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PubMed2026

Immunopeptidomics-driven MHC class II peptide-binding motif discovery for 2 common canine DR alleles.

Despite the central role of major histocompatibility complex (MHC) class II in adaptive immunity, peptide-binding motifs have yet to be characterized for any canine MHC class II allele. Here, we report the first immunopeptidomics-derived binding motifs for DLA-DRB1*015:01 (DLA-DR15) and DLA-DRB1*012:01 (DLA-DR12), 2 alleles overrepresented in breeds predisposed to immune-mediated diseases. Because dogs co-express DLA-DR and DLA-DQ, the MHC class II Ab clone YKIX334.2 was validated to be DLA-DR-specific, enabling allele-selective immunoaffinity purification of DLA-DR molecules from homozygous DLA-DR15 and DLA-DR12 donor spleens. Mass spectrometry and GibbsCluster motif deconvolution of 838 DLA-DR15-associated and 644 DLA-DR12-associated peptides eluted from their respective peptide-binding grooves revealed distinct allele-specific binding motifs, with characterization of anchor residue preferences, peptide-length distributions, cross-species comparisons with human and murine MHC class II motifs, and source protein composition of the eluted self-peptidome. To evaluate the translational utility of these motifs, recombinant DLA-DR15 and DLA-DR12 molecules were used to screen rabies virus glycoprotein and nucleoprotein peptide libraries via fluorescence-based peptide competition assays, identifying high-affinity candidate binders for both alleles. Spearman rank correlation between immunopeptidomics-derived position-specific scoring matrix scores and peptide competition assay rankings demonstrated modest associations, consistent with these approaches capturing complementary dimensions of peptide-MHC class II interaction. Ultimately, these findings establish what we believe is the first allele-specific peptide-binding motif framework for canine MHC class II, providing a foundation for DLA-allele-informed CD4+ T-cell epitope discovery studies and Ag-specific immune response characterization in the dog.

Animals↗

PubMed2002

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. RESULTS: Here, we present a novel approach, SVMHC, based on support vector machines to predict the binding of peptides to MHC class I molecules. This method seems to perform slightly better than two profile based methods, SYFPEITHI and HLA_BIND. The implementation of SVMHC is quite simple and does not involve any manual steps, therefore as more data become available it is trivial to provide prediction for more MHC types. SVMHC currently contains prediction for 26 MHC class I types from the MHCPEP database or alternatively 6 MHC class I types from the higher quality SYFPEITHI database. The prediction models for these MHC types are implemented in a public web service available at http://www.sbc.su.se/svmhc/. CONCLUSIONS: Prediction of MHC class I binding peptides using Support Vector Machines, shows high performance and is easy to apply to a large number of MHC class I types. As more peptide data are put into MHC databases, SVMHC can easily be updated to give prediction for additional MHC class I types. We suggest that the number of binding peptides needed for SVM training is at least 20 sequences.

Animals↗

PubMed2005

Ganglioside GM1-binding peptides as adjuvants of antigens inoculated by the intranasal route.

Forty-five GM1-binding peptides were identified using phage-displayed peptides libraries of random peptides. Most have a motif containing a hydrophobic amino acid followed by a serine (S). Based on a GM1-binding assays, two of these GM1-binding peptides (named 15 and 40) were chosen to investigate its immunostimulatory properties when chemically coupled to antigens. Mice intra-nasally (i.n.) vaccinated with some of these complexes developed a better local and systemic antibody response than mice i.n. vaccinated with the respective uncoupled antigens. The efficiency of the complex GM1-binding peptide-antigen strongly depends on the composition and structure of both of the components of the complex.

Adjuvants, Immunologic↗

PubMed1993

Roles of the six peptide-binding pockets of the HLA-A2 molecule in allorecognition by human cytotoxic T-cell clones.

