Biomedical subjects

Y Altuvia

Publications and source records attributed to Y Altuvia.

7 recordsLinked to original sources

PubMed2001

Examination of possible structural constraints of MHC-binding peptides by assessment of their native structure within their source proteins.

Antigenic peptides bind to major histocompatibility complex (MHC) molecules as a prerequisite for their presentation to T cells. In this study, we investigate possible structural preferences of MHC-binding peptides by examining the conformation space defined by the structures of these peptides within their native source proteins. Comparison of the conformation space of the native structures of MHC-binding nonamers and a corresponding conformation space defined by a random set of nonamers showed no significant difference. This suggests that the environment of the MHC binding groove has evolved to bind peptides with essentially any "structural background." A slight tendency for an extended beta-conformation at positions 8 and 9 was observed for the set of native structures. We suggest that such a preference may facilitate the binding of the C-terminal anchor position of processed peptides into the corresponding specificity pocket. MHC-binding peptides represent examples of short subsequences that are present in two different structural environments: within their native protein and within the MHC binding groove. Comparison of the native and of the bound structure of the peptides showed that peptides up to 14 residues long may adopt different conformations within different protein environments. This has direct implications for structure prediction algorithms.

Amino Acid Sequence↗

PubMed2001

Harnessing the cellular immune system to the gene-prediction cart.

Prediction of genes and verification of their bona fide expression in the cell are major challenges of the post-genomic era. Here, we demonstrate how information from the apparently unrelated field of cellular immunology can be recruited for these challenging tasks. The cellular immune system presents short peptides that are the degradation products of both foreign and self-proteins expressed in the cell. We carried out a comprehensive search comparing these peptides to all accumulated human sequence data. Our findings illustrate how these 'presented self-peptides' are informative for the identification of new genes, for hypothetical gene verification, for verifying gene expression at the protein level and for supporting splice junctions.

Antigen Presentation↗

PubMed2000

Sequence signals for generation of antigenic peptides by the proteasome: implications for proteasomal cleavage mechanism.

Proteasomal cleavage of proteins is the first step in the processing of most antigenic peptides that are presented to cytotoxic T cells. Still, its specificity and mechanism are not fully understood. To identify preferred sequence signals that are used for generation of antigenic peptides by the proteasome, we performed a rigorous analysis of the residues at the termini and flanking regions of naturally processed peptides eluted from MHC class I molecules. Our results show that both the C terminus (position P1 of the cleavage site) and its immediate flanking position (P1') possess significant signals. The N termini of the peptides show these signals only weakly, consistent with previous findings that antigenic peptides may be cleaved by the proteasome with N-terminal extensions. Nevertheless, we succeed to demonstrate indirectly that the N-terminal cleavage sites contain the same preferred signals at position P1'. This reinforces previous findings regarding the role of the P1' position of a cleavage site in determining the cleavage specificity, in addition to the well-known contribution of position P1. Our results apply to the generation of antigenic peptides and bare direct implications for the mechanism of proteasomal cleavage. We propose a model for proteasomal cleavage mechanism by which both ends of cleaved fragments are determined by the same cleavage signals, involving preferred residues at both P1 and P1' positions of a cleavage site. The compatibility of this model with experimental data on protein degradation products and generation of antigenic peptides is demonstrated.

Animals↗

PubMed2000

Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles.

Specific binding of antigenic peptides to major histocompatibility complex (MHC) class I molecules is a prerequisite for their recognition by cytotoxic T-cells. Prediction of MHC-binding peptides must therefore be incorporated in any predictive algorithm attempting to identify immunodominant T-cell epitopes, based on the amino acid sequence of the protein antigen. Development of predictive algorithms based on experimental binding data requires experimental testing of a very large number of peptides. A complementary approach relies on the structural conservation observed in crystallographically solved peptide-MHC complexes. By this approach, the peptide structure in the MHC groove is used as a template upon which peptide candidates are threaded, and their compatibility to bind is evaluated by statistical pairwise potentials. Our original algorithm based on this approach used the pairwise potential table of Miyazawa and Jernigan (Miyazawa S, Jernigan RL, 1996, J Mol Biol 256:623-644) and succeeded to correctly identify good binders only for MHC molecules with hydrophobic binding pockets, probably because of the high emphasis of hydrophobic interactions in this table. A recently developed pairwise potential table by Betancourt and Thirumalai (Betancourt MR, Thirumalai D, 1999, Protein Sci 8:361-369) that is based on the Miyazawa and Jernigan table describes the hydrophilic interactions more appropriately. In this paper, we demonstrate how the use of this table, together with a new definition of MHC contact residues by which only residues that contribute exclusively to sequence specific binding are included, allows the development of an improved algorithm that can be applied to a wide range of MHC class I alleles.

