An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles

Background

The immune system must detect a wide variety of microbial pathogens, such as viruses, bacteria, fungi and parasitic worms, to protect the host against disease. Antigenic peptides displayed by MHC II (class II Major Histocompatibility Complex) molecules is a pivotal process to activate CD4+ T_H cells (Helper T cells). The activated T_H cells can differentiate into effector cells which assist various cells in activating against pathogen invasion. Each MHC locus encodes a great number of allele variants. Yet this limited number of MHC molecules are required to display enormous number of antigenic peptides. Since the peptide binding measurements of MHC molecules by biochemical experiments are expensive, only a few of the MHC molecules have suffecient measured peptides. To perform accurate binding prediction for those MHC alleles without suffecient measured peptides, a number of computational algorithms were proposed in the last decades.

Results

Here, we propose a new MHC II binding prediction approach, OWA-PSSM, which is a significantly extended version of a well known method called TEPITOPE. The TEPITOPE method is able to perform prediction for only 50 MHC alleles, while OWA-PSSM is able to perform prediction for much more, up to 879 HLA-DR molecules. We evaluate the method on five benchmark datasets. The method is demonstrated to be the best one in identifying binding cores compared with several other popular state-of-the-art approaches. Meanwhile, the method performs comparably to the TEPITOPE and NetMHCIIpan2.0 approaches in identifying HLA-DR epitopes and ligands, and it performs significantly better than TEPITOPEpan in the identification of HLA-DR ligands and MultiRTA in identifying HLA-DR T cell epitopes.

Conclusions

The proposed approach OWA-PSSM is fast and robust in identifying ligands, epitopes and binding cores for up to 879 MHC II molecules.

     

Quantitative structure-activity relationships and the prediction of MHC supermotifs

The underlying assumption in quantitative structure-activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here--the additive method--is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A*0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.     

Study on molecular mechanism and 3D-QSAR of influenza neuraminidase inhibitors

Neuraminidase (NA) is a critical enzyme of the influenza virus and many inhibitors targeting to this enzyme are quite efficient and encouraging as anti-influenza agents. In this paper the binding model of five series of inhibitors to NA was examined using molecular simulation method. The resulted conformation and orientation of the compounds were directly put into CoMSIA study. The most significant amino acid residues at binding sites and the requirement for features of substituents were applied to direct design of new inhibitors. The robust QSAR model and its three-dimensional contour map provided guidelines to building novel compounds with new scaffold and for structural optimization of current molecules.     

A computational pipeline to generate MHC binding motifs

BACKGROUND: Major histocompatibility complex (MHC) class I molecules play key roles in host immunity against pathogens by presenting peptide antigens to CD8+ T-cells. Many variants of MHC molecules exist, and each has a unique preference for certain peptide ligands. Both experimental approaches and computational algorithms have been utilized to analyze these peptide MHC binding characteristics. Traditionally, MHC binding specificities have been described in terms of binding motifs. Such motifs classify certain peptide positions as primary and secondary anchors according to their impact on binding, and they list the preferred and deleterious residues at these positions. This provides a concise and easily communicatable summary of MHC binding specificities. However, so far there has been no algorithm to generate such binding motifs in an automated and uniform fashion. In this paper, we present a computational pipeline that takes peptide MHC binding data as input and produces a concise MHC binding motif. We tested our pipeline on a set of 18 MHC class I molecules and showed that the derived motifs are consistent with historic expert assignments. We have implemented a pipeline that formally codifies rules to generate MHC binding motifs. The pipeline has been incorporated into the immune epitope database and analysis resource (IEDB) and motifs can be visualized while browsing MHC alleles in the IEDB.     

