino acids that contains multiple T cell epitopes restricted by various HLA alleles. Subunit malaria vaccines including T* are highly immunogenic in rodents, non-human primates and humans. In this study we characterized a highly conserved HLA-DRβ1*04:01 (DR4) restricted T cell epitope (QNT-5) located at the C-terminus of T*. We found that a peptide containing QNT-5 was able to elicit long-term anti-CS Ab responses and prime CD4 T cells in HLA-DR4 transgenic mice despite forming relatively unstable MHC-peptide complexes highly susceptible to HLA-DM editing. We attempted to improve the immunogenicity of QNT-5 by replacing the P1 anchor position with an optimal tyrosine residue. The modified peptide QNT-Y formed stable MHC-peptide complexes highly resistant to HLA-DM editing. Contrary to expectations, a linear peptide containing QNT-Y elicited almost 10-fold lower long-term antibody and IFN-γ responses compared to the linear peptide containing the wild type QNT-5 sequence. Some possibilities regarding why QNT-5 is more effective than QNT-Y in inducing long-term T cell and anti-CS Ab when used as vaccine are discussed.

Analysis of genomic characters reveals that four distinct gene clusters are correlated with different functions in Burkholderia cenocepacia AU 1054

Possessing three circular chromosomes is a distinct genomic characteristic of Burkholderia cenocepacia AU 1054, a clinically important pathogen in cystic fibrosis. In this study, base composition, codon usage and functional role category were analyzed in the B. cenocepacia AU 1054 genome. Although no bias in the base and codon usage was detected between any two chromosomes, function differences did exist in the genes of each chromosome. Similar base composition and differential functional role categories indicated that genes on these three chromosomes were relatively stable and that a proper division of labor was established. Based on variations in the base or codon usage, four small gene clusters were observed in all of the genes. Multivariate analysis revealed that protein hydrophobicity played a predominant role in shaping base usage bias, while horizontal gene transfer and the gene expression level were the two most important factors that affected the codon usage bias. Interestingly, we also found that these gene clusters were correlated with different biological functions: (i) 45 pyrimidine-leading-codon preferred genes were predominantly involved in regulatory function; (ii) most drug resistance-related genes involved in 826 genes that coding for hydrophobic proteins; (iii) most of the 111 horizontal transfer genes were responsible for genomic plasticity; and (iv) 73 highly expressed genes (predicted by their codon adaptation index values) showed environmental adaptation to cystic fibrosis. Our results showed that genes with base or codon usage bias were affected by mutational pressure and natural selection, and their functions could contribute to drug assistance and transmissible activity in B. cenocepacia.

Thermodynamics of Peptide-MHC Class II Interactions: Not all Complexes are Created Equal

The adaptive immune response begins when CD4+ T cells recognize antigenic peptides bound to class II molecules of the Major Histocompatibility Complex (MHCII). The interaction between peptides and MHCII has been historically interpreted as a rigid docking event. However, this model has been challenged by the evidence that conformational flexibility plays an important role in peptide-MHCII complex formation. Thermodynamic analysis of the binding reaction suggests a model of complexation in which the physical-chemical nature of the peptide determines the variability in flexibility of the substates in the peptide-MHC conformational ensemble. This review discusses our understanding of the correlation between thermodynamics of peptide binding and structural features of the resulting complex as well as their impact on HLA-DM activity and on our ability to predict MHCII-restricted epitopes.

