Sequence-structure-function relationships in class I MHC: A local frustration perspective

Differences in F pocket impact on HLA I genetic associations with autoimmune diabetes

Introduction

Human leukocyte antigen (HLA) I molecules present antigenic peptides to activate CD8+ T cells. Type 1 Diabetes (T1D) is an auto-immune disease caused by aberrant activation of the CD8+ T cells that destroy insulin-producing pancreatic β cells. Some HLA I alleles were shown to increase the risk of T1D (T1D-predisposing alleles), while some reduce this risk (T1D-protective alleles).

Methods

Here, we compared the T1D-predisposing and T1D-protective allotypes concerning peptide binding, maturation, localization and surface expression and correlated it with their sequences and energetic profiles using experimental and computational methods.

Results

T1D-predisposing allotypes had more peptide-bound forms and higher plasma membrane levels than T1D-protective allotypes. This was related to the fact that position 116 within the F pocket was more conserved and made more optimal contacts with the neighboring residues in T1D-predisposing allotypes than in protective allotypes.

Conclusion

Our work uncovers that specific polymorphisms in HLA I molecules potentially influence their susceptibility to T1D.

Molecular Characteristics, Functional Definitions, and Regulatory Mechanisms for Cross-Presentation Mediated by the Major Histocompatibility Complex: A Comprehensive Review

The major histocompatibility complexes of vertebrates play a key role in the immune response. Antigen-presenting cells are loaded on MHC I molecules, which mainly present endogenous antigens; when MHC I presents exogenous antigens, this is called cross-presentation. The discovery of cross-presentation provides an important theoretical basis for the study of exogenous antigens. Cross-presentation is a complex process in which MHC I molecules present antigens to the cell surface to activate CD8+ T lymphocytes. The process of cross-representation includes many components, and this article briefly outlines the origins and development of MHC molecules, gene structures, functions, and their classical presentation pathways. The cross-presentation pathways of MHC I molecules, the cell lines that support cross-presentation, and the mechanisms of MHC I molecular transporting are all reviewed. After more than 40 years of research, the specific mechanism of cross-presentation is still unclear. In this paper, we summarize cross-presentation and anticipate the research and development prospects for cross-presentation.

Conformational plasticity of RAS Q61 family of neoepitopes results in distinct features for targeted recognition

The conformational landscapes of peptide/human leucocyte antigen (pHLA) protein complexes encompassing tumor neoantigens provide a rationale for target selection towards autologous T cell, vaccine, and antibody-based therapeutic modalities. Here, using complementary biophysical and computational methods, we characterize recurrent RAS55-64 Q61 neoepitopes presented by the common HLA-A*01:01 allotype. We integrate sparse NMR restraints with Rosetta docking to determine the solution structure of NRASQ61K/HLA-A*01:01, which enables modeling of other common RAS55-64 neoepitopes. Hydrogen/deuterium exchange mass spectrometry experiments alongside molecular dynamics simulations reveal differences in solvent accessibility and conformational plasticity across a panel of common Q61 neoepitopes that are relevant for recognition by immunoreceptors. Finally, we predict binding and provide structural models of NRASQ61K antigens spanning the entire HLA allelic landscape, together with in vitro validation for HLA-A*01:191, HLA-B*15:01, and HLA-C*08:02. Our work provides a basis to delineate the solution surface features and immunogenicity of clinically relevant neoepitope/HLA targets for cancer therapy.

