MHC class II complexes sample intermediate states along the peptide exchange pathway

Structural insights into human MHC-II association with invariant chain

The loading of processed peptides on to major histocompatibility complex II (MHC-II) molecules for recognition by T cells is vital to cell-mediated adaptive immunity. As part of this process, MHC-II associates with the invariant chain (Ii) during biosynthesis in the endoplasmic reticulum to prevent premature peptide loading and to serve as a scaffold for subsequent proteolytic processing into MHC-II-CLIP. Cryo-electron microscopy structures of full-length Human Leukocyte Antigen-DR (HLA-DR) and HLA-DQ complexes associated with Ii, resolved at 3.0 to 3.1 Å, elucidate the trimeric assembly of the HLA/Ii complex and define atomic-level interactions between HLA, Ii transmembrane domains, loop domains, and class II-associated invariant chain peptides (CLIP). Together with previous structures of MHC-II peptide loading intermediates DO and DM, our findings complete the structural path governing class II antigen presentation.

MHC-II dynamics are maintained in HLA-DR allotypes to ensure catalyzed peptide exchange

Presentation of antigenic peptides by major histocompatibility complex class II (MHC-II) proteins determines T helper cell reactivity. The MHC-II genetic locus displays a large degree of allelic polymorphism influencing the peptide repertoire presented by the resulting MHC-II protein allotypes. During antigen processing, the human leukocyte antigen (HLA) molecule HLA-DM (DM) encounters these distinct allotypes and catalyzes exchange of the placeholder peptide CLIP by exploiting dynamic features of MHC-II. Here, we investigate 12 highly abundant CLIP-bound HLA-DRB1 allotypes and correlate dynamics to catalysis by DM. Despite large differences in thermodynamic stability, peptide exchange rates fall into a target range that maintains DM responsiveness. A DM-susceptible conformation is conserved in MHC-II molecules, and allosteric coupling between polymorphic sites affects dynamic states that influence DM catalysis. As exemplified for rheumatoid arthritis, we postulate that intrinsic dynamic features of peptide-MHC-II complexes contribute to the association of individual MHC-II allotypes with autoimmune disease.

Incorporating the Molecular Mimicry of Environmental Antigens into the Causality of Autoimmune Hepatitis

Molecular mimicry between foreign and self-antigens has been implicated as a cause of autoimmune hepatitis in experimental models and cross-reacting antibodies in patients. This review describes the experimental and clinical evidence for molecular mimicry as a cause of autoimmune hepatitis, indicates the limitations and uncertainties of this premise, and encourages investigations that assess diverse environmental antigens as sources of disease-relevant molecular mimics. Pertinent articles were identified in PubMed using multiple search phrases. Several pathogens have linear or conformational epitopes that mimic the self-antigens of autoimmune hepatitis. The occurrence of an acute immune-mediated hepatitis after vaccination for severe acute respiratory syndrome (SARS)-associated coronavirus 2 (SARS-CoV-2) has suggested that vaccine-induced peptides may mimic disease-relevant tissue antigens. The intestinal microbiome is an under-evaluated source of gut-derived antigens that could also engage in molecular mimicry. Chaperone molecules may enhance the pathogenicity of molecular mimics, and they warrant investigation. Molecular mimics of immune dominant epitopes within cytochrome P450 IID6, the autoantigen most closely associated with autoimmune hepatitis, should be sought in diverse environmental antigens and assessed for pathogenicity. Avoidance strategies, dietary adjustments, vaccine improvement, and targeted manipulation of the intestinal microbiota may emerge as therapeutic possibilities. In conclusion, molecular mimicry may be a missing causality of autoimmune hepatitis. Molecular mimics of key immune dominant epitopes of disease-specific antigens must be sought in diverse environmental antigens. The ubiquity of molecular mimicry compels rigorous assessments of peptide mimics for immunogenicity and pathogenicity in experimental models. Molecular mimicry may complement epigenetic modifications as causative mechanisms of autoimmune hepatitis.