Molecular dynamics simulations to provide insights into epitopes coupled to the soluble and membrane-bound MHC-II complexes

Epitope recognition by major histocompatibility complex II (MHC-II) is essential for the activation of immunological responses to infectious diseases. Several studies have demonstrated that this molecular event takes place in the MHC-II peptide-binding groove constituted by the α and β light chains of the heterodimer. This MHC-II peptide-binding groove has several pockets (P1-P11) involved in peptide recognition and complex stabilization that have been probed through crystallographic experiments and in silico calculations. However, most of these theoretical calculations have been performed without taking into consideration the heavy chains, which could generate misleading information about conformational mobility both in water and in the membrane environment. Therefore, in absence of structural information about the difference in the conformational changes between the peptide-free and peptide-bound states (pMHC-II) when the system is soluble in an aqueous environment or non-covalently bound to a cell membrane, as the physiological environment for MHC-II is. In this study, we explored the mechanistic basis of these MHC-II components using molecular dynamics (MD) simulations in which MHC-II was previously co-crystallized with a small epitope (P₇) or coupled by docking procedures to a large (P₂₂) epitope. These MD simulations were performed at 310 K over 100 ns for the water-soluble (MHC-II_w, MHC-II-P_7w, and MHC-II-P_22w) and 150 ns for the membrane-bound species (MHC-II_m, MHC-II-P_7m, and MHC-II-P_22m). Our results reveal that despite the different epitope sizes and MD simulation environments, both peptides are stabilized primarily by residues lining P1, P4, and P6-7, and similar noncovalent intermolecular energies were observed for the soluble and membrane-bound complexes. However, there were remarkably differences in the conformational mobility and intramolecular energies upon complex formation, causing some differences with respect to how the two peptides are stabilized in the peptide-binding groove.

For many but not for all: how the conformational flexibility of the peptide/MHCII complex shapes epitope selection

The adaptive immune response starts when CD4+ T cells recognize peptide antigens presented by class II molecules of the Major Histocompatibility Complex (MHCII). Two outstanding features of MHCII molecules are their polymorphism and the ability of each allele to bind a large panoply of peptides. The ability of each MHCII molecule to interact with a limited, though broad, range of amino acid sequences, or "permissive specificity" of binding, is the result of structural flexibility. This flexibility has been identified through biochemical and biophysical studies, and molecular dynamic simulations have modeled the conformational rearrangements that the peptide and the MHCII undergo during interaction. Moreover, there is evidence that the structural flexibility of the peptide/MHCII complex correlates with the activity of the "peptide-editing" molecule DM. In light of the impact that these recent findings have on our ability to predict MHCII epitopes, a review of the structural and thermodynamic determinants of peptide binding to MHCII is proposed.

Structural mimicry between SLA/LP and Rickettsia surface antigens as a driver of autoimmune hepatitis: insights from an in silico study

BACKGROUND

Autoimmune hepatitis (AIH) is a chronic, progressive liver disease, characterized by continuing hepatocellular inflammation and necrosis. A subgroup of AIH patients presents specific autoantibodies to soluble liver antigen/liver-pancreas (SLA/LP) protein, which is regarded as a highly specific diagnostic marker. Autoantigenic SLA/LP peptides are targeted by CD4+ T cells, and restricted by the allele HLA-DRB1*03:01, which confers disease susceptibility in Europeans and Americans. A positively charged residue at position 71 has been indicated as critical for AIH susceptibility in all of the HLA alleles identified to date. Though the exact molecular mechanisms underlying pathogenesis of AIH are not clear, molecular mimicry between SLA/LP and viral/bacterial antigens has been invoked.

METHODS

The immunodominant region of SLA/LP was used as query in databank searches to identify statistically significant similarities with viral/bacterial peptides. Homology modeling and docking was used to investigate the potential interaction of HLA-DRB1*03:01 with the identified peptides. By molecular mechanics means, the interactions and energy of binding at the HLA binding site was also scrutinized.

RESULTS

A statistically significant structural similarity between the immunodominant regions of SLA/LP and a region of the surface antigen PS 120 from Rickettsia spp. has been detected. The interaction of the SLA/LP autoepitope and the corresponding Rickettsia sequence with the allele HLA-DRB1*03:01 has been simulated. The obtained results predict for both peptides a similar binding mode and affinity to HLA-DRB1*03:01. A "hot spot" of interaction between HLA-DRB1*03:01 and PS 120 is located at the P4 binding pocket, and is represented by a salt bridge involving Lys at position 71 of the HLA protein, and Glu 795 of PS120 peptide.