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

The Prognostic Significance of Selected HLA Alleles on Prostate Cancer Outcome

Recently, we have shown that HLA-A*02:01 and HLA-A*24:02 in de novo metastatic prostate cancer (MPCa) have an important role in disease progression. Since de novo MPCa represents a small group among patients diagnosed with prostate cancer (PCa), it was obvious to try to extend the validity of our results to larger cohorts of PCa patients. Herein, we analyzed patients irrespective of their disease status at diagnosis to include, besides patients with MPCa, those with localized PCa (LPCa). Our goal was to specify the prognostic value of HLA-A*02:01 and HLA-A*24:02 for overall survival (OS) prospectively and for early biochemical recurrence (BCR) and castrate resistance (CR) as additional clinical endpoints in a prospective/retrospective manner, to improve clinical decisions for patients covering all stages of PCa. On univariate analysis, HLA-A alleles were significantly associated as prognostic biomarkers with early BCR (p = 0.028; HR = 1.822), OS (p = 0.013; HR = 1.547) and showed a trend for CR (p = 0.150; HR = 1.239). On multivariate analysis, HLA-A alleles proved to be independent prognosticators for early BCR (p = 0.017; HR = 2.008), CR (p = 0.005; HR = 1.615), and OS (p = 0.002; HR = 2.063). Kaplan-Meier analyses revealed that patients belonging to the HLA-A*02:01+HLA-A*24:02- group progressed much faster to BCR and CR and had also shorter OS compared to HLA-A*24:02+ patients. Patients being HLA-A*02:01-HLA-A*24:02- exhibited varying clinical outcomes, pointing to the presence of additional HLA-A alleles with potential prognostic value. Our data underline the HLA-A alleles as valuable prognostic biomarkers for PCa that may assist with the appropriate treatment and follow-up schedule based on the risk for disease progression to avoid over-diagnosis and over-treatment.

The 1926 novel, "One, no one, one hundred thousand", metaphorizes the potential danger when the immune system is exposed to a repetitive antigen stimulation

In the worldwide scenario of infection prevention and control, the vaccine strategies are destined to increase rapidly. The availability of numerous vaccination options allows you to plan individually on how to boost your immune system. The immune system is a highly plastic cognitive dynamic network and performs its function by recognition of the uniqueness of the organism defined as self. The identification and attack of non-self antigens contribute to improving the strategies of self/non-self discrimination. However, repetitive antigen stimulation of the immune system may lead to several outcomes reassumed in three principal risks: (i) loss of the unique self codification (one), (ii) loss of own identifying (no one), and (iii) the increase of idiotype/anti-idiotype entities (one hundred thousand). Controlled production of idiotype/anti-idiotype antibodies protects against autoimmune diseases and immunodeficiency. The title of the famous novel by Nobel Prize for Literature winner Luigi Pirandello, "One, no one, one hundred thousand", recaps the three risks and the protagonist's journey exploring the complexities of personal identity, and warns to preserve the uniqueness of the organism. Taking inspiration from this metaphor, the authors propose to monitor antibody idiotype response for personalizing vaccine plans with the aim of preserving the uniqueness of the immune system and assuring safe protection.

Brain Hydrophobic Peptides Antagonists of Neurotoxic Amyloid β Peptide Monomers/Oligomers-Protein Interactions

Amyloid β (Aβ) oligomers have been linked to Alzheimer's disease (AD) pathogenesis and are the main neurotoxic forms of Aβ. This review focuses on the following: (i) the Aβ(1-42):calmodulin interface as a model for the design of antagonist Aβ peptides and its limitations; (ii) proteolytic degradation as the major source of highly hydrophobic peptides in brain cells; and (iii) brain peptides that have been experimentally demonstrated to bind to Aβ monomers or oligomers, Aβ fibrils, or Aβ plaques. It is highlighted that the hydrophobic amino acid residues of the COOH-terminal segment of Aβ(1-42) play a key role in its interaction with intracellular protein partners linked to its neurotoxicity. The major source of highly hydrophobic endogenous peptides of 8-10 amino acids in neurons is the proteasome activity. Many canonical antigen peptides bound to the major histocompatibility complex class 1 are of this type. These highly hydrophobic peptides bind to Aβ and are likely to be efficient antagonists of the binding of Aβ monomers/oligomers concentrations in the nanomolar range with intracellular proteins. Also, their complexation with Aβ will protect them against endopeptidases, suggesting a putative chaperon-like physiological function for Aβ that has been overlooked until now. Remarkably, the hydrophobic amino acid residues of Aβ responsible for the binding of several neuropeptides partially overlap with those playing a key role in its interaction with intracellular protein partners that mediates its neurotoxicity. Therefore, these latter neuropeptides are also potential candidates to antagonize Aβ peptides binding to target proteins. In conclusion, the analysis performed in this review points out that hydrophobic endogenous brain neuropeptides could be valuable biomarkers to evaluate the risk of the onset of sporadic AD, as well as for the prognosis of AD.

