Prediction of MHC-peptide binding: a systematic and comprehensive overview

T cell immune responses are driven by the recognition of peptide antigens (T cell epitopes) that are bound to major histocompatibility complex (MHC) molecules. T cell epitope immunogenicity is thus contingent on several events, including appropriate and effective processing of the peptide from its protein source, stable peptide binding to the MHC molecule, and recognition of the MHC-bound peptide by the T cell receptor. Of these three hallmarks, MHC-peptide binding is the most selective event that determines T cell epitopes. Therefore, prediction of MHC-peptide binding constitutes the principal basis for anticipating potential T cell epitopes. The tremendous relevance of epitope identification in vaccine design and in the monitoring of T cell responses has spurred the development of many computational methods for predicting MHC-peptide binding that improve the efficiency and economics of T cell epitope identification. In this report, we will systematically examine the available methods for predicting MHC-peptide binding and discuss their most relevant advantages and drawbacks

Recognition of the ligand-type specificity of classical and non-classical MHC I proteins.

Functional characterization of proteins belonging to the MHC I superfamily involves knowing their cognate ligands, which can be peptides, lipids or none. However, the experimental identification of these ligands is not an easy task and generally requires some a priori knowledge of their chemical nature (ligand-type specificity). Here, we trained k-nearest neighbor and support vector machine classifiers that predict the ligand-type specificity MHC I proteins with great accuracy. Moreover, we applied these classifiers to human and mouse MHC I proteins of uncharacterized ligands, obtaining some results that can be instrumental to unravel the function of these proteins

Computational analysis and modeling of cleavage by the immunoproteasome and the constitutive proteasome

Proteasomes play a central role in the major histocompatibility class I (MHCI) antigen processing pathway. They conduct the proteolytic degradation of proteins in the cytosol, generating the C-terminus of CD8 T cell epitopes and MHCI-peptide ligands (P1 residue of cleavage site). There are two types of proteasomes, the constitutive form, expressed in most cell types, and the immunoproteasome, which is constitutively expressed in mature dendritic cells. Protective CD8 T cell epitopes are likely generated by the immunoproteasome and the constitutive proteasome, and here we have modeled and analyzed the cleavage by these two proteases. RESULTS: We have modeled the immunoproteasome and proteasome cleavage sites upon two non-overlapping sets of peptides consisting of 553 CD8 T cell epitopes, naturally processed and restricted by human MHCI molecules, and 382 peptides eluted from human MHCI molecules, respectively, using N-grams. Cleavage models were generated considering different epitope and MHCI-eluted fragment lengths and the same number of C-terminal flanking residues. Models were evaluated in 5-fold cross-validation. Judging by the Mathew's Correlation Coefficient (MCC), optimal cleavage models for the proteasome (MCC = 0.43 +/- 0.07) and the immunoproteasome (MCC = 0.36 +/- 0.06) were obtained from 12-residue peptide fragments. Using an independent dataset consisting of 137 HIV1-specific CD8 T cell epitopes, the immunoproteasome and proteasome cleavage models achieved MCC values of 0.30 and 0.18, respectively, comparatively better than those achieved by related methods. Using ROC analyses, we have also shown that, combined with MHCI-peptide binding predictions, cleavage predictions by the immunoproteasome and proteasome models significantly increase the discovery rate of CD8 T cell epitopes restricted by different MHCI molecules, including A*0201, A*0301, A*2402, B*0702, B*2705. CONCLUSIONS: We have developed models that are specific to predict cleavage by the proteasome and the immunoproteasome. These models ought to be instrumental to identify protective CD8 T cell epitopes and are readily available for free public use at http://imed.med.ucm.es/Tools/PCPS

Selection of conserved epitopes from hepatitis C virus for pan-populational stimulation of T-cell responses