CONCLUSIONS

These findings strongly support the notion that a molecular mimicry mechanism can trigger AIH onset. CD4+ T cells recognizing peptides of SLA/LP could indeed cross-react with foreign Rickettsia spp. antigens. Finally, the same analysis suggests a molecular explanation for the importance of position 71 in conferring the susceptibility of the allele HLA-DRB1*03:01 to AIH. The lack of a positive charge at such position could prevent HLA alleles from binding the foreign peptides and triggering the molecular mimicry event.

Differential binding of pyruvate dehydrogenase complex-E2 epitopes by DRB1*08:01 and DRB1*11:01 Is predicted by their structural motifs and correlates with disease risk

DRB1*08:01 (DR0801) and DRB1*11:01 (DR1101) are highly homologous alleles that have opposing effects on susceptibility to primary biliary cirrhosis (PBC). DR0801 confers risk and shares a key feature with other HLA class II alleles that predispose to autoimmunity: a nonaspartic acid at beta57. DR1101 is associated with protection from PBC, and its sequence includes an aspartic acid at beta57. To elucidate a mechanism for the opposing effects of these HLA alleles on PBC susceptibility, we compared the features of epitopes presented by DR0801 and DR1101. First, we identified DR0801- and DR1101-restricted epitopes within multiple viral Ags, observing both shared and distinct epitopes. Because DR0801 is not well characterized, we deduced its motif by measuring binding affinities for a library of peptides, confirming its key features through structural modeling. DR0801 was distinct from DR1101 in its ability to accommodate charged residues within all but one of its binding pockets. In particular, DR0801 strongly preferred acidic residues in pocket 9. These findings were used to identify potentially antigenic sequences within PDC-E2 (an important hepatic autoantigen) that contain a DR0801 motif. Four peptides bound to DR0801 with reasonable affinity, but only one of these bound to DR1101. Three peptides, PDC-E2145-159, PDC-E2(249-263), and PDC-E2(629-643), elicited high-affinity T cell responses in DR0801 subjects, implicating these as likely autoreactive specificities. Therefore, the unique molecular features of DR0801 may lead to the selection of a distinct T cell repertoire that contributes to breakdown of self-tolerance in primary biliary cirrhosis, whereas those of DR1101 promote tolerance.

HLA-DM: arbiter conformationis

The recognition by CD4(+) T cells of peptides bound to class II MHC (MHCII) molecules expressed on the surface of antigen-presenting cells is a key step in the initiation of an adaptive immune response. Presentation of peptides is the outcome of an intracellular selection process occurring in dedicated endosomal compartments involving, among others, an MHCII-like molecule named HLA-DM (DM). The impact of DM on the epitope selection machinery has been known for more than 15 years. However, the mechanism by which DM skews the presented repertoire in favour of kinetically stable complexes has remained elusive. Here, a review of the most recent observations in the field is presented, pointing to the possibility that DM decides the survival of a peptide-MHCII complex (pMHCII) on the basis of its conformational flexibility, which is a function of the 'tightness' of interaction between the peptide and the MHCII at a specific region of the binding site.

Conformational variation in structures of classical and non-classical MHCII proteins and functional implications

Recent structural characterizations of classical and non-classical major histocompatibility complex class II (MHCII) proteins have provided a view into the dynamic nature of the MHCII-peptide binding groove and the role that structural changes play in peptide loading processes. Although there have been numerous reports of crystal structures for MHCII-peptide complexes, a detailed analysis comparing all the structures has not been reported, and subtle conformational variations present in these structures may not have been fully appreciated. We compared the 91 MHCII crystal structures reported in the PDB to date, including an HLA-DR mutant particularly susceptible to DM-mediated peptide exchange, and reviewed experimental and computational studies of the effect of peptide binding on MHCII structure. These studies provide evidence for conformational lability in and around the α-subunit 3-10 helix at residues α48-51, a region known to be critical for HLA-DM-mediated peptide exchange. A biophysical study of MHC-peptide hydrogen bond strengths and a recent structure of the non-classical MHCII protein HLA-DO reveal changes in the same region. Conformational variability was observed also in the vicinity of a kink in the β-subunit helical region near residue β66 and in the orientation and loop conformation in the β2 Ig domain. Here, we provide an overview of the regions within classical and non-classical MHCII proteins that display conformational changes and the potential role that these changes may have in the peptide loading/exchange process.

