SVM and SVR-based MHC-binding prediction using a mathematical presentation of peptide sequences.

At present, there are a number of methods for the prediction of T-cell epitopes and major histocompatibility complex (MHC)-binding peptides. Despite numerous methods for predicting T-cell epitopes, there still exist limitations that affect the reliability of prevailing methods. For this reason, the development of models with high accuracy are crucial. An accurate prediction of the peptides that bind to specific major histocompatibility complex class I and II (MHC-I and MHC-II) molecules is important for an understanding of the functioning of the immune system and the development of peptide-based vaccines. Peptide binding is the most selective step in identifying T-cell epitopes. In this paper, we present a new approach to predicting MHC-binding ligands that takes into account new weighting schemes for position-based amino acid frequencies, BLOSUM and VOGG substitution of amino acids, and the physicochemical and molecular properties of amino acids. We have made models for quantitatively and qualitatively predicting MHC-binding ligands. Our models are based on two machine learning methods support vector machine (SVM) and support vector regression (SVR), where our models have used for feature selection, several different encoding and weighting schemes for peptides. The resulting models showed comparable, and in some cases better, performance than the best existing predictors. The obtained results indicate that the physicochemical and molecular properties of amino acids (AA) contribute significantly to the peptide-binding affinity.

Software tools for simultaneous data visualization and T cell epitopes and disorder prediction in proteins.

We have developed EpDis and MassPred, extendable open source software tools that support bioinformatic research and enable parallel use of different methods for the prediction of T cell epitopes, disorder and disordered binding regions and hydropathy calculation. These tools offer a semi-automated installation of chosen sets of external predictors and an interface allowing for easy application of the prediction methods, which can be applied either to individual proteins or to datasets of a large number of proteins. In addition to access to prediction methods, the tools also provide visualization of the obtained results, calculation of consensus from results of different methods, as well as import of experimental data and their comparison with results obtained with different predictors. The tools also offer a graphical user interface and the possibility to store data and the results obtained using all of the integrated methods in the relational database or flat file for further analysis. The MassPred part enables a massive parallel application of all integrated predictors to the set of proteins. Both tools can be downloaded from http://bioinfo.matf.bg.ac.rs/home/downloads.wafl?cat=Software. Appendix A includes the technical description of the created tools and a list of supported predictors.

Epitope distribution in ordered and disordered protein regions. Part B - Ordered regions and disordered binding sites are targets of T- and B-cell immunity.

Intrinsically disordered proteins exist in highly flexible conformational states linked to different protein functions. In this work, we have presented evidence that HLA class-I- and class-II-binding T-cell epitopes, experimentally verified in several tumor-associated antigens and nuclear systemic autoantigens, are predominantly located in ordered protein regions or at disorder/order borderlines, defined by the majority of analyzed publicly available disorder predictors. We have also observed the overlapping of secondary structural elements and prevalently hydrophobic regions with T-cell epitopes in Epstein Barr Virus (EBV) nuclear antigen 1 (EBNA-1), cancer/testis antigen MAGE-A4, and Sm-B/B', U1 snRNPA (U1A) and U1-70kDa autoantigens. The results are in accordance with the clustering of the predicted HLA class-I and class-II epitopes in protein parts which encompass the consensus of ordered regions, determined by individual disorder predictors. Some HLA class-II epitopes and linear B-cell epitopes were located near the segments predicted to have elevated crystallographic B factor in EBNA-1, Sm-B/B' and U1 snRNP A proteins, suggesting that protein flexibility could influence the structural availability of epitopes. Naturally processed T-cell epitopes and linear B-cell epitopes could also be found within putative disordered binding sites, determined by "dips" in the prevalently disordered parts of prediction profiles of the majority of disorder predictors, and peaks in ANCHOR-prediction profile. Two minor antigenic regions within EBNA-1, mapped to the residues 58-85 and 398-458, encompassing putative disordered binding sites, contain epitopes connected with anti-Ro 60kDa and anti-Sm B/B' autoimmunity in systemic lupus erythematosus. One of these regions overlaps residues 395-450, identified as the binding site of USP7 (HAUSP), which regulates the EBNA-1 replication function. In Sm-B/B', one of the putative disordered binding sites (residues 114-165) encompasses the T-cell epitope 136-153, while another, residues 200-216, flanks two proline-rich B-cell epitopes (residues 190-198 and 216-222), overlapping the preferred CD2BP2-GYF-binding motif (R/K/G)XXPPGX(R/K), characteristic of splicosomal proteins. We have noticed that the same motif (residues 397-403) is mimicked in EBNA-1 and overlaps epitope 398-404, involved in anti-Sm B/B' autoimmunity. The majority of recognized T- and B-cell epitopes in analyzed autoantigens or tumor-associated antigens appertain to the ordered or transient protein structures. The congruence between certain B- and T-cell epitopes and predicted disordered binding sites or protein-binding eukaryotic motifs in the antigens participating in molecular complexes might influence the capture of antigens, their processing and subsequent presentation and immunodominance.

Epitope distribution in ordered and disordered protein regions - part A. T-cell epitope frequency, affinity and hydropathy.

Highly disordered protein regions are prevalently hydrophilic, extremely sensitive to proteolysis in vitro, and are expected to be under-represented as T-cell epitopes. The aim of this research was to find out whether disorder and hydropathy prediction methods could help in understanding epitope processing and presentation. According to the pan-specific T-cell epitope predictors NetMHCpan and NetMHCIIpan and 9 publicly available disorder predictors, frequency of epitopes presented by human leukocyte antigens (HLA) class-I or -II was found to be more than 2.5 times higher in ordered than in disordered protein regions (depending on the disorder predictor). Both HLA class-I and HLA class-II binding epitopes are prevalently hydrophilic in disordered and prevalently hydrophobic in ordered protein regions, whereas epitopes recognized by HLA class-II alleles are more hydrophobic than those recognized by HLA class-I. As regards both classes of HLA molecules, high-affinity binding epitopes display more hydrophobicity than low affinity-binding epitopes (in both ordered and disordered regions). Epitopes belonging to disordered protein regions were not predicted to have poor affinity to HLA class-II molecules, as expected from disorder intrinsic proteolytic instability. The relation of epitope hydrophobicity and order/disorder location was also valid if alleles were grouped according to the HLA class-I and HLA class-II supertypes, except for the class-I supertype A3 in which the main part of recognized epitopes was prevalently hydrophilic. Regarding specific supertypes, the affinity of epitopes belonging to ordered regions varies only slightly (depending on the disorder predictor) compared to the affinity of epitopes in corresponding disordered regions. The distribution of epitopes in ordered and disordered protein regions has revealed that the curves of order-epitope distribution were convex-like while the curves of disorder-epitope distribution were concave-like. The percentage of prevalently hydrophobic epitopes increases with the enhancement of epitope promiscuity level and moving from disordered to ordered regions. These data suggests that reverse vaccinology, oriented towards promiscuous and high-affinity epitopes, is also oriented towards prevalently hydrophobic, ordered regions. The analysis of predicted and experimentally evaluated epitopes of cancer-testis antigen MAGE-A3 has confirmed that the majority of T-cell epitopes, particularly those that are promiscuous or naturally processed, was located in ordered and disorder/order boundary protein regions overlapping hydrophobic regions.