Prediction of MHC class I binding peptides, using SVMHC

Background  

T-cells are key players in regulating a specific immune response. Activation of cytotoxic T-cells requires recognition of specific peptides bound to Major Histocompatibility Complex (MHC) class I molecules. MHC-peptide complexes are potential tools for diagnosis and treatment of pathogens and cancer, as well as for the development of peptide vaccines. Only one in 100 to 200 potential binders actually binds to a certain MHC molecule, therefore a good prediction method for MHC class I binding peptides can reduce the number of candidate binders that need to be synthesized and tested.     

Prediction of MHC class I binding peptides using probability distribution functions

Binding of peptides to specific Major Histo-compatibility Complex (MHC) molecule is important for understanding immunity and has applications to vaccine discovery and design of immunotherapy. Artificial neural networks (ANN) are widely used by predictions tools to classify the peptides as binders or non­binders (BNB). However, the number of known binders to a specific MHC molecule is limited in many cases, which poses a computational challenge for prediction of BNB and hence, needs improvement in learning of ANN. Here, we describe, the application of probability distribution functions to initialize the weights and biases of the artificial neural network in order to predict HLA­A*0201 binders and non­binders. The 10­fold cross validation has been used to validate the results. It is evident from the results that the A_ROC for 90% of test cases for Weibull, Uniform and Rayleigh distributions is in the range 0.90-1.0. Further, the standard deviation for AROC was minimum for Weibull distribution, and may be used to train the artificial neural network for HLA­A*0201 MHC Class­I binders and non­binders prediction.     

Effect of class I MHC binding peptides on recognition by natural killer cells.

NK cells can recognize and destroy a broad range of cells, including many tumor cells and virally infected cells, yet spare most normal cells. Identification of the target structure recognized by these cells has proved elusive. An attractive hypothesis is that, unlike B cells and T cells that recognize a specific foreign marker, NK cells respond to the absence of a "self" marker. Class I MHC molecules have been implicated as the self markers whose absence can trigger lysis. We show here that normal cells are lysed on incubation with IL-2-activated NK cells if peptides that can bind to the class I MHC molecules of the normal cells are also included in the assay, and speculate that this binding is somehow removing a self marker that normally protects a cell from lysis. NK cells were derived from splenocytes of young (5 to 8 wk old) athymic nude BALB/c (H-2d) or nude C57Bl/6 (H-2b) mice incubated with 1000 U/ml rIL-2, and target cells were derived from splenocytes of normal BALB/c or C57Bl/6 mice incubated with Con A. Peptides were from xenogeneic, viral, self, and mutated self protein sequences and included sequences specific for Kd, Kb, Db, and Ld. All peptides increased lysability of those targets to which they could bind.     

Presentation of antigenic peptides by MHC class I molecules

The basis for the immune response against intracellular pathogens is the recognition by cytotoxic T lymphocytes of antigenic peptides derived from cytosolic proteins, which are presented on the cell surface by major histocompatibility complex (MHC) class I molecules. The understanding of MHC class I-restricted peptide presentation has recently improved dramatically with the elucidation of the structural basis for the specificity of peptide binding to MHC class I molecules and the identification of proteins encoded in the class II region of the MHC that are putatively involved in the production of peptides and their transport into the endoplasmic reticulum, where they assemble with class I molecules.     

Prediction of MHC class I binding peptides with a new feature encoding technique

The recognition of specific peptides, bound to major histocompatibility complex (MHC) class I molecules, is of particular importance to the robust identification of T-cell epitopes and thus the successful design of protein-based vaccines. Here, we present a new feature amino acid encoding technique termed OEDICHO to predict MHC class I/peptide complexes. In the proposed method, we have combined orthonormal encoding (OE) and the binary representation of selected 10 best physicochemical properties of amino acids derived from Amino Acid Index Database (AAindex). We also have compared our method to current feature encoding techniques. The tests have been carried out on comparatively large Human Leukocyte Antigen (HLA)-A and HLA-B allele peptide binding datasets. Empirical results show that our amino acid encoding scheme leads to better classification performance on a standalone classifier.     

Disulfide bond engineering to trap peptides in the MHC class I binding groove

Immunodominant peptides in CD8 T cell responses to pathogens and tumors are not always tight binders to MHC class I molecules. Furthermore, antigenic peptides that bind weakly to the MHC can be problematic when designing vaccines to elicit CD8 T cells in vivo or for the production of MHC multimers for enumerating pathogen-specific T cells in vitro. Thus, to enhance peptide binding to MHC class I, we have engineered a disulfide bond to trap antigenic peptides into the binding groove of murine MHC class I molecules expressed as single-chain trimers or SCTs. These SCTs with disulfide traps, termed dtSCTs, oxidized properly in the endoplasmic reticulum, transited to the cell surface, and were recognized by T cells. Introducing a disulfide trap created remarkably tenacious MHC/peptide complexes because the peptide moiety of the dtSCT was not displaced by high-affinity competitor peptides, even when relatively weak binding peptides were incorporated into the dtSCT. This technology promises to be useful for DNA vaccination to elicit CD8 T cells, in vivo study of CD8 T cell development, and construction of multivalent MHC/peptide reagents for the enumeration and tracking of T cells-particularly when the antigenic peptide has relatively weak affinity for the MHC.     