Decoupling peptide binding from T cell receptor recognition with engineered chimeric MHC-I molecules

Major Histocompatibility Complex class I (MHC-I) molecules display self, viral or aberrant epitopic peptides to T cell receptors (TCRs), which employ interactions between complementarity-determining regions with both peptide and MHC-I heavy chain 'framework' residues to recognize specific Human Leucocyte Antigens (HLAs). The highly polymorphic nature of the HLA peptide-binding groove suggests a malleability of interactions within a common structural scaffold. Here, using structural data from peptide:MHC-I and pMHC:TCR structures, we first identify residues important for peptide and/or TCR binding. We then outline a fixed-backbone computational design approach for engineering synthetic molecules that combine peptide binding and TCR recognition surfaces from existing HLA allotypes. X-ray crystallography demonstrates that chimeric molecules bridging divergent HLA alleles can bind selected peptide antigens in a specified backbone conformation. Finally, in vitro tetramer staining and biophysical binding experiments using chimeric pMHC-I molecules presenting established antigens further demonstrate the requirement of TCR recognition on interactions with HLA framework residues, as opposed to interactions with peptide-centric Chimeric Antigen Receptors (CARs). Our results underscore a novel, structure-guided platform for developing synthetic HLA molecules with desired properties as screening probes for peptide-centric interactions with TCRs and other therapeutic modalities.

Identification of novel interferon responsive protein partners of human leukocyte antigen A (HLA-A) using cross-linking mass spectrometry (CLMS) approach

The interferon signalling system elicits a robust cytokine response against a wide range of environmental pathogenic and internal pathological signals, leading to induction of a subset of interferon-induced proteins. We applied DSS (disuccinimidyl suberate) mediated cross-linking mass spectrometry (CLMS) to capture novel protein-protein interactions within the realm of interferon induced proteins. In addition to the expected interferon-induced proteins, we identified novel inter- and intra-molecular cross-linked adducts for the canonical interferon induced proteins, such as MX1, USP18, OAS3, and STAT1. We focused on orthogonal validation of a cohort of novel interferon-induced protein networks formed by the HLA-A protein (H2BFS-HLA-A-HMGA1) using co-immunoprecipitation assay, and further investigated them by molecular dynamics simulation. Conformational dynamics of the simulated protein complexes revealed several interaction sites that mirrored the interactions identified in the CLMS findings. Together, we showcase a proof-of-principle CLMS study to identify novel interferon-induced signaling complexes and anticipate broader use of CLMS to identify novel protein interaction dynamics within the tumour microenvironment.

Structure-based rational design of hydroxysteroid dehydrogenases for improving and diversifying steroid synthesis

A group of steroidogenic enzymes, hydroxysteroid dehydrogenases are involved in steroid metabolism which is very important in the cell: signaling, growth, reproduction, and energy homeostasis. The enzymes show an inherent function in the interconversion of ketosteroids and hydroxysteroids in a position- and stereospecific manner on the steroid nucleus and side-chains. However, the biocatalysis of steroids reaction is a vital and demanding, yet challenging, task to produce the desired enantiopure products with non-natural substrates or non-natural cofactors, and/or in non-physiological conditions. This has driven the use of protein design strategies to improve their inherent biosynthetic efficiency or activate their silent catalytic ability. In this review, the innate features and catalytic characteristics of enzymes based on sequence-structure-function relationships of steroidogenic enzymes are reviewed. Combining structure information and catalytic mechanisms, progress in protein redesign to stimulate potential function, for example, substrate specificity, cofactor dependence, and catalytic stability are discussed.

Crystal structures of N-myristoylated lipopeptide-bound HLA class I complexes indicate reorganization of B-pocket architecture upon ligand binding

Rhesus monkeys have evolved major histocompatibility complex (MHC)-encoded class I allomorphs such as Mamu-B*098 that are capable of binding N-myristoylated short lipopeptides rather than conventional long peptides; however, it remains unknown whether such antigen-binding molecules exist in other species, including humans. We herein demonstrate that human leukocyte antigen (HLA)-A*24:02 and HLA-C*14:02 proteins, which are known to bind conventional long peptides, also have the potential to bind N-myristoylated short lipopeptides. These HLA class I molecules shared a serine at position 9 (Ser9) with Mamu-B*098, in contrast to most MHC class I molecules that harbor a larger amino acid residue, such as tyrosine, at this position. High resolution X-ray crystallographic analyses of lipopeptide-bound HLA-A*24:02 and HLA-C*14:02 complexes indicated that Ser9 was at the bottom of the B pocket with its small hydroxymethyl side chain directed away from the B-pocket cavity, thereby contributing to the formation of a deep hydrophobic cavity suitable for accommodating the long-chain fatty acid moiety of lipopeptide ligands. Upon peptide binding, however, we found the hydrogen-bond network involving Ser9 was reorganized, and the remodeled B pocket was able to capture the second amino acid residue (P2) of peptide ligands. Apart from the B pocket, virtually no marked alterations were observed for the A and F pockets upon peptide and lipopeptide binding. Thus, we concluded that the structural flexibility of the large B pocket of HLA-A*2402 and HLA-C*1402 primarily accounted for their previously unrecognized capacity to bind such chemically distinct ligands as conventional peptides and N-myristoylated lipopeptides.

PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes

Deeper understanding of T-cell-mediated adaptive immune responses is important for the design of cancer immunotherapies and antiviral vaccines against pandemic outbreaks. T-cells are activated when they recognize foreign peptides that are presented on the cell surface by Major Histocompatibility Complexes (MHC), forming peptide:MHC (pMHC) complexes. 3D structures of pMHC complexes provide fundamental insight into T-cell recognition mechanism and aids immunotherapy design. High MHC and peptide diversities necessitate efficient computational modelling to enable whole proteome structural analysis. We developed PANDORA, a generic modelling pipeline for pMHC class I and II (pMHC-I and pMHC-II), and present its performance on pMHC-I here. Given a query, PANDORA searches for structural templates in its extensive database and then applies anchor restraints to the modelling process. This restrained energy minimization ensures one of the fastest pMHC modelling pipelines so far. On a set of 835 pMHC-I complexes over 78 MHC types, PANDORA generated models with a median RMSD of 0.70 Å and achieved a 93% success rate in top 10 models. PANDORA performs competitively with three pMHC-I modelling state-of-the-art approaches and outperforms AlphaFold2 in terms of accuracy while being superior to it in speed. PANDORA is a modularized and user-configurable python package with easy installation. We envision PANDORA to fuel deep learning algorithms with large-scale high-quality 3D models to tackle long-standing immunology challenges.

The pockets guide to HLA class I molecules

Human leukocyte antigens (HLA) are cell-surface proteins that present peptides to T cells. These peptides are bound within the peptide binding cleft of HLA, and together as a complex, are recognised by T cells using their specialised T cell receptors. Within the cleft, the peptide residue side chains bind into distinct pockets. These pockets ultimately determine the specificity of peptide binding. As HLAs are the most polymorphic molecules in humans, amino acid variants in each binding pocket influences the peptide repertoire that can be presented on the cell surface. Here, we review each of the 6 HLA binding pockets of HLA class I (HLA-I) molecules. The binding specificity of pockets B and F are strong determinants of peptide binding and have been used to classify HLA into supertypes, a useful tool to predict peptide binding to a given HLA. Over the years, peptide binding prediction has also become more reliable by using binding affinity and mass spectrometry data. Crystal structures of peptide-bound HLA molecules provide a means to interrogate the interactions between binding pockets and peptide residue side chains. We find that most of the bound peptides from these structures conform to binding motifs determined from prediction software and examine outliers to learn how these HLAs are stabilised from a structural perspective.

FrustratometeR: an R-package to compute local frustration in protein structures, point mutants and MD simulations

SUMMARY

Once folded, natural protein molecules have few energetic conflicts within their polypeptide chains. Many protein structures do however contain regions where energetic conflicts remain after folding, i.e. they are highly frustrated. These regions, kept in place over evolutionary and physiological timescales, are related to several functional aspects of natural proteins such as protein-protein interactions, small ligand recognition, catalytic sites and allostery. Here, we present FrustratometeR, an R package that easily computes local energetic frustration on a personal computer or a cluster. This package facilitates large scale analysis of local frustration, point mutants and molecular dynamics (MD) trajectories, allowing straightforward integration of local frustration analysis into pipelines for protein structural analysis.

