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The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

We established The Cancer Epitope Database and Analysis Resource (CEDAR) to catalog all epitope data in the context of cancer. The specific molecular targets of adaptive T cell and B cell immune responses are referred to as epitopes. Epitopes derived from cancer antigens are of high relevance as they are recognized by anti-cancer immune cells. Detailed knowledge of the molecular characteristic of cancer epitopes and associated metadata is relevant to understanding and planning prophylactic and therapeutic applications and accurately characterizing naturally occurring immune responses and cancer immunopathology. CEDAR provides a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature and serves as a companion site to the Immune Epitope Database (IEDB), which is focused on infectious, autoimmune, and allergic diseases. CEDAR is freely accessible at https://cedar.iedb.org/., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: COVID-19 mRNA vaccines have proven to be highly safe and effective. Myocarditis is an adverse event associated with mRNA vaccination, especially in young male subjects. These events are rare and, in the majority of cases, resolve quickly. As myocarditis can be driven by autoimmune responses, we wanted to determine if the SARS-CoV-2 spike protein antigen encoded in the mRNA COVID vaccines had potential cross-reactivity with auto-antigens previously associated with myocarditis., Methods: We performed a sequence identity comparison between SARS-CoV-2 spike protein-derived peptides and myocarditis-associated antigens. We also performed a structural analysis of these antigens and the SARS-CoV-2 spike protein to identify potential discontinuous 3-D epitope similarities., Findings: We found no significant enrichment in the frequency of spike-derived peptides similar to myocarditis-associated antigens as compared to several controls., Interpretation: Our results do not support the notion that increased occurrence of myocarditis after SARS-CoV-2-spike vaccination is mediated by a cross-reactive adaptive immune response., Competing Interests: Declaration of interests DM has nothing to disclose. JM has nothing to disclose. AS has participated in a Moderna Advisory Board. BP has nothing to disclose., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

The Immune Epitope Database and Analysis Resource (IEDB) contains information related to antibodies and T cells across an expansive scope of research fields (infectious diseases, allergy, autoimmunity, and transplantation). Capture and representation of the data to reflect growing scientific standards and techniques have required continual refinement of our rigorous curation and query and reporting processes beginning with the automated classification of over 28 million PubMed abstracts, and resulting in easily searchable data from over 20,000 published manuscripts. Data related to MHC binding and elution, nonpeptidics, natural processing, receptors, and 3D structure is first captured through manual curation and subsequently maintained through recuration to reflect evolving scientific standards. Upon promotion to the free, public database, users can query and export records of specific relevance via the online web portal which undergoes iterative development to best enable efficient data access. In parallel, the companion Analysis Resource site hosts a variety of tools that assist in the bioinformatic analyses of epitopes and related structures, which can be applied to IEDB-derived and independent datasets alike. Available tools are classified into two categories: analysis and prediction. Analysis tools include epitope clustering, sequence conservancy, and more, while prediction tools cover T and B cell epitope binding, immunogenicity, and TCR/BCR structures. In addition to these tools, benchmarking servers which allow for unbiased performance comparison are also offered. In order to expand and support the user-base of both the database and Analysis Resource, the research team actively engages in community outreach through publication of ongoing work, conference attendance and presentations, hosting of user workshops, and the provision of online help. This review provides a description of the IEDB database infrastructure, curation and recuration processes, query and reporting capabilities, the Analysis Resource, and our Community Outreach efforts, including assessment of the impact of the IEDB across the research community.