The mode of action of tapasin on major histocompatibility class I (MHC-I) molecules

Tapasin (Tsn) plays a critical role in antigen processing and presentation by major histocompatibility complex class I (MHC-I) molecules. The mechanism of Tsn-mediated peptide loading and exchange hinges on the conformational dynamics governing the interaction of Tsn and MHC-I with recent structural and functional studies pinpointing the critical sites of direct or allosteric regulation. In this review, we highlight these recent findings and relate them to the extensive molecular and cellular data that are available for these evolutionary interdependent proteins. Furthermore, allotypic differences of MHC-I with regard to the editing and chaperoning function of Tsn are reviewed and related to the mechanistic observations. Finally, evolutionary aspects of the mode of action of Tsn will be discussed, a short comparison with the Tsn-related molecule TAPBPR (Tsn-related protein) will be given, and the impact of Tsn on noncanonical MHC-I molecules will be described.

HIV-1-Infected CD4+ T Cells Present MHC Class II-Restricted Epitope via Endogenous Processing

HIV-1-specific CD4⁺ T cells (T_CD4+s) play a critical role in controlling HIV-1 infection. Canonically, T_CD4+s are activated by peptides derived from extracellular ("exogenous") Ags displayed in complex with MHC class II (MHC II) molecules on the surfaces of "professional" APCs such as dendritic cells (DCs). In contrast, activated human T_CD4+s, which express MHC II, are not typically considered for their APC potential because of their low endocytic capacity and the exogenous Ag systems historically used for assessment. Using primary T_CD4+s and monocyte-derived DCs from healthy donors, we show that activated human T_CD4+s are highly effective at MHC II-restricted presentation of an immunodominant HIV-1-derived epitope postinfection and subsequent noncanonical processing and presentation of endogenously produced Ag. Our results indicate that, in addition to marshalling HIV-1-specific immune responses during infection, T_CD4+s also act as APCs, leading to the activation of HIV-1-specific T_CD4+s.

Association of HLA-DM and HLA class II Genes with Antibody Response Induced by Inactivated Japanese Encephalitis Vaccine

HLA (HLA) class II molecules, HLA-DR, DP, and DQ, together with HLA II-like protein DM, play a dominant role in the processing and presentation of antigens, which may influence vaccine effectiveness. We previously demonstrated that variations in the HLA-DRB1, DPB1, and DQB1 genes may affect the neutralising antibody (NAb) response induced by the inactivated Japanese encephalitis vaccine (IJEV). In the present study, we genotyped HLA-DPA1, DQA1, DMA, and DMB genes and used previous HLA-DRB1, DPB1, and DQB1 data to evaluate the association of these genes with IJEV-induced NAbs, at both the seroconversion and geometric mean titres (GMTs). We confirmed the seropositive association of DQB1*02:01 and NAbs (0.156 vs. 0.075, Padj = 0.018; OR = 2.270; 95% CI = 1.285-3.999) and seronegative association of DQB1*02:02 (0.014 vs. 0.09, Padj = 0.0002; OR = 0.130; 95% CI = 0.047-0.400). Furthermore, the DMB*01:03-DMA*01:01-DPA1*01:03-DPB1*04:01 haplotype was associated with a negative response (0.020 vs. 0.074; Padj = 0.03; OR = 0.250; 95% CI = 0.097-0.649), whereas DRB1*15:02-DMB*01:01-DMA*01:01 was associated with a positive response (0.034 vs. 0; Padj = 0.044). In addition, DRB1*12:02, DRB1*13:02, DPB1*04:01, DPB1*05:01, DPB1*09:01, DQA1*06:01, and DQA1*01:02 were associated with a higher GMT of NAbs, whereas DRB1*11:01, DPB1*13:01, and DQA1*05:05 were associated with a lower GMT of NAbs. In conclusion, the present study suggests that variations in the HLA-DM and HLA class II genes, as well as their combined allotypes, may influence the IJEV NAbs at seroconversion and GMT levels. This article is protected by copyright. All rights reserved.

Dynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen-major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

Sortase-Mediated Multi-Fragment Assemblies by Ligation Site Switching

Sortase‐mediated ligation (SML) is a powerful tool of protein chemistry allowing the ligation of peptides containing LPxTG sorting motifs and N‐terminal glycine nucleophiles. The installation of a sorting motif into the product prohibits the assembly of multiple fragments by SML. Here we report multi‐fragment SML based on switchable sortase substrates. Substitution of the Leu residue by disulfide‐containing Cys(StBu) results in active sorting motifs, which are inactivatable by reduction. In combination with a photo‐protected N‐Gly nucleophile, multi‐fragment SML is enabled by repetitive cycles of SML and ligation site switching. The feasibility of this approach was demonstrated by a proof‐of‐concept four‐fragment ligation, the assembly of peptide probes for bivalent chromatin binding proteins and oligomerization of peptide antigens. Biochemical and immuno‐assays demonstrated functionality of these probes rendering them promising tools for immunology and chromatin biochemistry.

Partnering for the major histocompatibility complex class II and antigenic determinant requires flexibility and chaperons

Cytotoxic, or helper T cells recognize antigen via T cell receptors (TCRs) that can see their target antigen as short sequences of peptides bound to the groove of proteins of major histocompatibility complex (MHC) class I, and class II respectively. For MHC class II epitope selection from exogenous pathogens or self-antigens, participation of several accessory proteins, molecular chaperons, processing enzymes within multiple vesicular compartments is necessary. A major contributing factor is the MHC class II structure itself that uniquely offers a dynamic and flexible groove essential for epitope selection. In this review, I have taken a historical perspective focusing on the flexibility of the MHC II molecules as the driving force in determinant selection and interactions with the accessory molecules in antigen processing, HLA-DM and HLA-DO.

Major histocompatibility complex (MHC) class I and class II proteins: impact of polymorphism on antigen presentation

The major histocompatibility complex (MHC) loci are amongst the most polymorphic regions in the genomes of vertebrates. In the human population, thousands of MHC gene variants (alleles) exist that translate into distinct allotypes equipped with overlapping but unique peptide binding profiles. Understanding the differential structural and dynamic properties of MHC alleles and their interaction with critical regulators of peptide exchange bears the potential for more personalized strategies of immune modulation in the context of HLA-associated diseases.

The dominantly expressed class II molecule from a resistant MHC haplotype presents only a few Marek's disease virus peptides by using an unprecedented binding motif

Viral diseases pose major threats to humans and other animals, including the billions of chickens that are an important food source as well as a public health concern due to zoonotic pathogens. Unlike humans and other typical mammals, the major histocompatibility complex (MHC) of chickens can confer decisive resistance or susceptibility to many viral diseases. An iconic example is Marek's disease, caused by an oncogenic herpesvirus with over 100 genes. Classical MHC class I and class II molecules present antigenic peptides to T lymphocytes, and it has been hard to understand how such MHC molecules could be involved in susceptibility to Marek's disease, given the potential number of peptides from over 100 genes. We used a new in vitro infection system and immunopeptidomics to determine peptide motifs for the 2 class II molecules expressed by the MHC haplotype B2, which is known to confer resistance to Marek's disease. Surprisingly, we found that the vast majority of viral peptide epitopes presented by chicken class II molecules arise from only 4 viral genes, nearly all having the peptide motif for BL2*02, the dominantly expressed class II molecule in chickens. We expressed BL2*02 linked to several Marek's disease virus (MDV) peptides and determined one X-ray crystal structure, showing how a single small amino acid in the binding site causes a crinkle in the peptide, leading to a core binding peptide of 10 amino acids, compared to the 9 amino acids in all other reported class II molecules. The limited number of potential T cell epitopes from such a complex virus can explain the differential MHC-determined resistance to MDV, but raises questions of mechanism and opportunities for vaccine targets in this important food species, as well as providing a basis for understanding class II molecules in other species including humans.