Alleles↗

PubMed1997

A structure-based algorithm to predict potential binding peptides to MHC molecules with hydrophobic binding pockets.

Binding of peptides to MHC class I molecules is a prerequisite for their recognition by cytotoxic T cells. Consequently, identification of peptides that will bind to a given MHC molecule must constitute a central part of any algorithm for prediction of T-cell antigenic peptides based on the amino acid sequence of the protein. Binding motifs, defined by anchor positions only, have proven to be insufficient to ensure binding, suggesting that other positions along the peptide sequence also affect peptide-MHC interaction. The second phase of prediction schemes therefore take into account the effect of all positions along the peptide sequence, and are based on position-dependent-coefficients that are used in the calculation of a peptide score. These coefficients can be extracted from a large ensemble of binding sequences that were tested experimentally, or derived from structural considerations, as in the algorithm developed by us recently. This algorithm uses the coordinates of solved complexes to evaluate the interactions of peptide amino acids with MHC contact residues, and results in a peptide score that reflects its binding energy. Here we present our analysis for peptide binding to four MHC alleles (HLA-A2, HLA-A68, HLA-B27 and H-2Kb), and compare the predictions of the algorithm to experimental binding data. The algorithm performs successfully in predicting peptide binding to MHC molecules with hydrophobic binding pockets but not when MHC molecules with hydrophilic, charged pockets are considered. For MHC molecules with hydrophobic pockets it is demonstrated how the algorithm succeeds in distinguishing binding from non-binding peptides, and in high ranking of immunogenic peptides within all overlapping same-length peptides spanning their respective protein sequences. The latter property of the algorithm makes it a useful tool in the rational design of peptide vaccines aimed at T-cell immunity.

Algorithms↗

PubMed1995

Ranking potential binding peptides to MHC molecules by a computational threading approach.

In this paper, an approach developed to address the inverse protein folding problem is applied to prediction of potential binding peptides to a specific major histocompatibility complex (MHC) molecule. Overlapping peptides, spanning the entire protein sequence, are threaded through the backbone coordinates of a known peptide fold in the MHC groove, and their interaction energies are evaluated using statistical pairwise contact potentials. With currently available tables for pairwise potentials, promising results are obtained for MHC-peptide complexes where hydrophobic interactions predominate. By ranking the peptides in an ascending order according to their energy values, it is demonstrated that, in most cases, known antigenic peptides are highly ranked. Furthermore, predicted hierarchies are consistent with experimental binding results. Currently, predictions of potential binding peptides to a specific MHC molecule are based on the identification of allele-specific binding motifs. However, it has been demonstrated that these motifs are neither sufficient nor strictly required to ensure binding. The computational procedure presented here succeeds in determining the MHC binding potential of peptides along a protein amino acid sequence, without relying on binding motifs. The proposed scheme may significantly reduce the number of peptides to be tested, identify good binders that do not necessarily show the known allele-specific binding motifs, and identify the best candidates among those with the motifs. In general, when structural information about a protein-peptide complex is available, the current application of the threading approach can be used to screen a large library of peptides for selection of the best binders to the target protein.

Amino Acid Sequence↗

PubMed1994

Sequence features that correlate with MHC restriction.

Identification of common sequence motifs in antigenic peptides restricted to a specific class II molecule has not been easy due to the large variation in length and sequence that is observed in these peptides. The goal of this study is to develop an automated computerized method for the identification of sequence features and structural determinants that play a role in the MHC restriction of helper T-cell antigenic peptides. For this, we compiled an extended database of helper T-cell sites, including the information on MHC restriction, when available. Two groups of peptides are assigned to each MHC type: (1) peptides that bind to that MHC molecule to elicit a T-cell response, and (2) peptides that were shown experimentally either not to bind to or not to elicit a T-cell proliferative response in association with that MHC molecule. We search for common motifs in the group of binding peptides, and identify significant motifs that are frequent among these peptides but almost absent in the group of non-binding peptides. A motif consists of physical-chemical and structural properties that may be responsible for binding specificity and can be extracted from sequence data, such as, hydrophobicity, charge, hydrogen bonding capability, etc. The first search is performed on the non-aligned binding peptides. Next, the sequences are aligned according to an identified motif and a search for additional, conserved, properties is performed. The statistical significance of the motifs is evaluated as well as their compatibility with published experimental results on substitution effects. Here we demonstrate the general scheme of the analysis and results for I-Ek and I-Ak associated peptides.

Amino Acid Sequence↗