Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions.     

What to do with HLA-DO?

Antigenic peptide binding to MHC class II molecules in the endocytic pathway occurs via a multifactorial process that requires the support of a specialized lysosomal chaperone called HLA-DM. DM shows both in primary amino acid sequence and quaternary structure a high homology to both MHC class I and class II molecules. Like the peptide presenting class II molecules, DM is expressed in all professional antigen presenting cells. DM catalyzes the dissociation of peptides that do not bind stably to the class II peptide-binding groove, thereby leading to the preferential presentation of stably binding antigenic peptides. The recently discovered HLA-DO molecule is mainly expressed in B cells and associates with DM, thereby markedly affecting DM function. Like DM, the genes encoding the HLA-DO heterodimer lie within the MHC class II region and exhibit strong homology to classical class II molecules. This review evaluates the unique effects of DO on DM-mediated antigen presentation by MHC class II molecules and discusses the possible physiological relevance for the B cell-specific expression of DO and its function.     

Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms

Background  

Peptides binding to Major Histocompatibility Complex (MHC) class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides.     

Iterative stepwise discriminant analysis: a meta-algorithm for detecting quantitative sequence motifs.

An algorithm is presented for detecting a quantitative pattern in peptide fragments that bind class II major histocompatibility complex (MHC) molecules. It is referred to as a meta-algorithm because it requires successive applications of Stepwise Discriminate Analysis (SDA). On every iteration the best subsequence candidates are selected from sequences known to bind class II MHC molecules. When SDA compares probable binding subsequences with subsequences known not to bind class II MHC molecules, a quantitative model emerges that is capable of classifying subsequences as binding or non-binding. In an iterative manner, the resultant model is utilized as a criterion for selecting probable binding subsequence candidates. The procedure is repeated until models converge. In the illustrated examples, the final models correctly classify over 95% of the peptides in a database of peptides whose binding affinity for HLA-DR1 is known. The final model can then be used to predict the binding affinity of peptides that have not yet been laboratory tested.     

Prediction of MHC class II binding peptides based on an iterative learning model

Background

Prediction of the binding ability of antigen peptides to major histocompatibility complex (MHC) class II molecules is important in vaccine development. The variable length of each binding peptide complicates this prediction. Motivated by a text mining model designed for building a classifier from labeled and unlabeled examples, we have developed an iterative supervised learning model for the prediction of MHC class II binding peptides.

Results

A linear programming (LP) model was employed for the learning task at each iteration, since it is fast and can re-optimize the previous classifier when the training sets are altered. The performance of the new model has been evaluated with benchmark datasets. The outcome demonstrates that the model achieves an accuracy of prediction that is competitive compared to the advanced predictors (the Gibbs sampler and TEPITOPE). The average areas under the ROC curve obtained from one variant of our model are 0.753 and 0.715 for the original and homology reduced benchmark sets, respectively. The corresponding values are respectively 0.744 and 0.673 for the Gibbs sampler and 0.702 and 0.667 for TEPITOPE.

Conclusion

The iterative learning procedure appears to be effective in prediction of MHC class II binders. It offers an alternative approach to this important predictionproblem.     

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.

This study shows that chicken MHC class II molecules present peptides from only a handful of the more than 100 genes of the oncogenic herpesvirus Marek’s disease virus, explaining the strong genetic association of chicken MHC with resistance and susceptibility to this and other economically-important pathogens.     

Prediction of MHC class II binding affinity using SMM-align,a novel stabilization matrix alignment method

Background  

Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.     

A peptide filtering relation quantifies MHC class I peptide optimization

Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human Immunodeficiency Virus Gag-Pol polyprotein.     

Inhibition of experimental autoimmune encephalomyelitis by a nonimmunogenic non-self peptide that binds to I-Au.