Background: Treatment of autoimmune diseases has relied on broad immunosuppression. Knowledge of specific interactions between human leukocyte antigen (HLA), the autoantigen, and effector immune cells, provides the foundation for antigen-specific therapies. These studies investigated the role of HLA, specific myeloperoxidase (MPO) epitopes, CD4 + T cells, and ANCA specificity in shaping the immune response in patients with anti-neutrophil cytoplasmic autoantibody (ANCA) vasculitis., Methods: HLA sequence-based typing identified enriched alleles in our patient population (HLA-DPB1*04:01 and HLA-DRB4*01:01), while in silico and in vitro binding studies confirmed binding between HLA and specific MPO epitopes. Class II tetramers with MPO peptides were utilized to detect autoreactive CD4 + T cells. TCR sequencing was performed to determine the clonality of T cell populations. Longitudinal peptide ELISAs assessed the temporal nature of anti-MPO 447-461 antibodies. Solvent accessibility combined with chemical modification determined the buried regions of MPO., Results: We identified a restricted region of MPO that was recognized by both CD4 + T cells and ANCA. The autoreactive T cell population contained CD4 + CD25 intermediate CD45RO+ memory T cells and secreted IL-17A. T cell receptor (TCR) sequencing demonstrated that autoreactive CD4 + T cells had significantly less TCR diversity when compared to naïve and memory T cells, indicating clonal expansion. The anti-MPO 447-461 autoantibody response was detectable at onset of disease in some patients and correlated with disease activity in others. This region of MPO that is targeted by both T cells and antibodies is not accessible to solvent or chemical modification, indicating these epitopes are buried., Conclusions: These observations reveal interactions between restricted MPO epitopes and the adaptive immune system within ANCA vasculitis that may inform new antigen-specific therapies in autoimmune disease while providing insight into immunopathogenesis., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets., Results: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need., Conclusions: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre .

The utility of autologous induced pluripotent stem cell (iPSC) therapies for tissue regeneration depends on reliable production of immunologically silent functional iPSC derivatives. However, rejection of autologous iPSC-derived cells has been reported, although the mechanism underlying rejection is largely unknown. We hypothesized that de novo mutations in mitochondrial DNA (mtDNA), which has far less reliable repair mechanisms than chromosomal DNA, might produce neoantigens capable of eliciting immune recognition and rejection. Here we present evidence in mice and humans that nonsynonymous mtDNA mutations can arise and become enriched during reprogramming to the iPSC stage, long-term culture and differentiation into target cells. These mtDNA mutations encode neoantigens that provoke an immune response that is highly specific and dependent on the host major histocompatibility complex genotype. Our results reveal that autologous iPSCs and their derivatives are not inherently immunologically inert for autologous transplantation and suggest that iPSC-derived products should be screened for mtDNA mutations.

The Immune Epitope Database (IEDB, iedb.org) captures experimental data confined in figures, text and tables of the scientific literature, making it freely available and easily searchable to the public. The scope of the IEDB extends across immune epitope data related to all species studied and includes antibody, T cell, and MHC binding contexts associated with infectious, allergic, autoimmune, and transplant related diseases. Having been publicly accessible for >10 years, the recent focus of the IEDB has been improved query and reporting functionality to meet the needs of our users to access and summarize data that continues to grow in quantity and complexity. Here we present an update on our current efforts and future goals.

Motivation: Datasets that are derived from different studies (e.g. MHC ligand elution, MHC binding, B/T cell epitope screening etc.) often vary in terms of experimental approaches, sizes of peptides tested, including partial and or nested overlapping peptides and in the number of donors tested., Results: We present a customized application of the Immune Epitope Database's ImmunomeBrowser tool, which can be used to effectively aggregate and visualize heterogeneous immunological data. User provided peptide sets and associated response data is mapped to a user-provided protein reference sequence. The output consists of tables and figures representing the aggregated data represented by a Response Frequency score and associated estimated confidence interval. This allows the user to visualizing regions associated with dominant responses and their boundaries. The results are presented both as a user interactive javascript based web interface and a tabular format in a selected reference sequence., Availability and Implementation: The 'ImmunomeBrowser' has been a longstanding feature of the IEDB (http://www.iedb.org). The present application extends the use of this tool to work with user-provided datasets, rather than the output of IEDB queries. This new server version of the ImmunomeBrowser is freely accessible at http://tools.iedb.org/immunomebrowser/.