A probabilistic meta-predictor for the MHC class II binding peptides

Several computational methods for the prediction of major histocompatibility complex (MHC) class II binding peptides embodying different strengths and weaknesses have been developed. To provide reliable prediction, it is important to design a system that enables the integration of outcomes from various predictors. The construction of a meta-predictor of this type based on a probabilistic approach is introduced in this paper. The design permits the easy incorporation of results obtained from any number of individual predictors. It is demonstrated that this integrated method outperforms six state-of-the-art individual predictors based on computational studies using MHC class II peptides from 13 HLA alleles and three mouse MHC alleles obtained from the Immune Epitope Database and Analysis Resource. It is concluded that this integrative approach provides a clearly enhanced reliability of prediction. Moreover, this computational framework can be directly extended to MHC class I binding predictions.     

MHC class II binding of peptides derived from HLA-DR 1.

The aim of these studies was to determine whether auto- and alloreactivity can arise from T cell recognition of MHC-peptides in context of syngeneic MHC. Four synthetic peptides derived from the first domain of the HLA-DR beta 1 * 0101 chain were used in limiting dilution analysis to prime T cells from HLA-DR1- and HLA-DR1+ responders. The frequency of T cells responding to these four peptides was similar in individuals with or without HLA-DR1. In both cases, the peptide corresponding to the nonpolymorphic sequence 43-62, was less immunogenic than peptides corresponding to the three hypervariable regions 1-20, 21-42, and 66-90, eliciting a lower number of reactive T cells. Experiments using a T cell line with specific reactivity to peptide 21-42 showed, however, that this response can be efficiently blocked by adding to the culture a nonpolymorphic sequence peptide. This suggests that alloreactivity can be blocked by use of monomorphic (self) peptides. The binding of both "monomorphic" and "polymorphic" synthetic DR1 peptides to affinity purified HLA-DR 1 and DR 11 molecules was measured using radiolabeled peptides and high performance size exclusion chromatography. The data showed that the polymorphic as well as monomorphic synthetic DR1 peptides bound to both DR1 and DR11 molecules. Competitive inhibition studies indicated that the monomorphic 43-62 peptide can block the binding of the polymorphic peptides, consistent with the results obtained in T cell cultures. Taken together these data suggest that anti-MHC autoreactive T cells are present in the periphery and that both auto and alloreactivity can be elicited by MHC peptides binding to MHC class II molecules.     

Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors

We are able to make reliable predictions of the efficiency with which peptides of arbitrary lengths will be transported by TAP. The pressure exerted by TAP on Ag presentation thus can be assessed by checking to what extent MHC class I (MHC-I)-presented epitopes can be discriminated from random peptides on the basis of predicted TAP transport efficiencies alone. Best discriminations were obtained when N-terminally prolonged epitope precursor peptides were included and the contribution of the N-terminal residues to the score were down-weighted in comparison with the contribution of the C terminus. We provide evidence that two factors may account for this N-terminal down-weighting: 1) the uncertainty as to which precursors are used in vivo and 2) the coevolution in the C-terminal sequence specificities of TAP and other agents in the pathway, which may vary among the various MHC-I alleles. Combining predictions of MHC-I binding affinities with predictions of TAP transport efficiency led to an improved identification of epitopes, which was not the case when predictions of MHC-I binding affinities were combined with predictions of C-terminal cleavages made by the proteasome.     

Correlation between simulated physicochemical properties and hemolycity of protegrin-like antimicrobial peptides: predicting experimental toxicity

The therapeutic, antibiotic potential of antimicrobial peptides can be prohibitively diminished because of the cytotoxicity and hemolytic profiles they exhibit. Quantifying and predicting antimicrobial peptide toxicity against host cells is thus an important goal of AMP related research. In this work, we present quantitative structure activity relationships for toxicity of protegrin-like antimicrobial peptides against human cells (epithelial and red blood cells) based on physicochemical properties, such as interaction energies and radius of gyration, calculated from molecular dynamics simulations of the peptides in aqueous solvent. The hypothesis is that physicochemical properties of peptides, as manifest by their structure and interactions in a solvent and as captured by atomistic simulations, are responsible for their toxicity against human cells. Protegrins are beta-hairpin peptides with high activity against a wide variety of microbial species, but in their native state are toxic to human cells. Sixty peptides with experimentally determined toxicities were used to develop the models. We test the resulting relationships to determine their ability to predict the toxicity of several protegrin-like peptides. The developed QSARs provide insight into the mechanism of cytotoxic action of antimicrobial peptides. In a subsequent blind test, the QSAR correctly ranked four of five protegrin analogues newly synthesized and tested for toxicity.     