To evaluate the contribution of the major histocompatibility complex class I pockets to the binding of self-peptides recognized by alloreactive cytotoxic T-lymphocyte (CTL) clones, we have constructed an extensive library of HLA-A2 mutants with different amino acid substitutions in each of the six pockets. When these mutants were tested in cytotoxicity assays with a panel of HLA-A2-specific alloreactive CTL clones, each CTL clone showed a unique pattern of reactivity, implying the different contributions of each pocket to binding individual peptides. We noted that the majority of the mutants in pocket B significantly affect recognition by the CTL clones. Unexpectedly, the mutations influencing allorecognition are found in all other pockets as well. Overall, this study demonstrates that each of the six peptide-binding pockets plays an important and distinct role in binding of self-peptides required for recognition of the HLA-A2 molecule by alloreactive CTLs.

Cell Death↗

PubMed2003

Detailed analysis of the effects of Glu/Lys beta69 human leukocyte antigen-DP polymorphism on peptide-binding specificity.

The polymorphism at position beta69 of the human leukocyte antigen (HLA)-DP molecule has been associated with susceptibility to several immune disorders and alloreactivity. Using molecular modeling, we have predicted a detailed structure of the HLA-DP2 molecule (carrying Glubeta69) complexed with class II associated invariant chain derived peptide (CLIP) and compared it with the form carrying Lys at beta69 (HLA-DP2K69). Major changes between the two models were observed in the shape and charge distribution of pocket 4 and of the nearby pocket 6. Consequently, we analyzed in detail the peptide-binding specificities of both HLA-DP molecules expressed as recombinant proteins. We first determined that the minimum peptide-binding core of CLIP for both HLA-DP2 and DP2K69 is represented by nine aminoacids corresponding to the sequence 91-99 of invariant chain (Ii). We then assessed the peptide-binding specificities of the two pockets and determined the role of position beta69, using competition tests with the Ii-derived peptide CLIP and its mutated forms carrying all the aminoacidic substitutions in P4 and P6. Pocket 4 of HLA-DP2 showed high affinity for positively charged, aromatic, and polar residues, whereas aliphatic residues were disfavored. Pocket 4 of the DP2K69 variant showed a reduced aminoacid selectivity with aromatic residues most preferred. Pocket 6 of HLA-DP2 showed high affinity for aromatic residues, which was increased in DP2K69 and extended to arginine. Finally, we used the experimental data to determine the best molecular-modeling approach for assessing aminoacid selectivity of the two pockets. The results with best predictive value were obtained when single aminoacids were evaluated inside each single pocket, thus, reducing the influence of the overall peptide/ major histocompatibility complex interaction. In conclusion, the HLA-DPbeta69 polymorphism plays a fundamental role in the peptide-binding selectivity of HLA-DP. Furthermore, as this polymorphism is the main change in the pocket 4 area of HLA-DP, it could represent a supertype among HLA-DP molecules significantly contributing to the selection of epitopes presented in the context of this HLA isotype.

Amino Acid Sequence↗

PubMed2003

Searching sequence space for high-affinity binding peptides using ribosome display.

We present the construction of a synthetic library based on the scaffold of bovine heart fatty acid-binding protein (FABP) with 1.1x10(14) independent members. Ribosome display was applied to select streptavidin-binding peptides in vitro from 2x10(13) molecules of the library each encoding FABP with 15 contiguous random amino acid residues at its N terminus. The selection yielded several different binding peptides. The best binder possessed a dissociation constant as low as 4nM and, in contrast to the previously isolated peptides, contained no HPQ motif. A substitution analysis enabled shortening of the 15-mer peptide and revealed a 9-mer variant with a dissociation constant of 17nM, which is a 1000-fold increase of affinity compared to the already known peptides of this size. This high-affinity binding peptide in combination with the whole set of streptavidin conjugates should be an extremely useful tool for the detection and purification of recombinant proteins.

Animals↗

PubMed2006

Statistical deconvolution of enthalpic energetic contributions to MHC-peptide binding affinity.