Epitopes identified in large-scale screens of overlapping peptides often share significant levels of sequence identity, complicating the analysis of epitope-related data. Clustering algorithms are often used to facilitate these analyses, but available methods are generally insufficient in their capacity to define biologically meaningful epitope clusters in the context of the immune response. To fulfil this need we developed an algorithm that generates epitope clusters based on representative or consensus sequences. This tool allows the user to cluster peptide sequences on the basis of a specified level of identity by selecting among three different method options. These include the 'clique method', in which all members of the cluster must share the same minimal level of identity with each other, and the 'connected graph method', in which all members of a cluster must share a defined level of identity with at least one other member of the cluster. In cases where it is not possible to define a clear consensus sequence with the connected graph method, a third option provides a novel 'cluster-breaking algorithm' for consensus sequence driven sub-clustering. Herein we demonstrate the tool's clustering performance and applicability using (i) a selection of dengue virus epitopes for the 'clique method', (ii) sets of allergen-derived peptides from related species for the 'connected graph method' and (iii) large data sets of eluted ligand, major histocompatibility complex binding and T-cell recognition data captured within the Immune Epitope Database (IEDB) with the newly developed 'cluster-breaking algorithm'. This novel clustering tool is accessible at http://tools.iedb.org/cluster2/., (© 2018 The Authors. Immunology Published by John Wiley & Sons Ltd.)

Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2., (© 2018 John Wiley & Sons Ltd.)

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true 'machine-actionable interoperability', which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies.

The Immune Epitope Database (IEDB) is a free online resource that has manually curated over 18 500 references from the scientific literature. Our database presents experimental data relating to the recognition of immune epitopes by the adaptive immune system in a structured, searchable manner. In order to be consistent and accurate in our data representation across many different journals, authors and curators, we have implemented several quality control measures, such as curation rules, controlled vocabularies and links to external ontologies and other resources. Ontologies and other resources have greatly benefited the IEDB through improved search interfaces, easier curation practices, interoperability between the IEDB and other databases and the identification of errors within our dataset. Here, we will elaborate on how ontology mapping and usage can be used to find and correct errors in a manually curated database.Database URL: www.iedb.org.

The Immune Epitope Database (IEDB) project incorporates independently developed ontologies and controlled vocabularies into its curation and search interface. This simplifies curation practices, improves the user query experience and facilitates interoperability between the IEDB and other resources. While the use of independently developed ontologies has long been recommended as a best practice, there continues to be a significant number of projects that develop their own vocabularies instead, or that do not fully utilize the power of ontologies that they are using. We describe how we use ontologies in the IEDB, providing a concrete example of the benefits of ontologies in practice., Database Url: www.iedb.org., (© The Author(s) 2017. Published by Oxford University Press.)

A DNA prime/adenovirus boost malaria vaccine encoding Plasmodium falciparum strain 3D7 CSP and AMA1 elicited sterile clinical protection associated with CD8+ T cell interferon-gamma (IFN-γ) cells responses directed to HLA class 1-restricted AMA1 epitopes of the vaccine strain 3D7. Since a highly effective malaria vaccine must be broadly protective against multiple P. falciparum strains, we compared these AMA1 epitopes of two P. falciparum strains (7G8 and 3D7), which differ by single amino acid substitutions, in their ability to recall CD8+ T cell activities using ELISpot and flow cytometry/intracellular staining assays. The 7G8 variant peptides did not recall 3D7 vaccine-induced CD8+ T IFN-γ cell responses in these assays, suggesting that protection may be limited to the vaccine strain. The predicted MHC binding affinities of the 7G8 variant epitopes were similar to the 3D7 epitopes, suggesting that the amino acid substitutions of the 7G8 variants may have interfered with TCR recognition of the MHC:peptide complex or that the 7G8 variant may have acted as an altered peptide ligand. These results stress the importance of functional assays in defining protective epitopes. Clinical Trials Registrations: NCT00870987, NCT00392015., Competing Interests: The authors have declared that no competing interests exist.