Planar molecular arrangements aid the design of MHC class II binding peptides

The coupling between peptides and MHC-II proteins in the human immune system is not well understood. This work presents an evidence-based hypothesis of a guiding intermolecular force present in every human MHC-II protein (HLA-II). Previously, we examined the spatial positions of the fully conserved residues in all HLA-II protein types. In each one, constant planar patterns were revealed. These molecular planes comprise of amino acid groups of the same chemical species (for example, Gly) distributed across the protein structure. Each amino acid plane has a unique direction and this directional element offers spatial selectivity. Constant within all planes, too, is the presence of an aromatic residue possessing electrons in movement, leading the authors to consider that the planes generate electromagnetic fields that could serve as an attractive force in a single direction. Selection and attraction between HLA-II molecules and antigen peptides would, therefore, be non-random, resulting in a coupling mechanism as effective and rapid as is clearly required in the immune response. On the basis of planar projections onto the HLA-II groove, modifications were made by substituting the key residues in the class II-associated invariant chain peptide—a peptide with a universal binding affinity—resulting in eight different modified peptides with affinities greater than that of the unmodified peptide. Accurate and reliable prediction of MHC class II-binding peptides may facilitate the design of universal vaccine-peptides with greatly enhanced binding affinities. The proposed mechanisms of selection, attraction and coupling between HLA-II and antigen peptides are explained further in the paper.     

Soluble class I MHC with beta2-microglobulin covalently linked peptides: specific binding to a T cell hybridoma

Soluble forms of the mouse MHC class I molecule, Dd, were produced in which the peptide binding groove was uniformly occupied by peptides attached via a covalent flexible peptide linker to the N terminus of the associated beta2-microglobulin. The MHC heavy chain and beta2-microglobulin were firmly associated, and the molecules displayed an Ab epitope requiring proper occupancy of the peptide binding groove. Soluble Dd containing a covalent version of a well-characterized Dd-binding peptide from HIV stimulated a T cell hybridoma specific for this combination. Furthermore, a tetravalent version of this molecule bound specifically with apparent high avidity to this hybridoma.     

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.     

Receptor glycosylation regulates Ly-49 binding to MHC class I

Murine NK cells express the Ly-49 family of class I MHC-binding receptors that control their ability to lyse tumor or virally infected host target cells. X-ray crystallography studies have identified two predominant contact sites (sites 1 and 2) that are involved in the binding of the inhibitory receptor, Ly-49A, to H-2D(d). Ly-49G2 (inhibitory) and Ly-49D (activating) are highly homologous to Ly-49A and also recognize H-2D(d). However, the binding of Ly-49D and G(2) to H-2D(d) is of lower affinity than Ly-49A. All Ly-49s contain N-glycosylation motifs; however, the importance of receptor glycosylation in Ly-49-class I interactions has not been determined. Ly-49D and G(2) contain a glycosylation motif (NTT (221-223)), absent in Ly-49A, adjacent to one of the proposed binding sites for H-2D(d) (site 2). The presence of a complex carbohydrate group at this critical site could interfere with class I binding. In this study, we are able to demonstrate for the first time that Ly-49D binds H-2D(d) in the presence of mouse beta(2)-microglobulin. We also demonstrate that glycosylation of the NTT (221-23) motif of Ly-49D inteferes with recognition of H-2D(d). Alteration of the Ly-49D-NTT (221-23) motif to abolish glycosylation at this site resulted in enhanced H-2D(d) binding and receptor activation. Furthermore, glycosylation of Ly-49G2 at NTT (221-23) also reduces receptor binding to H-2D(d) tetramers. Therefore, the addition of complex carbohydrates to the Ly-49 family of receptors may represent a mechanism by which NK cells regulate affinity for host class I ligands.     

Peptide presentation by MHC class I molecules

The presentation of peptides by class I histocompatibility molecules plays a central role in the cellular immune response to virally infected or transformed cells. The main steps in this process include the degradation of both self and 'foreign' proteins to short peptides in the cytosol, translocation of peptides into the lumen of the endoplasmic reticulum, binding of a subset of peptides to assembling class I molecules and expression of class-I-peptide complexes at the cell surface for examination by cytotoxic T cells. A molecular understanding of most of these steps is emerging, revealing a remarkable coordination between the processes of peptide translocation, delivery and binding to class I molecules.     