Structural and functional analysis of multi-interface domains

A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of proteins have the multi-interface property, however the involved multi-interface domains account for only a tiny fraction (1.8%) of the total number of domains. The interfaces of these domains are distinguishable in terms of their fingerprints, indicating the functional specificity of the multiple interfaces in a domain. Furthermore, we observed that both cooperative and distinctive structural patterns, which will be useful for protein engineering, exist in the multiple interfaces of a domain.

A Peptide/MHCII conformer generated in the presence of exchange peptide is substrate for HLA-DM editing

The mechanism of HLA-DM (DM) activity is still unclear. We have shown that DM-mediated peptide release from HLA-DR (DR) is dependent on the presence of exchange peptide. However, DM also promotes a small amount of peptide release in the absence of exchange peptide. Here we show that SDS-PAGE separates purified peptide/DR1 complexes (pDR1) into two conformers whose ratio is peptide K(d)-dependent. In the absence of exchange peptide, DM only releases peptide from the slower migrating conformer. Addition of exchange peptide converts the DM-resistant conformer to the slower migrating conformer, which is DM labile. Thus, exchange peptide generates a conformer of pDR1 which constitutes the intermediate for peptide exchange and the substrate for DM activity. The resolution of the intermediate favors the highest affinity peptide. However, once folded into the DM-resistant conformer, even low affinity peptides can be presented in the absence of free peptide, broadening the repertoire available for presentation.

Enthalpy-entropy compensation and cooperativity as thermodynamic epiphenomena of structural flexibility in ligand-receptor interactions

Ligand binding is a thermodynamically cooperative process in many biochemical systems characterized by the conformational flexibility of the reactants. However, the contribution of conformational entropy to cooperativity of ligation needs to be elucidated. Here, we perform kinetic and thermodynamic analyses on a panel of cycle-mutated peptides, derived from influenza H3 HA(306-319), interacting with wild type and a mutant HLA-DR. We observe that, within a certain range of peptide affinity, this system shows isothermal entropy-enthalpy compensation (iEEC). The incremental increases in conformational entropy measured as disruptive mutations are added in the ligand or receptor are more than sufficient in magnitude to account for the experimentally observed lack of free-energy decrease cooperativity. Beyond this affinity range, compensation is not observed, and therefore, the ability of the residual interactions to form a stable complex decreases in an exponential fashion. Taken together, our results indicate that cooperativity and iEEC constitute the thermodynamic epiphenomena of the structural fluctuation that accompanies ligand-receptor complex formation in flexible systems. Therefore, ligand binding affinity prediction needs to consider how each source of binding energy contributes synergistically to the folding and kinetic stability of the complex in a process based on the trade-off between structural tightening and restraint of conformational mobility.

Prediction of the binding affinities of peptides to class II MHC using a regularized thermodynamic model

Background

The binding of peptide fragments of extracellular peptides to class II MHC is a crucial event in the adaptive immune response. Each MHC allotype generally binds a distinct subset of peptides and the enormous number of possible peptide epitopes prevents their complete experimental characterization. Computational methods can utilize the limited experimental data to predict the binding affinities of peptides to class II MHC.

Results

We have developed the Regularized Thermodynamic Average, or RTA, method for predicting the affinities of peptides binding to class II MHC. RTA accounts for all possible peptide binding conformations using a thermodynamic average and includes a parameter constraint for regularization to improve accuracy on novel data. RTA was shown to achieve higher accuracy, as measured by AUC, than SMM-align on the same data for all 17 MHC allotypes examined. RTA also gave the highest accuracy on all but three allotypes when compared with results from 9 different prediction methods applied to the same data. In addition, the method correctly predicted the peptide binding register of 17 out of 18 peptide-MHC complexes. Finally, we found that suboptimal peptide binding registers, which are often ignored in other prediction methods, made significant contributions of at least 50% of the total binding energy for approximately 20% of the peptides.