The hepatitis C virus (HCV) is able to persist as a chronic infection, which can lead to cirrhosis and liver cancer. There is evidence that clearance of HCV is linked to strong responses by CD8 cytotoxic T lymphocytes (CTLs), suggesting that eliciting CTL responses against HCV through an epitope-based vaccine could prove an effective means of immunization. However, HCV genomic plasticity as well as the polymorphisms of HLA I molecules restricting CD8 T-cell responses challenges the selection of epitopes for a widely protective vaccine. Here, we devised an approach to overcome these limitations. From available databases, we first collected a set of 245 HCV-specific CD8 T-cell epitopes, all known to be targeted in the course of a natural infection in humans. After a sequence variability analysis, we next identified 17 highly invariant epitopes. Subsequently, we predicted the epitope HLA I binding profiles that determine their potential presentation and recognition. Finally, using the relevant HLA I-genetic frequencies, we identified various epitope subsets encompassing 6 conserved HCV-specific CTL epitopes each predicted to elicit an effective T-cell response in any individual regardless of their HLA I background. We implemented this epitope selection approach for free public use at the EPISOPT web server

Computational assembly of a human Cytomegalovirus vaccine upon experimental epitope legacy

Background: Human Cytomegalovirus (HCMV) is a ubiquitous herpesvirus affecting approximately 90% of the world population. HCMV causes disease in immunologically naive and immunosuppressed patients. The prevention, diagnosis and therapy of HCMV infection are thus crucial to public health. The availability of effective prophylactic and therapeutic treatments remain a significant challenge and no vaccine is currently available. Here, we sought to define an epitope-based vaccine against HCMV, eliciting B and T cell responses, from experimentally defined HCMV-specific epitopes. Results: We selected 398 and 790 experimentally validated HCMV-specific B and T cell epitopes, respectively, from available epitope resources and apply a knowledge-based approach in combination with immunoinformatic predictions to ensemble a universal vaccine against HCMV. The T cell component consists of 6 CD8 and 6 CD4 T cell epitopes that are conserved among HCMV strains. All CD8 T cell epitopes were reported to induce cytotoxic activity, are derived from early expressed genes and are predicted to provide population protection coverage over 97%. The CD4 T cell epitopes are derived from HCMV structural proteins and provide a population protection coverage over 92%. The B cell component consists of just 3 B cell epitopes from the ectodomain of glycoproteins L and H that are highly flexible and exposed to the solvent. Conclusions: We have defined a multiantigenic epitope vaccine ensemble against the HCMV that should elicit T and B cell responses in the entire population. Importantly, although we arrived to this epitope ensemble with the help of computational predictions, the actual epitopes are not predicted but are known to be immunogenic

EPIPOX:immunoinformatic characterization of the shared T-cell epitome between variola virus and related pathogenic orthopoxviruses

Concerns that variola viruses might be used as bioweapons have renewed the interest in developing new and safer smallpox vaccines. Variola virus genomes are now widely available, allowing computational characterization of the entire T-cell epitome and the use of such information to develop safe and yet effective vaccines. To this end, we identified 124 proteins shared between various species of pathogenic orthopoxviruses including variola minor and major, monkeypox, cowpox, and vaccinia viruses, and we targeted them for T-cell epitope prediction. We recognized 8,106, and 8,483 unique class I and class II MHC-restricted T-cell epitopes that are shared by all mentioned orthopoxviruses. Subsequently, we developed an immunological resource, EPIPOX, upon the predicted T-cell epitome. EPIPOX is freely available online and it has been designed to facilitate reverse vaccinology. Thus, EPIPOX includes key epitope-focused protein annotations: time point expression, presence of leader and transmembrane signals, and known location on outer membrane structures of the infective viruses. These features can be used to select specific T-cell epitopes suitable for experimental validation restricted by single MHC alleles, as combinations thereof, or by MHC supertypes

Nuclear engineering and technology transfer: The Spanish strategies to deal with US, french and german nuclear manufacturers, 1955–1985

[en]We analysed the process of construction and connection to the electrical grid of four Spanish nuclear power plants with different financial and technological foreign partners: those of Zorita (PWR by Westinghouse), Garoña (BWR by General Electric) and Vandellós I (GCR by EDF) (belonging to the first generation of atomic plants and producing electricity from 1969–72) and that of Trillo I (PWR by KWU, connected in 1988). These four examples allow us to observe how the learning curve of nuclear engineering and the acquisition of skills by Spanish companies evolved. Progressively the domestic industry achieved higher levels of participation, fostered by the Ministry of Industry and Energy. When the atomic plants under construction were paralysed by the nuclear moratorium of 1984, and several other projects were abandoned by the utilities along the way, Spain had developed an industrial sector around the fabrication of service components and engineering for nuclear power plants to compete internationally