Unlabelled: Vaccinia virus (VACV) A27 is a target for viral neutralization and part of the Dryvax smallpox vaccine. A27 is one of the three glycosaminoglycan (GAG) adhesion molecules and binds to heparan sulfate. To understand the function of anti-A27 antibodies, especially their protective capacity and their interaction with A27, we generated and subsequently characterized 7 murine monoclonal antibodies (MAbs), which fell into 4 distinct epitope groups (groups I to IV). The MAbs in three groups (groups I, III, and IV) bound to linear peptides, while the MAbs in group II bound only to VACV lysate and recombinant A27, suggesting that they recognized a conformational and discontinuous epitope. Only group I antibodies neutralized the mature virion in a complement-dependent manner and protected against VACV challenge, while a group II MAb partially protected against VACV challenge but did not neutralize the mature virion. The epitope for group I MAbs was mapped to a region adjacent to the GAG binding site, a finding which suggests that group I MAbs could potentially interfere with the cellular adhesion of A27. We further determined the crystal structure of the neutralizing group I MAb 1G6, as well as the nonneutralizing group IV MAb 8E3, bound to the corresponding linear epitope-containing peptides. Both the light and the heavy chains of the antibodies are important in binding to their antigens. For both antibodies, the L1 loop seems to dominate the overall polar interactions with the antigen, while for MAb 8E3, the light chain generally appears to make more contacts with the antigen., Importance: Vaccinia virus is a powerful model to study antibody responses upon vaccination, since its use as the smallpox vaccine led to the eradication of one of the world's greatest killers. The immunodominant antigens that elicit the protective antibodies are known, yet for many of these antigens, little information about their precise interaction with antibodies is available. In an attempt to better understand the interplay between the antibodies and their antigens, we generated and functionally characterized a panel of anti-A27 antibodies and studied their interaction with the epitope using X-ray crystallography. We identified one protective antibody that binds adjacent to the heparan sulfate binding site of A27, likely affecting ligand binding. Analysis of the antibody-antigen interaction supports a model in which antibodies that can interfere with the functional activity of the antigen are more likely to confer protection than those that bind at the extremities of the antigen., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

The Immune Epitope Database is uniquely positioned to assess the body of research related to immune epitopes, we have manually curated all such published data. Thus, we are able to make observations on the state of these fields of research, as well as aggregate the individual data points to present a clearer picture of the immune response to specific antigens in all studied hosts. Additionally, we are able to identify where conflicts in the literature exist and where publications fall short in terms of identifiable methods and in reproducibility. Here we present guidelines to improve the quality of immune epitope data, which will benefit journals and researchers alike., (© 2015 John Wiley & Sons Ltd.)

The Immune Epitope Database (IEDB) is a repository of published epitope data for infectious diseases, allergy, transplantation and autoimmunity. Herein we provide an introduction to the IEDB search interface, focusing on data related to autoimmune diseases, including alopecia areata (AA). We demonstrate how common questions related can be answered, such as how to search for specific autoantigens, epitope sequences, response types (B- and/or T-cell assays), or host, as well as how to search for epitopes of known major histocompatibility complex restriction and for data related to a specific disease. Our survey of the data found that while as a whole Autoimmunity-specific records represent a significant portion (∼30%); epitopes reported for AA are remarkably few, just 23 epitopes from six antigens. This reveals a significant knowledge gap for AA, and suggests that additional mapping of epitopes and identification of novel AA-associated autoantigens is warranted. Citing recently published examples, we show how bioinformatic, proteomic, and technological advances make it now increasingly feasible to identify epitopes and novel antigens in human disease. The goal herein was to increase awareness of the IEDB as a free resource for the scientific community and to demonstrate its use in finding (existing) and analyzing (prediction) epitope data.

Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given task. To provide a solid basis on which to compare different prediction tools, we here describe a framework for the automated benchmarking of peptide-MHC class I binding prediction tools. The framework runs weekly benchmarks on data that are newly entered into the Immune Epitope Database (IEDB), giving the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding capability. Upon experimental binding validation, these peptides entered the benchmark study., Results: The benchmark has run for 15 weeks and includes evaluation of 44 datasets covering 17 MHC alleles and more than 4000 peptide-MHC binding measurements. Inspection of the results allows the end-user to make educated selections between participating tools. Of the four participating servers, NetMHCpan performed the best, followed by ANN, SMM and finally ARB., Availability and Implementation: Up-to-date performance evaluations of each server can be found online at http://tools.iedb.org/auto_bench/mhci/weekly. All prediction tool developers are invited to participate in the benchmark. Sign-up instructions are available at http://tools.iedb.org/auto_bench/mhci/join., Contact: mniel@cbs.dtu.dk or bpeters@liai.org, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Human RSV is one of the most prevalent viral pathogens of early childhood for which no vaccine is available. Herein we provide an analysis of RSV epitope data to examine its application to vaccine design and development. Our objective was to provide an overview of antigenic coverage, identify critical antibody and T cell determinants, and then analyze the cumulative RSV epitope data from the standpoint of functional responses using a combinational approach to characterize antigenic structure and epitope location. A review of the cumulative data revealed, not surprisingly, that the vast majority of epitopes have been defined for the two major surface antigens, F and G. Antibody and T cell determinants have been reported from multiple hosts, including those from human subjects following natural infection, however human data represent a minority of the data. A structural analysis of the major surface antigen, F, showed that the majority of epitopes defined for functional antibodies (neutralizing and/or protective) were either shown to bind pre-F or to be accessible in both pre- and post-F forms. This finding may have has implications for on-going vaccine design and development. These interpretations are in agreement with previous work and can be applied in the larger context of functional epitopes on the F protein. It is our hope that this work will provide the basis for further RSV-specific epitope discovery and investigation into the nature of antigen conformation in immunogenicity.