Experimental autoimmune encephalomyelitis (EAE) is an inflammatory neurologic disease initiated by myelin basic protein-reactive CD4+ T cells, which are restricted by a particular MHC class II molecule. Recent studies have utilized inhibitor peptides that bind to restricting MHC class II molecules in order to inhibit EAE, presumably by means of competing with encephalitogenic epitopes. However, these studies leave open the possibility of alternative explanations, such as Ag-specific nonresponsiveness and immunodominance. In order to demonstrate that competition for MHC binding alone can inhibit EAE, the inhibitor peptide should ideally be structurally unrelated and nonimmunogenic yet physically associate with the MHC class II molecule. In this study, we show that the OVA-323-339 peptide, which is unrelated to the disease-inducing peptide, binds to A alpha uA beta u. However, although OVA-323-339 is extremely immunogenic in A alpha dA beta d-expressing BALB/c mice, it is nonimmunogenic in (PL/J x SJL)F1 and PL/J mice expressing A alpha uA beta u. When administered as a coimmunogen with Ac1-11, OVA-323-339 inhibited induction of EAE in (PL/J x SJL)F1 mice. Myelin basic protein-89-101, which does not bind A alpha uA beta u, had no effect on the disease process. This study provides evidence that MHC class II binding alone can modulate the induction of EAE. The use of a nonimmunogenic non-self peptide to modulate an autoimmune disease minimizes the potential complications of immunodominance or alternative regulatory mechanisms associated with immunogenic peptide therapies and further confirms the MHC-blocking model of immunosuppression.     

Kinetics of peptide binding to the class II MHC protein I-Ek

Class II MHC glycoproteins bind short (7-25 amino acid) peptides in an extended type II polyproline-like conformation and present them for immune recognition. Because empty MHC is unstable, measurement of the rate of the second-order reaction between peptide and MHC is challenging. In this report, we use dissociation of a pre-bound peptide to generate the active, peptide-receptive form of the empty class II MHC molecule I-Ek. This allows us to measure directly the rate of reaction between active, empty I-Ek and a set of peptides that vary in structure. We find that all peptides studied, despite having highly variable dissociation rates, bind with similar association rate constants. Thus, the rate-limiting step in peptide binding is minimally sensitive to peptide side-chain structure. An interesting complication to this simple model is that a single peptide can sometimes bind to I-Ek in two kinetically distinguishable conformations, with the stable peptide-MHC complex isomer forming much more slowly than the less-stable one. This demonstrates that an additional free-energy barrier limits the formation of certain specific MHC-peptide complex conformations.     

Peptide length significantly influences in vitro affinity for MHC class II molecules

Background

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Results

By analysing 1279 peptide elongation events covering 19 distinct HLA alleles it was observed that, in general, peptide elongation resulted in increased MHC class II molecule affinity. It was also possible to determine an optimal peptide length for MHC class II affinity of approximately 18–20 amino acids; elongation of peptides beyond this length resulted in a null or negative effect on affinity.

Conclusion

The observed relationship between peptide length and MHC class II affinity has significant implications for the design of vaccines and the study of the epitopic basis of immunological disease.     

MHC Class I/peptide interactions: Binding specificity and kinetics

Recent developments in the preparation of soluble analogues of the major histocompatibility complex (MHC) class l molecules as well as in the applications of real time biosensor technology have permitted the direct analysis of the binding of MHC class l molecules to antigenic peptides. Using synthetic peptide analogues with cysteine substitutions at appropriate positions, peptides can be immobilized on a dextran-modified gold biosensor surface with a specific spatial orientation. A full set of such substituted peptides (known as ‘pepsicles’, as they are peptides on a stick) representing antigenic or self peptides can be used in the functional mapping of the MHC class l peptide binding site. Scans of sets of peptide analogues reveal that some amino acid side chains of the peptide are critical to stable binding to the MHC molecule, while others are not. This is consistent with functional experiments using substituted peptides and three-dimensional molecular models of MHC/peptide complexes. Details analysis of the kinetic dissociation rates (k_d) of the MHC molecules from the specifically coupled solid phase peptides revels that the stability of the complex is a function of the particular peptide, its coupling position, and the MHC molecule. Measured k_d values for antigenic peptide/class I interactions at 25°C are in the range of ca 10^?4–10^?6/s. Biosensor methodology for the analysis of the binding of MHC class I molecules to solid-phase peptides using real time surface plasmon resonance offers a rational approach to the general analysis of protein/peptide interactions.     

NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

Background  

The major histocompatibility complex (MHC) molecule plays a central role in controlling the adaptive immune response to infections. MHC class I molecules present peptides derived from intracellular proteins to cytotoxic T cells, whereas MHC class II molecules stimulate cellular and humoral immunity through presentation of extracellularly derived peptides to helper T cells. Identification of which peptides will bind a given MHC molecule is thus of great importance for the understanding of host-pathogen interactions, and large efforts have been placed in developing algorithms capable of predicting this binding event.     

Structure-based identification of MHC binding peptides: Benchmarking of prediction accuracy

Identification of MHC binding peptides is essential for understanding the molecular mechanism of immune response. However, most of the prediction methods use motifs/profiles derived from experimental peptide binding data for specific MHC alleles, thus limiting their applicability only to those alleles for which such data is available. In this work we have developed a structure-based method which does not require experimental peptide binding data for training. Our method models MHC-peptide complexes using crystal structures of 170 MHC-peptide complexes and evaluates the binding energies using two well known residue based statistical pair potentials, namely Betancourt-Thirumalai (BT) and Miyazawa-Jernigan (MJ) matrices. Extensive benchmarking of prediction accuracy on a data set of 1654 epitopes from class I and class II alleles available in the SYFPEITHI database indicate that BT pair-potential can predict more than 60% of the known binders in case of 14 MHC alleles with AUC values for ROC curves ranging from 0.6 to 0.9. Similar benchmarking on 29,522 class I and class II MHC binding peptides with known IC(50) values in the IEDB database showed AUC values higher than 0.6 for 10 class I alleles and 9 class II alleles in predictions involving classification of a peptide to be binder or non-binder. Comparison with recently available benchmarking studies indicated that, the prediction accuracy of our method for many of the class I and class II MHC alleles was comparable to the sequence based methods, even if it does not use any experimental data for training. It is also encouraging to note that the ranks of true binding peptides could further be improved, when high scoring peptides obtained from pair potential were re-ranked using all atom forcefield and MM/PBSA method.     

Stable peptide binding to MHC class II molecule is rapid and is determined by a receptive conformation shaped by prior association with low affinity peptides

Formation of stable class II MHC/peptide complex involves conformational changes and proceeds via an intermediate. Although this intermediate complex forms and dissociates in minutes, its conversion to a stable complex is a very slow process, taking up to a few days to reach completion. Here, we investigate the different steps of this binding and demonstrate that the conformational changes necessary to generate a receptive molecule is the rate-determining slow step in the process, while formation of the stable MHC/peptide complex is very rapid. With HLA-DR1 as our model class II molecule, we first used low affinity variants of hemagglutinin peptide (HA306-318), which lack the principal anchor, to shape the conformation of the MHC and then studied the kinetics of stable binding of HA306-318 to such an induced conformation. We found that the apparent association rate of HA306-318 is equivalent to the dissociation rate of the low affinity peptide. A 4- to 18-fold enhancement in the binding rates of HA306-318 was observed depending on the dissociation rates of the low affinity peptides. These results establish that 1) formation of stable MHC/peptide complexes is very rapid and 2) prior binding of low affinity peptide induces a receptive conformation in MHC for efficient stable peptide binding. Furthermore, in the absence of any free peptide, this receptive molecule rapidly reverts to slow binding behavior toward the subsequently offered peptide. These results have important implications for the roles of low affinity MHC/peptide complexes in Ag presentation.     

pH dependence and exchange of high and low responder peptides binding to a class II MHC molecule.