AVAILABILITY AND IMPLEMENTATION

https://github.com/proteinphysiologylab/frustratometeR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Dynamics of MHC-I molecules in the antigen processing and presentation pathway

The endogenous antigen processing and presentation (APP) is a fundamental pathway found in jawed vertebrates, which allows for a set of epitope peptides sampled from the intracellular proteome to be assembled and displayed on class I proteins of the major histocompatibility complex (MHC-I). Peptide/MHC-I antigens enable different aspects of adaptive immunity to emerge, by providing a basis for recognition of self vs. non-self by T cells and Natural Killer (NK) cells. Pioneering studies of pMHC-I molecules and their higher-order protein complexes with molecular chaperones and membrane receptors have gleaned important insights into the peptide loading and antigen recognition mechanisms. While X-ray and cryoEM structures have provided us with static snapshots of different MHC-I assembly stages, complementary biophysical techniques have revealed that MHC-I molecules are highly mobile on a range of biologically relevant timescales, which bears importance for their assembly, peptide repertoire selection, membrane display and turnover. This review summarizes insights gained from experimental and simulation studies aimed at investigating MHC-I dynamics, and their functional implications.

Venus flytrap or pas de trois? The dynamics of MHC class I molecules

The peptide binding site of major histocompatibility complex (MHC) class I molecules is natively unfolded when devoid of peptides. Peptide binding stabilizes the structure and slows the dynamics, but peptide-specific and subtype-specific motions influence, and are influenced by, interaction with assembly chaperones, the T cell receptor, and other class I-binding proteins. The molecular mechanisms of cooperation between peptide, class I heavy chain, and beta-2 microglobulin are insufficiently known but are being elucidated by nuclear magnetic resonance and other modern methods. It appears that micropolymorphic clusters of charged amino acids, often hidden in the molecule interior, determine the dynamics and thus chaperone dependence, cellular fate, and disease association of class I.

Unraveling the Allosteric Communication Mechanisms in T-Cell Receptor-Peptide-Loaded Major Histocompatibility Complex Dynamics Using Molecular Dynamics Simulations: An Approach Based on Dynamic Cross Correlation Maps and Residue Interaction Energy Calculations

Antigen presentation by major histocompatibility complex (MHC) proteins to T-cell receptors (TCRs) plays a crucial role in triggering the adaptive immune response. Most of our knowledge on TCR-peptide-loaded major histocompatibility complex (pMHC) interaction stemmed from experiments yielding static structures, yet the dynamic aspects of this molecular interaction are equally important to understand the underlying molecular mechanisms and to develop treatment strategies against diseases such as cancer and autoimmune diseases. To this end, computational biophysics studies including all-atom molecular dynamics simulations have provided useful insights; however, we still lack a basic understanding of an overall allosteric mechanism that results in conformational changes in the TCR and subsequent T-cell activation. Previous hydrogen-deuterium exchange and nuclear magnetic resonance studies provided clues regarding these molecular mechanisms, including global rigidification and allosteric effects on the constant domain of TCRs away from the pMHC interaction site. Here, we show that molecular dynamics simulations can be used to identify how this overall rigidification may be related to the allosteric communication within TCRs upon pMHC interaction via essential dynamics and nonbonded residue-residue interaction energy analyses. The residues taking part in the rigidification effect are highlighted with an intricate analysis on residue interaction changes, which lead to a detailed outline of the complex formation event. Our results indicate that residues of the Cβ domain of TCRs show significant differences in their nonbonded interactions upon complex formation. Moreover, the dynamic cross correlations between these residues are also increased, in line with their nonbonded interaction energy changes. Altogether, our approach may be valuable for elucidating intramolecular allosteric changes in the TCR structure upon pMHC interaction in molecular dynamics simulations.

HLA-A29 and Birdshot Uveitis: Further Down the Rabbit Hole

HLA class I alleles constitute established risk factors for non-infectious uveitis and preemptive genotyping of HLA class I alleles is standard practice in the diagnostic work-up. The HLA-A29 serotype is indispensable to Birdshot Uveitis (BU) and renders this enigmatic eye condition a unique model to better understand how the antigen processing and presentation machinery contributes to non-infectious uveitis or chronic inflammatory conditions in general. This review will discuss salient points regarding the protein structure of HLA-A29 and how key amino acid positions impact the peptide binding preference and interaction with T cells. We discuss to what extent the risk genes ERAP1 and ERAP2 uniquely affect HLA-A29 and how the discovery of a HLA-A29-specific submotif may impact autoantigen discovery. We further provide a compelling argument to solve the long-standing question why BU only affects HLA-A29-positive individuals from Western-European ancestry by exploiting data from the 1000 Genomes Project. We combine novel insights from structural and immunopeptidomic studies and discuss the functional implications of genetic associations across the HLA class I antigen presentation pathway to refine the etiological basis of Birdshot Uveitis.