Effect of isotypes and allelic polymorphism on the binding of staphylococcal exotoxins to MHC class II molecules

Interaction of staphylococcal exotoxins (SE) with MHC class II molecules plays a central role in the activation of immune cells by SE. We have recently demonstrated directly that toxic shock syndrome toxin-1 (TSST-1) binds to MHC class II molecules with high affinity, and similar results have been reported for SEA and SEB. The ability of T cells to respond to individual SE is associated with the expression of particular TCR-V beta gene elements. In the present study we have examined the effect of polymorphism on the ability of MHC class II molecules to bind SEB and TSST-1. We have used a panel of L cell transfectants that express different allelic forms of each of the three human class II isotypes. Radioligand binding assays detected binding of SEB and TSST-1 to most, but not all of the MHC class II molecules examined. Toxin-driven MHC class II-dependent T cell proliferation occurred with all transfectants examined even in the absence of detectable toxin binding. These results indicate that SE can bind to human MHC class II molecules of diverse phenotypes.     

Selection of T-cell epitopes from foot-and-mouth disease virus reflects the binding affinity to different cattle MHC class II molecules

The major histocompatibility complex (MHC)-restricted selection of T-cell epitopes of foot-and-mouth disease virus (FMDV) by individual cattle MHC class II DR (BoLA-DR) molecules was studied in a direct MHC-peptide binding assay. By in vitro priming of T lymphocytes derived from animals homozygous for both MHC class I and II, five T-cell epitopes were analyzed in the context of three MHC class II haplotypes. We found that the presentation of these T-cell epitopes was mediated by DR molecules, since blocking this pathway of antigen presentation using monoclonal antibody TH14B completely abolished the proliferative responses against the peptides. To study the DR-restricted presentation of these T-cell epitopes, a direct MHC-peptide binding assay on isolated cattle DR molecules was developed. Purified cattle MHC class II DR molecules of the BoLA-DRB3*0201, BoLA-DRB3*1101, and BoLA-DRB3*1201 alleles were isolated from peripheral blood mononuclear cells. For each allele, one of the identified T-cell epitopes was biotinylated, and used as a marker peptide for the development of a competitive MHC-peptide binding assay. Subsequently, the T-cell epitopes of FMDV with functionally defined MHC class II specificity were analyzed in this binding assay. The affinity of the epitopes to bind to certain DR molecules was significantly correlated to the capacity to induce T-cell proliferation. This demonstrated at the molecular level that the selection of individual T-cell epitopes found at the functional level was indeed the result of MHC restriction.     

NK cell inhibitory receptor Ly-49C residues involved in MHC class I binding.

Mouse NK cells express Ly-49 receptors specific for classical MHC class I molecules. Several of the Ly-49 receptors have been characterized in terms of function and ligand specificity. However, the only Ly-49 receptor-ligand interaction previously described in detail is that between Ly-49A and H-2D(d), as studied by point mutations in the ligand and the crystal structure of the co-complex of these molecules. It is not known whether other Ly-49 receptors bind MHC class I in a similar manner as Ly-49A. Here we have studied the effect of mutations in Ly-49C on binding to the MHC class I molecules H-2K(b), H-2D(b), and H-2D(d). The MHC class I molecules were used as soluble tetramers to stain transiently transfected 293T cells expressing the mutated Ly-49C receptors. Three of nine mutations in Ly-49C led to loss of MHC class I binding. The three Ly-49C mutations that affected MHC binding correspond to Ly-49A residues that are in contact or close to H-2D(d) in the co-crystal, demonstrating that MHC class I binding by Ly-49C is dependent on residues in the same area as that used by Ly-49A for ligand contacts.     

In vitro maximum binding of antigenic peptides to murine MHC class II molecules does not always take place at the acidic pH of the in vivo endosomal compartment.