BACKGROUND: MHC Class I molecules present antigenic peptides to cytotoxic T cells, which forms an integral part of the adaptive immune response. Peptides are bound within a groove formed by the MHC heavy chain. Previous approaches to MHC Class I-peptide binding prediction have largely concentrated on the peptide anchor residues located at the P2 and C-terminus positions. RESULTS: A large dataset comprising MHC-peptide structural complexes was created by re-modelling pre-determined x-ray crystallographic structures. Static energetic analysis, following energy minimisation, was performed on the dataset in order to characterise interactions between bound peptides and the MHC Class I molecule, partitioning the interactions within the groove into van der Waals, electrostatic and total non-bonded energy contributions. CONCLUSION: The QSAR techniques of Genetic Function Approximation (GFA) and Genetic Partial Least Squares (G/PLS) algorithms were used to identify key interactions between the two molecules by comparing the calculated energy values with experimentally-determined BL50 data. Although the peptide termini binding interactions help ensure the stability of the MHC Class I-peptide complex, the central region of the peptide is also important in defining the specificity of the interaction. As thermodynamic studies indicate that peptide association and dissociation may be driven entropically, it may be necessary to incorporate entropic contributions into future calculations.

Binding Sites↗

PubMed2006

Learning MHC I--peptide binding.

MOTIVATION AND RESULTS: Motivated by the ability of a simple threading approach to predict MHC I--peptide binding, we developed a new and improved structure-based model for which parameters can be estimated from additional sources of data about MHC-peptide binding. In addition to the known 3D structures of a small number of MHC-peptide complexes that were used in the original threading approach, we included three other sources of information on peptide-MHC binding: (1) MHC class I sequences; (2) known binding energies for a large number of MHC-peptide complexes; and (3) an even larger binary dataset that contains information about strong binders (epitopes) and non-binders (peptides that have a low affinity for a particular MHC molecule). Our model significantly outperforms the standard threading approach in binding energy prediction. In our approach, which we call adaptive double threading, the parameters of the threading model are learnable, and both MHC and peptide sequences can be threaded onto structures of other alleles. These two properties make our model appropriate for predicting binding for alleles for which very little data (if any) is available beyond just their sequence, including prediction for alleles for which 3D structures are not available. The ability of our model to generalize beyond the MHC types for which training data is available also separates our approach from epitope prediction methods which treat MHC alleles as symbolic types, rather than biological sequences. We used the trained binding energy predictor to study viral infections in 246 HIV patients from the West Australian cohort, and over 1000 sequences in HIV clade B from Los Alamos National Laboratory database, capturing the course of HIV evolution over the last 20 years. Finally, we illustrate short-, medium-, and long-term adaptation of HIV to the human immune system. AVAILABILITY: http://www.research.microsoft.com/~jojic/hlaBinding.html.

Algorithms↗

PubMed2005

Characterization of the peptide-binding specificity of Mamu-A*11 results in the identification of SIV-derived epitopes and interspecies cross-reactivity.

The SIV-infected Indian rhesus macaque is the most established model of HIV infection, providing insight into pathogenesis and a system for testing novel vaccines. However, only a limited amount of information is available regarding the peptide-binding motifs and epitopes bound by their class I and class II MHC molecules. In this study, we utilized a library of over 1,000 different peptides and a high throughput MHC-peptide binding assay to detail the binding specificity of the rhesus macaque class I molecule Mamu-A*11. These studies defined the fine specificity of primary anchor positions, and dissected the role of secondary anchors, for peptides of 8-11 residues in length. This detailed information was utilized to develop size-specific polynomial algorithms to predict Mamu-A*11 binding capacity. Testing SIVmac239-derived Mamu-A*11 binding peptides for recognition by peripheral blood mononuclear cells (PBMC) from Mamu-A*11-positive, SIV-infected macaques, identified five novel SIV-derived Mamu-A*11 epitopes. Finally, we detected extensive cross-reactivity at the binding level between Mamu-A*11 and the mouse H-2 class I molecule Kk. Further experiments revealed that three out of four Mamu-A*11 binding peptides which bound Kk and were immunogenic in Kk mice were also recognized in Mamu-A*11-infected macaques. This is the first detailed description of mouse-macaque interspecies cross-reactivity, potentially useful in testing novel vaccines in mice and macaques.