Impact of Structural Observables From Simulations to Predict the Effect of Single-Point Mutations in MHC Class II Peptide Binders

The prediction of peptide binders to Major Histocompatibility Complex (MHC) class II receptors is of great interest to study autoimmune diseases and for vaccine development. Most approaches predict the affinities using sequence-based models trained on experimental data and multiple alignments from known peptide substrates. However, detecting activity differences caused by single-point mutations is a challenging task. In this work, we used interactions calculated from simulations to build scoring matrices for quickly estimating binding differences by single-point mutations. We modelled a set of 837 peptides bound to an MHC class II allele, and optimized the sampling of the conformations using the Rosetta backrub method by comparing the results to molecular dynamics simulations. From the dynamic trajectories of each complex, we averaged and compared structural observables for each amino acid at each position of the 9°mer peptide core region. With this information, we generated the scoring-matrices to predict the sign of the binding differences. We then compared the performance of the best scoring-matrix to different computational methodologies that range in computational costs. Overall, the prediction of the activity differences caused by single mutated peptides was lower than 60% for all the methods. However, the developed scoring-matrix in combination with existing methods reports an increase in the performance, up to 86% with a scoring method that uses molecular dynamics.

Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes

Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide-MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide-MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide-MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.

Impact of HLA-DR Antigen Binding Cleft Rigidity on T Cell Recognition

The interaction between T cell receptor (TCR) and peptide (p)-Human Leukocyte Antigen (HLA) complexes is the critical first step in determining T cell responses. X-ray crystallographic studies of pHLA in TCR-bound and free states provide a structural perspective that can help understand T cell activation. These structures represent a static “snapshot”, yet the nature of pHLAs and their interactions with TCRs are highly dynamic. This has been demonstrated for HLA class I molecules with in silico techniques showing that some interactions, thought to stabilise pHLA-I, are only transient and prone to high flexibility. Here, we investigated the dynamics of HLA class II molecules by focusing on three allomorphs (HLA-DR1, -DR11 and -DR15) that are able to present the same epitope and activate CD4+ T cells. A single TCR (F24) has been shown to recognise all three HLA-DR molecules, albeit with different affinities. Using molecular dynamics and crystallographic ensemble refinement, we investigate the molecular basis of these different affinities and uncover hidden roles for HLA polymorphic residues. These polymorphisms were responsible for the widening of the antigen binding cleft and disruption of pHLA-TCR interactions, underpinning the hierarchy of F24 TCR binding affinity, and ultimately T cell activation. We expanded this approach to all available pHLA-DR structures and discovered that all HLA-DR molecules were inherently rigid. Together with in vitro protein stability and peptide affinity measurements, our results suggest that HLA-DR1 possesses inherently high protein stability, and low HLA-DM susceptibility.

Revisiting nonclassical HLA II functions in antigen presentation: Peptide editing and its modulation

The nonclassical major histocompatibility complex of class II molecules (ncMHCII) HLA-DM (DM) and HLA-DO (DO) feature essential functions for the selection of the peptides that are displayed by classical MHCII proteins (MHCII) for CD4⁺ T_h cell surveillance. Thus, although the binding groove of classical MHCII dictates the main features of the peptides displayed, ncMHCII function defines the preferential loading of peptides from specific cellular compartments and the extent to which they are presented. DM acts as a chaperone for classical MHCII molecules facilitating peptide exchange and thereby favoring the binding of peptide-MHCII complexes of high kinetic stability mostly in late endosomal compartments. DO on the other hand binds to DM blocking its peptide-editing function in B cells and thymic epithelial cells, limiting DM activity in these cellular subsets. DM and DO distinct expression patterns therefore define specific antigen presentation profiles that select unique peptide pools for each set of antigen presenting cell. We have come a long way understanding the mechanistic underpinnings of such distinct editing profiles and start to grasp the implications for ncMHCII biological function. DM acts as filter for the selection of immunodominant, pathogen-derived epitopes while DO blocks DM activity under certain physiological conditions to promote tolerance to self. Interestingly, recent findings have shown that the unexplored and neglected ncMHCII genetic diversity modulates retroviral infection in mouse, and affects human ncMHCII function. This review aims at highlighting the importance of ncMHCII function for CD4⁺ T_h cell responses while integrating and evaluating what could be the impact of distinct editing profiles because of natural genetic variations.

HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy

PURPOSE

HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures.

METHODS

Here we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization.

RESULTS

To illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles.

CONCLUSION

These workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development.

PySFD: comprehensive molecular insights from significant feature differences detected among many simulated ensembles

Motivation

Many modeling analyses of molecular dynamics (MD) simulations are based on a definition of states that can be (groups of) clusters of simulation frames in a feature space composed of molecular coordinates. With increasing dimension of this feature space (due to the increasing size or complexity of a simulated molecule), it becomes very difficult to cluster the underlying MD data and estimate a statistically robust model. To mitigate this “curse of dimensionality”, one can reduce the feature space, e.g., with principal component or time-lagged independent component analysis transformations, focusing the analysis on the most important modes of transitions. In practice, however, all these reduction strategies may neglect important molecular details that are susceptible to experimental verification.

Results

To recover such molecular details, I have developed PySFD (Significant Feature Differences analyzer for Python), a multi-processing software package that efficiently selects significantly different features of any user-defined feature type among potentially many different simulated state ensembles, such as meta-stable states of a Markov State Model (MSM). Applying PySFD on MSMs of an aggregate of 300 microseconds MD simulations recently performed on the major histocompatibility complex class II (MHCII) protein, I demonstrate how this toolkit can extract and visualize valuable mechanistic information from big MD simulation data, e.g., in form of networks of dynamic interaction changes connecting functionally relevant sites of a protein complex.

Availability and implementation

PySFD is freely available under the L-GPL license at https://github.com/markovmodel/PySFD.

Supplementary information

Supplementary data are available at Bioinformatics online.

CD4+ Th immunogenicity of the Ascaris spp. secreted products

Ascaris spp. is a major health problem of humans and animals alike, and understanding the immunogenicity of its antigens is required for developing urgently needed vaccines. The parasite-secreted products represent the most relevant, yet complex (>250 proteins) antigens of Ascaris spp. as defining the pathogen-host interplay. We applied an in vitro antigen processing system coupled to quantitative proteomics to identify potential CD4⁺ T_h cell epitopes in Ascaris-secreted products. This approach considerably restricts the theoretical list of epitopes using conventional CD4⁺ T_h cell epitope prediction tools. We demonstrate the specificity and utility of our approach on two sets of candidate lists, allowing us identifying hits excluded by either one or both computational methods. More importantly, one of the candidates identified experimentally, clearly demonstrates the presence of pathogen-reactive T cells in healthy human individuals against these antigens. Thus, our work pipeline identifies the first human T cell epitope against Ascaris spp. and represents an easily adaptable platform for characterization of complex antigens, in particular for those pathogens that are not easily amenable for in vivo experimental validation.

Distinct editing functions of natural HLA-DM allotypes impact antigen presentation and CD4+ T cell activation

Classical human leukocyte antigen (HLA) molecules of the major histocompatibility class II (MHCII) complex present peptides for the development, surveillance and activation of CD4+ T cells. The nonclassical MHCII-like protein HLA-DM (DM) catalyzes the exchange and loading of peptides onto MHCII molecules, thereby shaping MHCII immunopeptidomes. Natural variations of DM in both chains of the protein (DMA and DMB) have been hypothesized to impact peptide presentation, but no evidence for altered function has been reported. Here we define the presence of DM allotypes in human populations covered by the 1000 Genomes Project and probe their activity. The functional properties of several allotypes are investigated and show strong enhancement of peptide-induced T cell activation for a particular combination of DMA and DMB. Biochemical evidence suggests a broader pH activity profile for the new variant relative to that of the most commonly expressed DM allotype. Immunopeptidome analysis indicates that the compartmental activity of the new DM heterodimer extends beyond the late endosome and suggests that the natural variation of DM has profound effects on adaptive immunity when antigens bypass the canonical processing pathway.