We have compared the binding kinetics of two antigenic peptides to a soluble class II MHC molecule. One of the peptides provokes a strong T cell response and the other a much weaker one. Both show greatly increased (approximately 40-fold) association rates at pH 5 in comparison to neutral pH, consistent with the low pH environment of late endosomes being most conducive to class II MHC--peptide binding. Interestingly, the weak peptide has a much faster off-rate that is significantly increased at pH 5 and it can be entirely replaced in an exchange reaction by the stronger one. This suggests that one characteristic of immunodominant peptides is that of nearly irreversible binding, such that they will be strongly selected for in the course of class II MHC transit and recycling through endosomal compartments. Modelling the parameters of this peptide exchange also suggests that a large fraction of the GPI-chimeric MHC molecules used in this study are 'empty' with respect to endogenous peptides, or else occupied with extremely weak ones, consistent with their inability to load processed peptides intracellularly.     

C-terminal anchoring of a peptide to class II MHC via the P10 residue is compatible with a peptide bulge.

The binding of antigenic peptide to class II MHC is mediated by hydrogen bonds between the MHC and the peptide, by salt bridges, and by hydrophobic interactions. The latter are confined to a number of deeper pockets within the peptide binding groove, and peptide side chains that interact with these pockets are referred to as anchor residues. T cell recognition involves solvent-accessible peptide residues along with minor changes in MHC helical pitch induced by the anchor residues. In class I MHC there is an added level of epitope complexity that results from binding of longer peptides that bulge out into the solvent-accessible, T cell contact area. Unlike class I MHC, class II MHC does not bind peptides of discrete length, and the possibility of peptide bulging has not been clearly addressed. A peptide derived from position 24-37 of integrin beta(3) can either bind or not bind to the class II MHC molecule HLA DRB3*0101 based on a polymorphism at the P9 anchor. We show that the loss of binding can be compensated by changes at the P10 position. We propose that this could be an example of a class II peptide bulge. Although not as efficient as P9 anchoring, the use of P10 as an anchor adds another possible mechanism by which T cell epitopes can be generated in the class II presentation system.     

Crystal structure of MHC class II I-Ab in complex with a human CLIP peptide: prediction of an I-Ab peptide-binding motif

Association between the class II major histocompatibility complex (MHC) and the class II invariant chain-associated peptide (CLIP) occurs naturally as an intermediate step in the MHC class II processing pathway. Here, we report the crystal structure of the murine class II MHC molecule I-A(b) in complex with human CLIP at 2.15A resolution. The structure of I-A(b) accounts, via the peptide-binding groove's unique physicochemistry, for the distinct peptide repertoire bound by this allele. CLIP adopts a similar conformation to peptides bound by other I-A alleles, reinforcing the notion that CLIP is presented as a conventional peptide antigen. When compared to the related HLA-DR3/CLIP complex structure, the CLIP peptide displays a slightly different conformation and distinct interaction pattern with residues in I-A(b). In addition, after examining the published sequences of peptides presented by I-A(b), we discuss the possibility of predicting peptide alignment in the I-A(b) binding groove using a simple scoring matrix.     

Ligand exchange of major histocompatibility complex class II proteins is triggered by H-bond donor groups of small molecules

Hydrogen bonds (H-bonds) are crucial for the stability of the peptide-major histocompatibility complex (MHC) complex. In particular, the H-bonds formed between the peptide ligand and the MHC class II binding site appear to have a great influence on the half-life of the complex. Here we show that functional groups with the capacity to disrupt hydrogen bonds (e.g. -OH) can efficiently catalyze ligand exchange reactions on HLA-DR molecules. In conjunction with simple carrier molecules (such as propyl or benzyl residues), they trigger the release of low affinity ligands, which permits the rapid binding of peptides with higher affinity. Similar to HLA-DM, these compounds are able to influence the MHC class II ligand repertoire. In contrast to HLA-DM, however, these simple small molecules are still active at neutral pH. Under physiological conditions, they increase the number of "peptide-receptive" MHC class II molecules and facilitate exogenous peptide loading of dendritic cells. The drastic acceleration of the ligand exchange on these antigen presenting cells suggests that, in general, availability of H-bond donors in the extracellular milieu controls the rate of MHC class II ligand exchange reactions on the cell surface. These molecules may therefore be extremely useful for the loading of antigens onto dendritic cells for therapeutic purposes.