Amino Acid Sequence↗

PubMed2001

Molecular determinants of peptide binding to two common rhesus macaque major histocompatibility complex class II molecules.

Major histocompatibility complex class II molecules encoded by two common rhesus macaque alleles Mamu-DRB1*0406 and Mamu-DRB*w201 have been purified, and quantitative binding assays have been established. The structural requirements for peptide binding to each molecule were characterized by testing panels of single-substitution analogs of the two previously defined epitopes HIV Env242 (Mamu-DRB1*0406 restricted) and HIV Env482 (Mamu-DRB*w201 restricted). Anchor positions of both macaque DR molecules were spaced following a position 1 (P1), P4, P6, P7, and P9 pattern. The specific binding motif associated with each molecule was distinct, but largely overlapping, and was based on crucial roles of aromatic and/or hydrophobic residues at P1, P6, and P9. Based on these results, a tentative Mamu class II DR supermotif was defined. This pattern is remarkably similar to a previously defined human HLA-DR supermotif. Similarities in binding motifs between human HLA and macaque Mamu-DR molecules were further illustrated by testing a panel of more than 60 different single-substitution analogs of the HLA-DR-restricted HA 307-319 epitope for binding to Mamu-DRB*w201 and HLA-DRB1*0101. The Mamu-DRB1*0406 and -DRB*w201 binding capacity of a set of 311 overlapping peptides spanning the entire simian immunodeficiency virus (SIV) genome was also evaluated. Ten peptides capable of binding both molecules were identified, together with 19 DRB1*0406 and 43 DRB*w201 selective binders. The Mamu-DR supermotif was found to be present in about 75% of the good binders and in 50% of peptides binding with intermediate affinity but only in approximately 25% of the peptides which did not bind either Mamu class II molecule. Finally, using flow cytometric detection of antigen-induced intracellular gamma interferon, we identify a new CD4(+) T-lymphocyte epitope encoded within the Rev protein of SIV.

Amino Acid Sequence↗

PubMed1998

RNA bulge entropies in the unbound state correlate with peptide binding strengths for HIV-1 and BIV TAR RNA because of improved conformational access.

For the binding of peptides to wild-type HIV-1 and BIV TAR RNA and to mutants with bulges of various sizes, changes in the DeltaDelta G values of binding were determined from experimental K d values. The corresponding entropies of these bulges are estimated by enumerating all possible RNA bulge conformations on a lattice and then applying the Boltzmann relationship. Independent calculations of entropies from fluctuations are also carried out using the Gaussian network model (GNM) recently introduced for analyzing folded structures. Strong correlations are seen between the changes in free energy determined for binding and the two different unbound entropy calculations. The fact that the calculated entropy increase with larger bulge size is correlated with the enhanced experimental binding free energy is unusual. This system exhibits a dependence on the entropy of the unbound form that is opposite to usual binding models. Instead of a large initial entropy being unfavorable since it would be reduced upon binding, here the larger entropies actually favor binding. Several interpretations are possible: (i) the higher conformational freedom implies a higher competence for binding with a minimal strain, by suitable selection amongst the set of already accessible conformations; (ii) larger bulge entropies enhance the probability of the specific favorable conformation of the bound state; (iii) the increased freedom of the larger bulges contri-butes more to the bound state than to the unbound state; (iv) indirectly the large entropy of the bound state might have an unfavorable effect on the solvent structure. Nonetheless, this unusual effect is interesting.

Animals↗

PubMed2000

Identification of regions in the Moloney murine leukemia virus SU protein that tolerate the insertion of an integrin-binding peptide.