HLA-DM catalytically enhances peptide dissociation by sensing peptide-MHC class II interactions throughout the peptide-binding cleft

Human leukocyte antigen-DM (HLA-DM) is an integral component of the major histocompatibility complex class II (MHCII) antigen-processing and -presentation pathway. HLA-DM shapes the immune system by differentially catalyzing peptide exchange on MHCII molecules, thereby editing the peptide-MHCII (pMHCII) repertoire by imposing a bias on the foreign and self-derived peptide cargos that are presented on the cell surface for immune surveillance and tolerance induction by CD4⁺ T cells. To better understand DM selectivity, here we developed a real-time fluorescence anisotropy assay to delineate the pMHCII intrinsic stability, DM-binding affinity, and catalytic turnover, independent kinetic parameters of HLA-DM enzymatic activity. We analyzed prominent pMHCII contacts by differentiating the kinetic parameters in pMHCII homologs, observing that peptide interactions throughout the MHCII-binding cleft influence both the rate of peptide dissociation from the DM-pMHCII catalytic complex and the binding affinity of HLA-DM for a pMHCII. We show that the intrinsic stability of a pMHCII linearly correlates with DM catalytic turnover, but is nonlinearly correlated with its binding affinity. Surprisingly, interactions at the peptides N terminus up to and including MHCII position one (P1) anchor affected the catalytic turnover, suggesting that the active DM-pMHCII catalytic complex operates on pMHCII complexes with full peptide occupancy. Furthermore, interactions at the peptide C terminus modulated DM-binding affinity, suggesting distal communication between peptide interactions with the MHCII and the DM-pMHCII binding interface. Our results imply an intimate linkage between the DM-pMHCII interface and peptide-MHCII interactions throughout the peptide-binding cleft.

Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations

Predicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors.

Dynamically Driven Allostery in MHC Proteins: Peptide-Dependent Tuning of Class I MHC Global Flexibility

T cell receptor (TCR) recognition of antigenic peptides bound and presented by class I major histocompatibility complex (MHC) proteins underlies the cytotoxic immune response to diseased cells. Crystallographic structures of TCR-peptide/MHC complexes have demonstrated how TCRs simultaneously interact with both the peptide and the MHC protein. However, it is increasingly recognized that, beyond serving as a static platform for peptide presentation, the physical properties of class I MHC proteins are tuned by different peptides in ways that are not always structurally visible. These include MHC protein motions, or dynamics, which are believed to influence interactions with a variety of MHC-binding proteins, including not only TCRs, but other activating and inhibitory receptors as well as components of the peptide loading machinery. Here, we investigated the mechanisms by which peptides tune the dynamics of the common class I MHC protein HLA-A2. By examining more than 50 lengthy molecular dynamics simulations of HLA-A2 presenting different peptides, we identified regions susceptible to dynamic tuning, including regions in the peptide binding domain as well as the distal α3 domain. Further analyses of the simulations illuminated mechanisms by which the influences of different peptides are communicated throughout the protein, and involve regions of the peptide binding groove, the β₂-microglobulin subunit, and the α3 domain. Overall, our results demonstrate that the class I MHC protein is a highly tunable peptide sensor whose physical properties vary considerably with bound peptide. Our data provides insight into the underlying principles and suggest a role for dynamically driven allostery in the immunological function of MHC proteins.

Quantitative comparison of adaptive sampling methods for protein dynamics

Adaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. In this work, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a priori knowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.