The IEDB, www.iedb.org, contains information on immune epitopes--the molecular targets of adaptive immune responses--curated from the published literature and submitted by National Institutes of Health funded epitope discovery efforts. From 2004 to 2012 the IEDB curation of journal articles published since 1960 has caught up to the present day, with >95% of relevant published literature manually curated amounting to more than 15,000 journal articles and more than 704,000 experiments to date. The revised curation target since 2012 has been to make recent research findings quickly available in the IEDB and thereby ensure that it continues to be an up-to-date resource. Having gathered a comprehensive dataset in the IEDB, a complete redesign of the query and reporting interface has been performed in the IEDB 3.0 release to improve how end users can access this information in an intuitive and biologically accurate manner. We here present this most recent release of the IEDB and describe the user testing procedures as well as the use of external ontologies that have enabled it., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Unlabelled: The incidence of infection with any of the four dengue virus serotypes (DENV1 to -4) has increased dramatically in the last few decades, and the lack of a treatment or vaccine has contributed to significant morbidity and mortality worldwide. A recent comprehensive analysis of the human T cell response against wild-type DENV suggested an human lymphocyte antigen (HLA)-linked protective role for CD8(+) T cells. We have collected one-unit blood donations from study participants receiving the monovalent or tetravalent live attenuated DENV vaccine (DLAV), developed by the U.S. National Institutes of Health. Peripheral blood mononuclear cells from these donors were screened in gamma interferon enzyme-linked immunosorbent spot assays with pools of predicted, HLA-matched, class I binding peptides covering the entire DENV proteome. Here, we characterize for the first time CD8(+) T cell responses after live attenuated dengue vaccination and show that CD8(+) T cell responses in vaccinees were readily detectable and comparable to natural dengue infection. Interestingly, whereas broad responses to structural and nonstructural (NS) proteins were observed after monovalent vaccination, T cell responses following tetravalent vaccination were, dramatically, focused toward the highly conserved NS proteins. Epitopes were highly conserved in a vast variety of field isolates and able to elicit multifunctional T cell responses. Detailed knowledge of the T cell response will contribute to the identification of robust correlates of protection in natural immunity and following vaccination against DENV., Importance: The development of effective vaccination strategies against dengue virus (DENV) infection and clinically significant disease is a task of high global public health value and significance, while also being a challenge of significant complexity. A recent efficacy trial of the most advanced dengue vaccine candidate, demonstrated only partial protection against all four DENV serotypes, despite three subsequent immunizations and detection of measurable neutralizing antibodies to each serotype in most subjects. These results challenge the hypothesis that seroconversion is the only reliable correlate of protection. Here, we show that CD8(+) T cell responses in vaccinees were readily detectable and comparable to natural dengue virus infection. Detailed knowledge of the T cell response may further contribute to the identification of robust correlates of protection in natural immunity and vaccination against DENV., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

The IMV envelope protein D8 is an adhesion molecule and a major immunodominant antigen of vaccinia virus (VACV). Here we identified the optimal D8 ligand to be chondroitin sulfate E (CS-E). CS-E is characterized by a disaccharide moiety with two sulfated hydroxyl groups at positions 4' and 6' of GalNAc. To study the role of antibodies in preventing D8 adhesion to CS-E, we have used a panel of murine monoclonal antibodies, and tested their ability to compete with CS-E for D8 binding. Among four antibody specificity groups, MAbs of one group (group IV) fully abrogated CS-E binding, while MAbs of a second group (group III) displayed widely varying levels of CS-E blocking. Using EM, we identified the binding site for each antibody specificity group on D8. Recombinant D8 forms a hexameric arrangement, mediated by self-association of a small C-terminal domain of D8. We propose a model in which D8 oligomerization on the IMV would allow VACV to adhere to heterogeneous population of CS, including CS-C and potentially CS-A, while overall increasing binding efficiency to CS-E.