Targeting of retroviral vectors to specific cells has been attempted through engineering of the surface (SU) protein of the murine leukemia viruses (MuLVs), but in many cases this has adversely affected protein function and targeted delivery has been difficult to achieve. In this study, we have inserted a 15-mer peptide that binds specifically to the alpha(v)beta(3) integrin into the Moloney MuLV SU protein, including regions that are surface exposed in the crystal structure of the ecotropic receptor-binding domain. We have concentrated in particular on the variable regions VRA, VRB, and VRC, which are responsible for the use of distinct cellular receptors by different MuLV subtypes and therefore may be more likely to accommodate a heterologous binding moiety. Despite these considerations, only 8 of 26 insertion sites were tolerated, including two separate regions in VRA, a cluster of sites in VRC, and previously identified sites at the N-terminus of the protein and in the proline-rich region immediately downstream of the receptor-binding domain. When expressed on retroviral vector particles, all of the viable proteins retained the ability to bind to and transduce murine cells, although the VRC mutants and an insertion in VRA gave reduced binding and titer. Finally, although all of the viable chimeras could bind to alpha(v)beta(3) in a solid-phase binding assay, we were unable to demonstrate expanded tropism for alpha(v)beta(3)-expressing human cells. This study highlights the difficulty of engineering the Moloney MuLV SU protein, even when structural information is available, and provides guidelines for the insertion of peptide ligands into the SU protein.

Amino Acid Sequence↗

PubMed2000

Peptide design based on an antibody complementarity-determining region (CDR): construction of porphyrin-binding peptides and their affinity maturation by a combinatorial method.

We have utilized sequence information from an antiheme monoclonal antibody to develop novel porphyrin-binding peptides. Several peptides which have an intramolecular disulfide bond in different positions and different chain lengths were prepared. The affinities of peptides for meso-tetrakis(4-carboxyphenyl)porphyrin were increased by an appropriate conformational restraint using a disulfide bond. Detailed studies with a representative 12-peptide, 12C4, whose length was reduced from 20 residues of the complementarity-determining region (CDR), indicated that both the hydrophobic and electrostatic interactions were essential factors in the peptide-porphyrin binding. Moreover, two-dimensional 1H NMR spectroscopy revealed the conformation of the peptide and the critical residues for the porphyrin-binding. According to the obtained results, a further minimized 9-peptide, 9L, was successfully redesigned with a sequence capable of forming a beta-turn instead of a disulfide bond. Furthermore, affinity maturation studies of 9L were performed by using a combinatorial approach such as the spot-synthesis method. Peptides with an improved affinity for porphyrins were prepared by systematic amino acid replacement. Thus, the design of peptides targeted to porphyrins was demonstrated by the combination of antibody information and the rationally designed combinatorial method.

Amino Acid Sequence↗

PubMed1994

[Structure of MHC molecules and binding peptides].

MHC class I associates with beta 2-microglobulin and one of a range of short peptides which bind to the groove formed by two alpha helix and beta sheet on the alpha 1 and alpha 2 domains of the class I molecules. The class I molecules present the peptides with allele-specific motif to T cells. Recent studies showed that melanoma specific CTL and minor histocompatibility specific CTL recognize peptides presented by the class I molecules. Further studies of peptides bound to the class I and class II molecules are expected to identify peptides which induce autoimmune disease.

Animals↗

PubMed2006

Identification of a small topoisomerase I-binding peptide that has synergistic antitumor activity with 9-aminocamptothecin.

The topoisomerase I (top1)-targeted camptothecin class of anticancer drugs is important in the treatment of several types of cancers. This class of drug inhibits the top1 enzyme during its catalytic DNA relaxation cycle, stabilizing the transient covalent top1-DNA complex by simultaneous noncovalent interactions with DNA and top1. We examined top1 using phage display because of the significance of this known top1-directed drug action. Several peptides that bind top1 were discovered and these were examined for top1 affinity, top1 catalytic and cleavage complex effects, and cytotoxic effects in cultured cell lines and in an in vivo tumor model. Although several peptides exhibited nanomolar and low-micromolar affinity for top1, none had cytotoxic effects when administered alone. However, in combination with 9-aminocamptothecin, one 15-mer peptide (SAYAATVRGPLSSAS) had synergistic cytotoxic effects with 9-aminocamptothecin both in the cytotoxicity assay and in nude mouse xenograft human tumor models. This report details the investigation of this peptide.