The Role of Molecular Flexibility in Antigen Presentation and T Cell Receptor-Mediated Signaling

Antigen presentation is a cellular process that involves a number of steps, beginning with the production of peptides by proteolysis or aberrant synthesis and the delivery of peptides to cellular compartments where they are loaded on MHC class I (MHC-I) or MHC class II (MHC-II) molecules. The selective loading and editing of high-affinity immunodominant antigens is orchestrated by molecular chaperones: tapasin/TAP-binding protein, related for MHC-I and HLA-DM for MHC-II. Once peptide/MHC (pMHC) complexes are assembled, following various steps of quality control, they are delivered to the cell surface, where they are available for identification by αβ receptors on CD8⁺ or CD4⁺ T lymphocytes. In addition, recognition of cell surface peptide/MHC-I complexes by natural killer cell receptors plays a regulatory role in some aspects of the innate immune response. Many of the components of the pathways of antigen processing and presentation and of T cell receptor (TCR)-mediated signaling have been studied extensively by biochemical, genetic, immunological, and structural approaches over the past several decades. Until recently, however, dynamic aspects of the interactions of peptide with MHC, MHC with molecular chaperones, or of pMHC with TCR have been difficult to address experimentally, although computational approaches such as molecular dynamics (MD) simulations have been illuminating. Studies exploiting X-ray crystallography, cryo-electron microscopy, and multidimensional nuclear magnetic resonance (NMR) spectroscopy are beginning to reveal the importance of molecular flexibility as it pertains to peptide loading onto MHC molecules, the interactions between pMHC and TCR, and subsequent TCR-mediated signals. In addition, recent structural and dynamic insights into how molecular chaperones define peptide selection and fine-tune the MHC displayed antigen repertoire are discussed. Here, we offer a review of current knowledge that highlights experimental data obtained by X-ray crystallography and multidimensional NMR methodologies. Collectively, these findings strongly support a multifaceted role for protein plasticity and conformational dynamics throughout the antigen processing and presentation pathway in dictating antigen selection and recognition.

Particle-based membrane model for mesoscopic simulation of cellular dynamics

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

Exploring Substrate Binding in the Extracellular Vestibule of MhsT by Atomistic Simulations and Markov Models

Neurotransmitter:sodium symporters (NSS) terminate neurotransmission through Na⁺-driven reuptake of cognate neurotransmitters. Crystallographically, whereas both substrates and inhibitors have been found to bind in the central binding (S1) site of NSS, inhibitors were found to bind to a second binding (S2) site in the extracellular vestibule (EV) of transporters for leucine (LeuT) and serotonin. On the basis of computational and experimental studies, we proposed that substrates bind to the S2 site of LeuT as well and that substrate binding to the S2 site is essential for Na⁺-coupled symport. Recent binding experiments show that substrate (l-Trp) binding in the S2 site of MhsT, another bacterial NSS, is also central to the allosteric transport mechanism. Here, we used extensive molecular dynamics simulations combined with Markov state model analysis to investigate the interaction of l-Trp with the EV of MhsT and identified potential binding poses of l-Trp as well as induced conformational changes in the EV. Our computational findings were validated by experimental mutagenesis studies and shed light on the ligand binding characteristics of the EV of NSS, which may facilitate development of allosteric ligands targeting NSS.

The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation

Cocaine, a widely abused psychostimulant, inhibits the dopamine transporter (DAT) by trapping the protein in an outward-open conformation, whereas atypical DAT inhibitors such as benztropine have low abuse liability and prefer less outward-open conformations. Here, we use a spectrum of computational modeling and simulation approaches to obtain the underlying molecular mechanism in atomistic detail. Interestingly, our quantum mechanical calculations and molecular dynamics (MD) simulations suggest that a benztropine derivative JHW007 prefers a different stereoisomeric conformation of tropane in binding to DAT compared to that of a cocaine derivative, CFT. To further investigate the different inhibition mechanisms of DAT, we carried out MD simulations in combination with Markov state modeling analysis of wild-type and Y156F DAT in the absence of any ligand or the presence of CFT or JHW007. Our results indicate that the Y156F mutation and CFT shift the conformational equilibrium toward an outward-open conformation, whereas JHW007 prefers an inward-occluded conformation. Our findings reveal the mechanistic details of DAT inhibition by JHW007 at the atomistic level, which provide clues for rational design of atypical inhibitors.