An analysis to inventory all immune epitope data related to multiple sclerosis (MS) was performed using the Immune Epitope Database (IEDB). The analysis revealed that MS related data represent >20% of all autoimmune data, and that studies of EAE predominate; only 22% of the references describe human data. To date, >5800 unique peptides, analogs, mimotopes, and/or non-protein epitopes have been reported from 861 references, including data describing myelin-containing, as well as non-myelin antigens. This work provides a reference point for the scientific community of the universe of available data for MS-related adaptive immunity in the context of EAE and human disease., (Copyright © 2014 Elsevier B.V. All rights reserved.)

T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4-6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.

The immune system rapidly responds to intracellular infections by detecting MHC class I restricted T-cell epitopes presented on infected cells. It was originally thought that viral peptides are liberated during constitutive protein turnover, but this conflicts with the observation that viral epitopes are detected within minutes of their synthesis even when their source proteins exhibit half-lives of days. The DRiPs hypothesis proposes that epitopes derive from Defective Ribosomal Products (DRiPs), rather than degradation of mature protein products. One potential source of DRiPs is premature translation termination. If this is a major source of DRiPs, this should be reflected in positional bias towards the N-terminus. By contrast, if downstream initiation is a major source of DRiPs, there should be positional bias towards the C-terminus. Here, we systematically assessed positional bias of epitopes in viral antigens, exploiting the large set of data available in the Immune Epitope Database and Analysis Resource. We show a statistically significant degree of positional skewing among epitopes; epitopes from both ends of antigens tend to be under-represented. Centric-skewing correlates with a bias towards class I binding peptides being over-represented in the middle, in parallel with a higher degree of evolutionary conservation.

The recognition of specific epitopes on allergens by antibodies and T cells is a key element in allergic processes. Analysis of epitope data may be of interest for basic immunopathology or for potential application in diagnostics or immunotherapy. The Immune Epitope Database (IEDB) is a freely available repository of epitope data from infectious disease agents, as well as epitopes defined for allergy, autoimmunity, and transplantation. The IEDB curates the experiments associated with each epitope and thus provides a variety of different ways to search the data. This review aims to demonstrate the utility of the IEDB and its query strategies, including searching by epitope structure (peptidic/nonpeptidic), by assay methodology, by host, by the allergen itself, or by the organism from which the allergen was derived. Links to tools for visualization of 3-D structures, epitope prediction, and analyses of B and T cell reactivity by host response frequency score are also highlighted., (Copyright © 2012 S. Karger AG, Basel.)

The immune system has evolved to become highly specialized in recognizing and responding to pathogens and foreign molecules. Specifically, the function of HLA class II is to ensure that a sufficient sample of peptides derived from foreign molecules is presented to T cells. This leads to an important concern in human drug development as the possible immunogenicity of biopharmaceuticals, especially those intended for chronic administration, can lead to reduced efficacy and an undesired safety profile for biological therapeutics. As part of this review, we will highlight the molecular basis of antigen presentation as a key step in the induction of T cell responses, emphasizing the events associated with peptide binding to polymorphic and polygenic HLA class II molecules. We will further review methodologies that predict HLA class II binding peptides and candidate epitopes. We will focus on tools provided by the Immune Epitope Database and Analysis Resource, discussing the basic features of different prediction methods, the objective evaluation of prediction quality, and general guidelines for practical use of these tools. Finally the use, advantages, and limitations of the methodology will be demonstrated in a review of two previous studies investigating the immunogenicity of erythropoietin and timothy grass pollen.