Gene transfer preferentially selects MHC class I positive tumour cells and enhances tumour immunogenicity

The modulated expression of MHC class I on tumour tissue is well documented. Although the effect of MHC class I expression on the tumorigenicity and immunogenicity of MHC class I negative tumour cell lines has been rigorously studied, less is known about the validity of gene transfer and selection in cell lines with a mixed MHC class I phenotype. To address this issue we identified a C26 cell subline that consists of distinct populations of MHC class I (H-2D/K) positive and negative cells. Transient transfection experiments using liposome-based transfer showed a lower transgene expression in MHC class I negative cells. In addition, MHC class I negative cells were more sensitive to antibiotic selection. This led to the generation of fully MHC class I positive cell lines. In contrast to C26 cells, all transfectants were rejected in vivo and induced protection against the parental tumour cells in rechallenge experiments. Tumour cell specificity of the immune response was demonstrated in in vitro cytokine secretion and cytotoxicity assays. Transfectants expressing CD40 ligand and hygromycin phosphotransferase were not more immunogenic than cells expressing hygromycin resistance alone. We suggest that the MHC class I positive phenotype of the C26 transfectants had a bearing on their immunogenicity, because selected MHC class I positive cells were more immunogenic than parental C26 cells and could induce specific anti-tumour immune responses. These data demonstrate that the generation of tumour cell transfectants can lead to the selection of subpopulations that show an altered phenotype compared to the parental cell line and display altered immunogenicity independent of selection marker genes or other immune modulatory genes. Our results show the importance of monitoring gene transfer in the whole tumour cell population, especially for the evaluation of in vivo therapies targeted to heterogeneous tumour cell populations.     

OETMAP: a new feature encoding scheme for MHC class I binding prediction

Deciphering the understanding of T cell epitopes is critical for vaccine development. As recognition of specific peptides bound to Major histocompatibility complex (MHC) class I molecules, cytotoxic T cells are activated. This is the major step to initiate of immune system response. Knowledge of the MHC specificity will enlighten the way of diagnosis, treatment of pathogens as well as peptide vaccine development. So far, a number of methods have been developed to predict MHC/peptide binding. In this article, a novel feature amino acid encoding scheme is proposed to predict MHC/peptide complexes. In the proposed method, we have combined orthonormal encoding (OE) and Taylor’s Venn-diagram, and have used Linear support vector machines as the classifier in the tests. We also have compared our method to current feature encoding scheme techniques. The tests have been carried out on comparatively large Human leukocyte antigen (HLA)-A and HLA-B allele peptide three binding datasets extracted from the Immune epitope database and analysis resource. On three datasets experimented, the IC50 cutoff a criteria is used to select the binders and non-binders peptides. Experimental results show that our amino acid encoding scheme leads to better classification performance than other amino acid encoding schemes on a standalone classifier.     

A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes

In the present study, a systematic attempt has been made to develop an accurate method for predicting MHC class I restricted T cell epitopes for a large number of MHC class I alleles. Initially, a quantitative matrix (QM)-based method was developed for 47 MHC class I alleles having at least 15 binders. A secondary artificial neural network (ANN)-based method was developed for 30 out of 47 MHC alleles having a minimum of 40 binders. Combination of these ANN-and QM-based prediction methods for 30 alleles improved the accuracy of prediction by 6% compared to each individual method. Average accuracy of hybrid method for 30 MHC alleles is 92.8%. This method also allows prediction of binders for 20 additional alleles using QM that has been reported in the literature, thus allowing prediction for 67 MHC class I alleles. The performance of the method was evaluated using jack-knife validation test. The performance of the methods was also evaluated on blind or independent data. Comparison of our method with existing MHC binder prediction methods for alleles studied by both methods shows that our method is superior to other existing methods. This method also identifies proteasomal cleavage sites in antigen sequences by implementing the matrices described earlier. Thus, the method that we discover allows the identification of MHC class I binders (peptides binding with many MHC alleles) having proteasomal cleavage site at C-terminus. The user-friendly result display format (HTML-II) can assist in locating the promiscuous MHC binding regions from antigen sequence. The method is available on the web at www.imtech.res.in/raghava/nhlapred and its mirror site is available at http://bioinformatics.uams.edu/mirror/nhlapred/.     

Distribution of tripeptides in MHC binding peptides

Major Histocompatibility Complex (MHC) molecules are cell surface glycoproteins that are central to the process of immunity. MHC Class I and II molecules differ in their peptide binding specificity. In this study we have analyzed a non redundant set of MHC binding peptides derived from MHCPEP database, in terms of tripeptides and their positional preference. Results indicate that certain tripeptides have a preference to appear at a particular position for a specific allele. Further, the distribution of rigid tripeptides across all binding sequences was also analyzed and their positions were correlated with anchor residue positions.