Customized Predictions of Peptide–MHC Binding and T-Cell Epitopes Using EPIMHC

Molero-Abraham, Magdalena; Lafuente, Esther M.; Reche, Pedro A.

doi:10.1007/978-1-4939-1115-8_18

Cited by 9 publications

(4 citation statements)

References 32 publications

(27 reference statements)

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“…Data-driven methods for peptide-MHC binding prediction are based on peptide sequences that are known to bind to MHC molecules. These peptide sequences are generally available in specialized epitope databases such as IEDB [ 15 ], EPIMHC [ 16 ], Antijen [ 17 , 18 ]. Both MHC I and II binding peptides contain frequently occurring amino acids at particular peptide positions, known as anchor residues.…”

Section: T-cell Epitope Predictionmentioning

confidence: 99%

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Sanchez-Trincado

Gómez-Perosanz

Reche

2017

Journal of Immunology Research

419

390

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Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate antigens known as epitopes. There is great interest in identifying epitopes in antigens for a number of practical reasons, including understanding disease etiology, immune monitoring, developing diagnosis assays, and designing epitope-based vaccines. Epitope identification is costly and time-consuming as it requires experimental screening of large arrays of potential epitope candidates. Fortunately, researchers have developed in silico prediction methods that dramatically reduce the burden associated with epitope mapping by decreasing the list of potential epitope candidates for experimental testing. Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.

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Section: T-cell Epitope Predictionmentioning

confidence: 99%

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Sanchez-Trincado

Gómez-Perosanz

Reche

2017

Journal of Immunology Research

419

390

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“…CD8 T cell epitope prediction methods are widely regarded as the most accurate and yet only 10% of predicted T cell epitopes are found to be immunogenic [36]. To bypass this problem, we formulated an epitope vaccine ensemble for HCMV through a computer-assisted approach that feeds on previously identified epitopes readily available in specialized databases [37–40]. Clearly, the main advantage of this approach is the saving of time and resources as it depends on experimentally-validated epitopes.…”

Section: Discussionmentioning

confidence: 99%

Computational assembly of a human Cytomegalovirus vaccine upon experimental epitope legacy

et al. 2019

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BackgroundHuman 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.ResultsWe 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.ConclusionsWe 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.

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“…(iii) were included in the EPIMHC database ( 51 ), which collected datasets of T cell response against epitope candidates. In this database, non-immunogenic peptides were selected by applying the following parameters: Allele, HLA A0201; Length, 9mer; MHC source, Human; Peptide source organism, HIV1; Peptide Binding Level, all; T-cell activity, all; Immunogenicity level, all; Processing, all.…”

Section: Methodsmentioning

confidence: 99%

Proteasome-Generated cis-Spliced Peptides and Their Potential Role in CD8+ T Cell Tolerance

et al. 2021

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The human immune system relies on the capability of CD8+ T cells to patrol body cells, spot infected cells and eliminate them. This cytotoxic response is supposed to be limited to infected cells to avoid killing of healthy cells. To enable this, CD8+ T cells have T Cell Receptors (TCRs) which should discriminate between self and non-self through the recognition of antigenic peptides bound to Human Leukocyte Antigen class I (HLA-I) complexes—i.e., HLA-I immunopeptidomes—of patrolled cells. The majority of these antigenic peptides are produced by proteasomes through either peptide hydrolysis or peptide splicing. Proteasome-generated cis-spliced peptides derive from a given antigen, are immunogenic and frequently presented by HLA-I complexes. Theoretically, they also have a very large sequence variability, which might impinge upon our model of self/non-self discrimination and central and peripheral CD8+ T cell tolerance. Indeed, a large variety of cis-spliced epitopes might enlarge the pool of viral-human zwitter epitopes, i.e., peptides that may be generated with the exact same sequence from both self (human) and non-self (viral) antigens. Antigenic viral-human zwitter peptides may be recognized by CD8+ thymocytes and T cells, induce clonal deletion or other tolerance processes, thereby restraining CD8+ T cell response against viruses. To test this hypothesis, we computed in silico the theoretical frequency of zwitter non-spliced and cis-spliced epitope candidates derived from human proteome (self) and from the proteomes of a large pool of viruses (non-self). We considered their binding affinity to the representative HLA-A*02:01 complex, self-antigen expression in Medullary Thymic Epithelial cells (mTECs) and the relative frequency of non-spliced and cis-spliced peptides in HLA-I immunopeptidomes. Based on the present knowledge of proteasome-catalyzed peptide splicing and neglecting CD8+ TCR degeneracy, our study suggests that, despite their frequency, the portion of the cis-spliced peptides we investigated could only marginally impinge upon the variety of functional CD8+ cytotoxic T cells (CTLs) involved in anti-viral response.

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Customized Predictions of Peptide–MHC Binding and T-Cell Epitopes Using EPIMHC

Cited by 9 publications

References 32 publications

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Computational assembly of a human Cytomegalovirus vaccine upon experimental epitope legacy

Proteasome-Generated cis-Spliced Peptides and Their Potential Role in CD8+ T Cell Tolerance

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