Amino Acid Sequence↗

PubMed1998

Structural principles that govern the peptide-binding motifs of class I MHC molecules.

The peptides that bind class I MHC molecules are restricted in length and often contain key amino acids, anchor residues, at particular positions. The side-chains of peptide anchor residues interact with the polymorphic complementary pockets in MHC peptide-binding grooves and provide the molecular basis for allele-specific recognition of antigenic peptides. We establish correlations between class I MHC specificities for anchor residues and class I MHC sequence markers that occur at the polymorphic positions lining the structural pockets. By analyzing the pocket structures of nine crystallized class I MHC molecules and the modeled structures of another 39 class I MHC molecules, we show that class I pockets can be classified into families that are distinguishable by their common physico-chemical properties and peptide side-chain selectivities. The identification of recurrent structural principles among class I pockets makes it possible to greatly expand the repertoire of known peptide-binding motifs of class I MHC molecules. The evolutionary strategies underlying the emergence of pocket families is briefly discussed.

Alleles↗

PubMed2002

Radicicol-sensitive peptide binding to the N-terminal portion of GRP94.

GRP94 is a molecular chaperone that carries immunologically relevant peptides from cell to cell, transferring them to major histocompatibility proteins for presentation to T cells. Here we examine the binding of several peptides to recombinant GRP94 and study the regulation and site of peptide binding. We show that GRP94 contains a peptide-binding site in its N-terminal 355 amino acids. A number of peptides bind to this site with low on- and off-rates and with specificity that is distinct from that of another endoplasmic reticulum chaperone, BiP/GRP78. Binding to the N-terminal fragment is sufficient to account for the peptide binding activity of the entire molecule. Peptide binding is inhibited by radicicol, a known inhibitor of the chaperone activities of HSP90-family proteins. However, the peptide-binding site is distinct from the radicicol-binding pocket, because both can bind to the N-terminal fragment simultaneously. Furthermore, peptide binding does not cause the same conformational change as does binding of radicicol. When the latter binds to the N-terminal domain, it induces a conformational change in the downstream, acidic domain of GRP94, as measured by altered gel mobility and loss of an antibody epitope. These results relate the peptide-binding activity of GRP94 to its other function as a chaperone.

Amino Acid Sequence↗

PubMed2005

Predictive Bayesian neural network models of MHC class II peptide binding.

We used Bayesian regularized neural networks to model data on the MHC class II-binding affinity of peptides. Training data consisted of sequences and binding data for nonamer (nine amino acid) peptides. Independent test data consisted of sequences and binding data for peptides of length </=25. We assumed that MHC class II-binding activity of peptides depends only on the highest ranked embedded nonamer and that reverse sequences of active nonamers are inactive. We also internally validated the models by using 30% of the training data in an internal test set. We obtained robust models, with near identical statistics for multiple training runs. We determined how predictive our models were using statistical tests and area under the Receiver Operating Characteristic (ROC) graphs (A(ROC)). Most models gave training A(ROC) values close to 1.0 and test set A(ROC) values >0.8. We also used both amino acid indicator variables (bin20) and property-based descriptors to generate models for MHC class II-binding of peptides. The property-based descriptors were more parsimonious than the indicator variable descriptors, making them applicable to larger peptides, and their design makes them able to generalize to unknown peptides outside of the training space. None of the external test data sets contained any of the nonamer sequences in the training sets. Consequently, the models attempted to predict the activity of truly unknown peptides not encountered in the training sets. Our models were well able to tackle the difficult problem of correctly predicting the MHC class II-binding activities of a majority of the test set peptides. Exceptions to the assumption that nonamer motif activities were invariant to the peptide in which they were embedded, together with the limited coverage of the test data, and the fuzziness of the classification procedure, are likely explanations for some misclassifications.

Amino Acid Sequence↗