Peptide and Peptide-Dependent Motions in MHC Proteins: Immunological Implications and Biophysical Underpinnings

Structural biology of peptides presented by class I and class II MHC proteins has transformed immunology, impacting our understanding of fundamental immune mechanisms and allowing researchers to rationalize immunogenicity and design novel vaccines. However, proteins are not static structures as often inferred from crystallographic structures. Their components move and breathe individually and collectively over a range of timescales. Peptides bound within MHC peptide-binding grooves are no exception and their motions have been shown to impact recognition by T cell and other receptors in ways that influence function. Furthermore, peptides tune the motions of MHC proteins themselves, which impacts recognition of peptide/MHC complexes by other proteins. Here, we review the motional properties of peptides in MHC binding grooves and discuss how peptide properties can influence MHC motions. We briefly review theoretical concepts about protein motion and highlight key data that illustrate immunological consequences. We focus primarily on class I systems due to greater availability of data, but segue into class II systems as the concepts and consequences overlap. We suggest that characterization of the dynamic “energy landscapes” of peptide/MHC complexes and the resulting functional consequences is one of the next frontiers in structural immunology.

Introduction: MHC/KIR and governance of specificity

The MHC controls specificity, to ensure that appropriate immune responses are mounted to invading pathogens whilst maintaining tolerance to the host. It encodes molecules that act as sentinels, providing a snapshot of the health of the interior and exterior of the cell for immune surveillance. To maintain the ability to respond appropriately to any disease requires a delicate balance of expression and function, and many subtleties of the system have been described at the gene, individual and population level. The main players are the highly polymorphic classical MHC class I and class II molecules, as well as some non-classical loci of both types. Transporter associated with antigen processing (TAP) peptide transporters, proteasome components and Tapasin, encoded within the MHC, are also involved in selection of peptide for presentation. The plethora of mechanisms microorganisms use to subvert immune recognition, through blocking these antigen processing and presentation pathways, attests to the importance of HLA in resistance to infection. There is continued interest in MHC genetics in its own right, as well as in relation to KIR, to transplantation, infection, autoimmunity and reproduction. Also of topical interest, cancer immunotherapy through checkpoint inhibition depends on highly specific recognition of cancer peptide antigen and continued expression of HLA molecules. Here, we briefly introduce some background to the MHC/KIR axis in man. This special issue of immunogenetics expands on these topics, in humans and other model species.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell's own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors-tapasin for class I and HLA-DM for class II-contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell’s own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors—tapasin for class I and HLA-DM for class II—contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Recent advances in Major Histocompatibility Complex (MHC) class I antigen presentation: Plastic MHC molecules and TAPBPR-mediated quality control

We have known since the late 1980s that the function of classical major histocompatibility complex (MHC) class I molecules is to bind peptides and display them at the cell surface to cytotoxic T cells. Recognition by these sentinels of the immune system can lead to the destruction of the presenting cell, thus protecting the host from pathogens and cancer. Classical MHC class I molecules (MHC I hereafter) are co-dominantly expressed, polygenic, and exceptionally polymorphic and have significant sequence diversity. Thus, in most species, there are many different MHC I allotypes expressed, each with different peptide-binding specificity, which can have a dramatic effect on disease outcome. Although MHC allotypes vary in their primary sequence, they share common tertiary and quaternary structures. Here, we review the evidence that, despite this commonality, polymorphic amino acid differences between allotypes alter the ability of MHC I molecules to change shape (that is, their conformational plasticity). We discuss how the peptide loading co-factor tapasin might modify this plasticity to augment peptide loading. Lastly, we consider recent findings concerning the functions of the non-classical MHC I molecule HLA-E as well as the tapasin-related protein TAPBPR (transporter associated with antigen presentation binding protein-related), which has been shown to act as a second quality-control stage in MHC I antigen presentation.