Conclusions

The RTA method accurately predicts peptide binding affinities to class II MHC and accounts for multiple peptide binding registers while reducing overfitting through regularization. The method has potential applications in vaccine design and in understanding autoimmune disorders. A web server implementing the RTA prediction method is available at http://bordnerlab.org/RTA/.

Cutting edge: HLA-DM-mediated peptide exchange functions normally on MHC class II-peptide complexes that have been weakened by elimination of a conserved hydrogen bond

The mechanism by which HLA-DM (DM) promotes exchange of peptides bound to HLA-DR (DR) is still unclear. We have shown that peptide interaction with DR1 can be considered a folding process as evidenced by cooperativity. However, in DM-mediated ligand exchange, prebound peptide release is noncooperative, which could be a function of the breaking of a critical interaction. The hydrogen bond (H-bond) between beta-chain His(81) and the peptide backbone at the -1 position is a candidate for such a target. In this study, we analyze the exchange of peptides bound to a DR1 mutant in which formation of this H-bond is impaired. We observe that DM still functions normally. However, as expected of a cooperative model, this H-bond contributes to the overall energetics of the complex and its disruption impacts the ability of the exchange ligand to fold with the binding groove into a stable complex.

Cutting edge: HLA-DM functions through a mechanism that does not require specific conserved hydrogen bonds in class II MHC-peptide complexes

HLA-DM catalyzes peptide dissociation and exchange in class II MHC molecules through a mechanism that has been proposed to involve the disruption of specific components of the conserved hydrogen bond network in MHC-peptide complexes. HLA-DR1 molecules with alanine substitutions at each of the six conserved H- bonding positions were expressed in cells, and susceptibility to DM catalytic activity was evaluated by measuring the release of CLIP. The mutants alphaN62A, alphaN69A, alphaR76A, and betaH81A DR1 were fully susceptible to DM-mediated CLIP release, and betaN82A resulted in spontaneous release of CLIP. Using recombinant soluble DR1 molecules, the amino acid betaN82 was observed to contribute disproportionately in stabilizing peptide complexes. Remarkably, the catalytic potency of DM with each beta-chain mutant was equal to or greater than that observed with wild-type DR1. Our results support the conclusion that no individual component of the conserved hydrogen bond network plays an essential role in the DM catalytic mechanism.

The binding of antigenic peptides to HLA-DR is influenced by interactions between pocket 6 and pocket 9

Peptide binding to class II MHC protein is commonly viewed as a combination of discrete anchor residue preferences for pockets 1, 4, 6/7, and 9. However, previous studies have suggested cooperative effects during the peptide binding process. Investigation of the DRB1*0901 binding motif demonstrated a clear interaction between peptide binding pockets 6 and 9. In agreement with prior studies, pockets 1 and 4 exhibited clear binding preferences. Previously uncharacterized pockets 6 and 7 accommodated a wide variety of residues. However, although it was previously reported that pocket 9 is completely permissive, several substitutions at this position were unable to bind. Structural modeling revealed a probable interaction between pockets 6 and 9 through beta9Lys. Additional binding studies with doubly substituted peptides confirmed that the amino acid bound within pocket 6 profoundly influences the binding preferences for pocket 9 of DRB1*0901, causing complete permissiveness of pocket 9 when a small polar residue is anchored in pocket 6 but accepting relatively few residues when a basic residue is anchored in pocket 6. The beta9Lys residue is unique to DR9 alleles. However, similar studies with doubly substituted peptides confirmed an analogous interaction effect for DRA1/B1*0301, a beta9Glu allele. Accounting for this interaction resulted in improved epitope prediction. These findings provide a structural explanation for observations that an amino acid in one pocket can influence binding elsewhere in the MHC class II peptide binding groove.