Presentation of Ag to the T cell requires binding of specific peptide fragments of the Ag to MHC II molecules. The ability of a peptide to bind to MHC class II appears to be pH dependent. Recent reports indicate that the binding of peptide to MHC class II molecules takes place primarily within an endosomal compartment of the cell at around pH 5. In this study, we have explored the in vitro pH dependence of peptide binding to different haplotypes of murine MHC class II molecules. The binding of peptides to MHC II was analyzed and quantitated by silica gel TLC, using radiolabeled peptides. The MBP peptide fragments, MBP(1-14)A4 and MBP(88-101)Y88, bound maximally at pH 8 to IAk and IAs, respectively. The binding of PLP peptide fragment, PLP(138-151)Y138, to IAs was maximal at around neutral pH. The maximum binding of an OVA peptide fragment, OVA(323-340)Y340, to IAd, was found to occur at pH 6. Results presented in this report thus suggest that the in vitro maximum binding of peptide is pH dependent and does not always occur at pH 5. The optimum pH range for maximum binding may depend on the nature and net charge of the peptide and its interaction with MHC class II molecules.     

Constitutive internalization of murine MHC class I molecules

The total number of cell surface glycoprotein molecules at the plasma membrane results from a balance between their constitutive internalization and their egress to the cell surface from intracellular pools and/or biosynthetic pathway. Constitutive internalization is net result of constitutive endocytosis and endocytic recycling. In this study we have compared spontaneous internalization of murine major histocompatibility complex (MHC) class I molecules (K(d), D(d), full L(d), and empty L(d)) after depletion of their egress to the cell surface (Cycloheximide [CHX], brefeldin A [BFA]) and internalization after external binding of monoclonal antibody (mAb). MHC class I alleles differ regarding their cell surface stability, kinetics, and in the way of internalization and degradation. K(d) and D(d) molecules are more stable at the cell surface than L(d) molecules and, thus, constitutively internalized more slowly. Although the binding of mAbs to cell surface MHC class I molecules results in faster internalization than depletion of their egress, it is still slow and, thereby, can serve as a model for tracking of MHC class I endocytosis. Internalization of fully conformed MHC class I molecules (K(d), D(d), and L(d)) was neither inhibited by chlorpromazine (CP) (inhibitor of clathrin endocytosis), nor with filipin (inhibitor of lipid raft dependent endocytosis), indicating that fully conformed MHC class I molecules are internalized via the bulk pathway. In contrast, internalization of empty L(d) molecules was inhibited by filipin, indicating that non-conformed MHC class I molecules require intact cholesterol-rich membrane microdomains for their constitutive internalization. Thus, conformed and non-conformed MHC class I molecules use different endocytic pathways for constitutive internalization.     

Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools

Binding of short antigenic peptides to major histocompatibility complex (MHC) molecules is a core step in adaptive immune response. Precise identification of MHC-restricted peptides is of great significance for understanding the mechanism of immune response and promoting the discovery of immunogenic epitopes. However, due to the extremely high MHC polymorphism and huge cost of biochemical experiments, there is no experimentally measured binding data for most MHC molecules. To address the problem of predicting peptides binding to these MHC molecules, recently computational approaches, called pan-specific methods, have received keen interest. Pan-specific methods make use of experimentally obtained binding data of multiple alleles, by which binding peptides (binders) of not only these alleles but also those alleles with no known binders can be predicted. To investigate the possibility of further improvement in performance and usability of pan-specific methods, this article extensively reviews existing pan-specific methods and their web servers. We first present a general framework of pan-specific methods. Then, the strategies and performance as well as utilities of web servers are compared. Finally, we discuss the future direction to improve pan-specific methods for MHC-peptide binding prediction.     

Diverse repertoire of the MHC class II-peptide complexes is required for presentation of viral superantigens

Among other features, peptides affect MHC class II molecules, causing changes in the binding of bacterial superantigens (b-Sag). Whether peptides can alter binding of viral superantigens (v-Sag) to MHC class II was not known. Here we addressed the question of whether mutations limiting the diversity of peptides bound by the MHC class II molecules influenced the presentation of v-Sag and, subsequently, the life cycle of the mouse mammary tumor virus (MMTV). T cells reactive to v-Sag were found in mice lacking DM molecules as well as in A(b)Ep-transgenic mice in which MHC class II binding grooves were predominantly occupied by an invariant chain fragment or Ealpha(52-68) peptide, respectively. APCs from the mutant mice failed to present v-Sag, as determined by the lack of Sag-specific T cell activation, Sag-induced T cell deletion, and by the aborted MMTV infection. In contrast, mice that express I-A(b) with a variety of bound peptides presented v-Sag and were susceptible to MMTV infection. Comparison of v-Sag and b-Sag presentation by the same mutant cells suggested that presentation of v-Sag had requirements similar to that for presentation of toxic shock syndrome toxin-1. Thus, MHC class II peptide repertoire is critical for recognition of v-Sag by the T cells and affects the outcome of infection with a retrovirus.     

Comparison of structural requirements for interaction of the same peptide with I-Ek and I-Ed molecules in the activation of MHC class II-restricted T cells.

We have analyzed the interaction of the hen egg-white lysozyme (HEL) peptide 107-116 with the MHC class II molecule I-Ek, using truncated and single residue substitution analogues to measure activation of I-Ek-restricted, 107-116-specific T cell hybridomas and competition for Ag presentation by I-Ek molecules. These results have been compared with previous findings on the interaction of the same peptide with the I-Ed molecule. Stimulation of T cell hybridomas by truncated peptides defines the sequence 108-116 as the minimum epitope necessary for activation of both I-Ek- and I-Ed-restricted T cell hybridomas. Substitution analysis pinpoints three residues (V109, A110, and K116) in the sequence 108-116 as being critical for binding to I-Ek molecules and demonstrates the involvement of most other residues in recognition by T cells. Results previously obtained for binding of HEL 107-116 to I-Ed molecules indicated that peptide residues R112, R114, and K116 were critical for interaction with I-Ed. Comparison of these results indicates a difference in the likely MHC contact residues between the HEL sequence 108-116 and I-Ed or I-Ek molecules, suggesting that the same HEL peptide assumes a different conformation in the binding site of these two MHC molecules. This in turn affects residues interacting with the specific T cell receptor. According to the hypothetical tridimensional structure predicted for class II molecules, the difference in MHC contact residues observed within the sequence 108-116 can be related to polymorphic amino acids in the binding site of I-Ek and I-Ed molecules. A search through published binding data for a common pattern in this and other I-Ek-binding peptides has permitted us to derive a possible motif for predicting peptide binding to I-Ek molecules. This putative motif was tested by determining binding to I-Ek of an unbiased panel of about 150 synthetic peptides. Binding data indeed demonstrate the presence of this motif in the majority of good binders to I-Ek molecules.     

MHCcluster, a method for functional clustering of MHC molecules

The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.     

Modeling alternative binding registers of a minimal immunogenic peptide on two class II major histocompatibility complex (MHC II) molecules predicts polarized T-cell receptor (TCR) contact positions.

Several major histocompatibility complex class II (MHC II) complexes with known minimal immunogenic peptides have now been solved by X-ray crystallography. Specificity pockets within the MHC II binding groove provide distinct peptide contacts that influence peptide conformation and define the binding register within different allelic MHC II molecules. Altering peptide ligands with respect to the residues that contact the T-cell receptor (TCR) can drastically change the nature of the ensuing immune response. Here, we provide an example of how MHC II (I-A) molecules may indirectly effect TCR contacts with a peptide and drive functionally distinct immune responses. We modeled the same immunogenic 12-amino acid peptide into the binding grooves of two allelic MHC II molecules linked to distinct cytokine responses against the peptide. Surprisingly, the favored conformation of the peptide in each molecule was distinct with respect to the exposure of the N- or C-terminus of the peptide above the MHC II binding groove. T-cell clones derived from each allelic MHC II genotype were found to be allele-restricted with respect to the recognition of these N- vs. C-terminal residues on the bound peptide. Taken together, these data suggest that MHC II alleles may influence T-cell functions by restricting TCR access to specific residues of the I-A-bound peptide. Thus, these data are of significance to diseases that display genetic linkage to specific MHC II alleles, e.g. type 1 diabetes and rheumatoid arthritis.     