HLA-DM mediates epitope selection by a "compare-exchange" mechanism when a potential peptide pool is available

Background

HLA-DM (DM) mediates exchange of peptides bound to MHC class II (MHCII) during the epitope selection process. Although DM has been shown to have two activities, peptide release and MHC class II refolding, a clear characterization of the mechanism by which DM facilitates peptide exchange has remained elusive.

Methodology/Principal Findings

We have previously demonstrated that peptide binding to and dissociation from MHCII in the absence of DM are cooperative processes, likely related to conformational changes in the peptide-MHCII complex. Here we show that DM promotes peptide release by a non-cooperative process, whereas it enhances cooperative folding of the exchange peptide. Through electron paramagnetic resonance (EPR) and fluorescence polarization (FP) we show that DM releases prebound peptide very poorly in the absence of a candidate peptide for the exchange process. The affinity and concentration of the candidate peptide are also important for the release of the prebound peptide. Increased fluorescence energy transfer between the prebound and exchange peptides in the presence of DM is evidence for a tetramolecular complex which resolves in favor of the peptide that has superior folding properties.

Conclusion/Significance

This study shows that both the peptide releasing activity on loaded MHCII and the facilitating of MHCII binding by a candidate exchange peptide are integral to DM mediated epitope selection. The exchange process is initiated only in the presence of candidate peptides, avoiding possible release of a prebound peptide and loss of a potential epitope. In a tetramolecular transitional complex, the candidate peptides are checked for their ability to replace the pre-bound peptide with a geometry that allows the rebinding of the original peptide. Thus, DM promotes a “compare-exchange” sorting algorithm on an available peptide pool. Such a “third party”-mediated mechanism may be generally applicable for diverse ligand recognition in other biological systems.

Three dimensional structure directs T-cell epitope dominance associated with allergy

BACKGROUND

CD4+ T-cell epitope immunodominance is not adequately explained by peptide selectivity in class II major histocompatibility proteins, but it has been correlated with adjacent segments of conformational flexibility in several antigens.

METHODS

The published T-cell responses to two venom allergens and two aeroallergens were used to construct profiles of epitope dominance, which were correlated with the distribution of conformational flexibility, as measured by crystallographic B factors, solvent-accessible surface, COREX residue stability, and sequence entropy.

RESULTS

Epitopes associated with allergy tended to be excluded from and lie adjacent to flexible segments of the allergen.

CONCLUSION

During the initiation of allergy, the N- and/or C-terminal ends of proteolytic processing intermediates were preferentially loaded into antigen presenting proteins for the priming of CD4+ T cells.

Genomic analysis of Ovis aries (Ovar) MHC class IIa loci

Determining the genomic organization of the Ovis aries (Ovar) major histocompatibility complex class IIa region is essential for future functional studies related to antigen presentation. In this study, a bacterial artificial chromosome (BAC) library of genomic DNA from peripheral blood leukocytes (PBL) of a Rambouillet ram was constructed, and BAC clone consisting of the major histocompatibility complex (MHC) class II DQB2, DQA2, DQB1, DQA1, and DRB1 loci was identified and completely sequenced. The BAC clone consists of 160,889 bp of finished sequence with the loci arranged in the following order: DQB2, DQA2, DQB1, DQA1, and DRB1 with 14.3, 25, 6.6, and 40.9 Kb spanning between the loci, respectively. All five of these loci were transcribed in the animal used to generate the MHC class II BAC clone. Repeat or retrotransposable elements along with MHC class II cis promoter elements consisting of S, X, and Y boxes were identified in the sequence. In addition, 16 non-coding conserved sequences amongst primates, carnivores, and ruminants were identified (p < 0.001). These conserved sequences include binding sites for transcription factors with known roles in immune cells, and they provide a basis for further functional investigation of the genes in this region. This is the first ruminant finished sequence of the DQB2-DRB1 region, and this sequence information will aid in whole genome and transcriptome analyses of MHC class II.