Classical and nonclassical class I major histocompatibility complex molecules exhibit subtle conformational differences that affect binding to CD8alphaalpha

The cell surface molecules CD4 and CD8 greatly enhance the sensitivity of T-cell antigen recognition, acting as "co-receptors" by binding to the same major histocompatibility complex (MHC) molecules as the T-cell receptor (TCR). Here we use surface plasmon resonance to study the binding of CD8alphaalpha to class I MHC molecules. CD8alphaalpha bound the classical MHC molecules HLA-A*0201, -A*1101, -B*3501, and -C*0702 with dissociation constants (K(d)) of 90-220 microm, a range of affinities distinctly lower than that of TCR/peptide-MHC interaction. We suggest such affinities apply to most CD8alphaalpha/classical class I MHC interactions and may be optimal for T-cell recognition. In contrast, CD8alphaalpha bound both HLA-A*6801 and B*4801 with a significantly lower affinity (>/=1 mm), consistent with the finding that interactions with these alleles are unable to mediate cell-cell adhesion. Interestingly, CD8alphaalpha bound normally to the nonclassical MHC molecule HLA-G (K(d) approximately 150 microm), but only weakly to the natural killer cell receptor ligand HLA-E (K(d) >/= 1 mm). Site-directed mutagenesis experiments revealed that variation in CD8alphaalpha binding affinity can be explained by amino acid differences within the alpha3 domain. Taken together with crystallographic studies, these results indicate that subtle conformational changes in the solvent exposed alpha3 domain loop (residues 223-229) can account for the differential ability of both classical and nonclassical class I MHC molecules to bind CD8.     

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.     

MHC motif viewer

In vertebrates, the major histocompatibility complex (MHC) presents peptides to the immune system. In humans, MHCs are called human leukocyte antigens (HLAs), and some of the loci encoding them are the most polymorphic in the human genome. Different MHC molecules present different subsets of peptides, and knowledge of their binding specificities is important for understanding the differences in the immune response between individuals. Knowledge of motifs may be used to identify epitopes, to understand the MHC restriction of epitopes, and to compare the specificities of different MHC molecules. Algorithms that predict which peptides MHC molecules bind have recently been developed and cover many different alleles, but the utility of these algorithms is hampered by the lack of tools for browsing and comparing the specificity of these molecules. We have, therefore, developed a web server, MHC motif viewer, that allows the display of the likely binding motif for all human class I proteins of the loci HLA A, B, C, and E and for MHC class I molecules from chimpanzee (Pan troglodytes), rhesus monkey (Macaca mulatta), and mouse (Mus musculus). Furthermore, it covers all HLA-DR protein sequences. A special viewing feature, MHC fight, allows for display of the specificity of two different MHC molecules side by side. We show how the web server can be used to discover and display surprising similarities as well as differences between MHC molecules within and between different species. The MHC motif viewer is available at .     

Determination of structural principles underlying three different modes of lymphocytic choriomeningitis virus escape from CTL recognition

Lymphocytic choriomeningitis virus infection of H-2(b) mice generates a strong CD8(+) CTL response mainly directed toward three immunodominant epitopes, one of which, gp33, is presented by both H-2D(b) and H-2K(b) MHC class I molecules. This CTL response acts as a selective agent for the emergence of viral escape variants. These variants generate altered peptide ligands (APLs) that, when presented by class I MHC molecules, antagonize CTL recognition and ultimately allow the virus to evade the cellular immune response. The emergence of APLs of the gp33 epitope is particularly advantageous for LCMV, as it allows viral escape in the context of both H-2D(b) and H-2K(b) MHC class I molecules. We have determined crystal structures of three different APLs of gp33 in complex with both H-2D(b) and H-2K(b). Comparison between these APL/MHC structures and those of the index gp33 peptide/MHC reveals the structural basis for three different strategies used by LCMV viral escape mutations: 1) conformational changes in peptide and MHC residues that are potential TCR contacts, 2) impairment of APL binding to the MHC peptide binding cleft, and 3) introduction of subtle changes at the TCR/pMHC interface, such as the removal of a single hydroxyl group.