As the amount of biomedical information available in the literature continues to increase, databases that aggregate this information continue to grow in importance and scope. The population of databases can occur either through fully automated text mining approaches or through manual curation by human subject experts. We here report our experiences in populating the National Institute of Allergy and Infectious Diseases sponsored Immune Epitope Database and Analysis Resource (IEDB, http://iedb.org), which was created in 2003, and as of 2012 captures the epitope information from approximately 99% of all papers published to date that describe immune epitopes (with the exception of cancer and HIV data). This was achieved using a hybrid model based on automated document categorization and extensive human expert involvement. This task required automated scanning of over 22 million PubMed abstracts followed by classification and curation of over 13 000 references, including over 7000 infectious disease-related manuscripts, over 1000 allergy-related manuscripts, roughly 4000 related to autoimmunity, and 1000 transplant/alloantigen-related manuscripts. The IEDB curation involves an unprecedented level of detail, capturing for each paper the actual experiments performed for each different epitope structure. Key to enabling this process was the extensive use of ontologies to ensure rigorous and consistent data representation as well as interoperability with other bioinformatics resources, including the Protein Data Bank, Chemical Entities of Biological Interest, and the NIAID Bioinformatics Resource Centers. A growing fraction of the IEDB data derives from direct submissions by research groups engaged in epitope discovery, and is being facilitated by the implementation of novel data submission tools. The present explosion of information contained in biological databases demands effective query and display capabilities to optimize the user experience. Accordingly, the development of original ways to query the database, on the basis of ontologically driven hierarchical trees, and display of epitope data in aggregate in a biologically intuitive yet rigorous fashion is now at the forefront of the IEDB efforts. We also highlight advances made in the realm of epitope analysis and predictive tools available in the IEDB., (© 2012 The Authors. Immunology © 2012 Blackwell Publishing Ltd.)

Background: The Immune Epitope Database (IEDB) project manually curates information from published journal articles that describe immune epitopes derived from a wide variety of organisms and associated with different diseases. In the past, abstracts of scientific articles were retrieved by broad keyword queries of PubMed, and were classified as relevant (curatable) or irrelevant (not curatable) to the scope of the database by a Naïve Bayes classifier. The curatable abstracts were subsequently manually classified into categories corresponding to different disease domains. Over the past four years, we have examined how to further improve this approach in order to enhance classification performance and to reduce the need for manual intervention., Results: Utilizing 89,884 abstracts classified by a domain expert as curatable or uncuratable, we found that a SVM classifier outperformed the previously used Naïve Bayes classifier for curatability predictions with an AUC of 0.899 and 0.854, respectively. Next, using a non-hierarchical and a hierarchical application of SVM classifiers trained on 22,833 curatable abstracts manually classified into three levels of disease specific categories we demonstrated that a hierarchical application of SVM classifiers outperformed non-hierarchical SVM classifiers for categorization. Finally, to optimize the hierarchical SVM classifiers' error profile for the curation process, cost sensitivity functions were developed to avoid serious misclassifications. We tested our design on a benchmark dataset of 1,388 references and achieved an overall category prediction accuracy of 94.4%, 93.9%, and 82.1% at the three levels of categorization, respectively., Conclusions: A hierarchical application of SVM algorithms with cost sensitive output weighting enabled high quality reference classification with few serious misclassifications. This enabled us to significantly reduce the manual component of abstract categorization. Our findings are relevant to other databases that are developing their own document classifier schema and the datasets we make available provide large scale real-life benchmark sets for method developers.

IEDB-3D is the 3D structural component of the Immune Epitope Database (IEDB) available via the 'Browse by 3D Structure' page at http://www.iedb.org. IEDB-3D catalogs B- and T-cell epitopes and Major Histocompatibility Complex (MHC) ligands for which 3D structures of complexes with antibodies, T-cell receptors or MHC molecules are available in the Protein Data Bank (PDB). Journal articles that are primary citations of PDB structures and that define immune epitopes are curated within IEDB as any other reference along with accompanying functional assays and immunologically relevant information. For each curated structure, IEDB-3D provides calculated data on intermolecular contacts and interface areas and includes an application, EpitopeViewer, to visualize the structures. IEDB-3D is fully embedded within IEDB, thus allowing structural data, both curated and calculated, and all accompanying information to be queried using multiple search interfaces. These include queries for epitopes recognized in different pathogens, eliciting different functional immune responses, and recognized by different components of the immune system. The query results can be downloaded in Microsoft Excel format, or the entire database, together with structural data both curated and calculated, can be downloaded in either XML or MySQL formats.

In the last decade, significant progress has been made in expanding the scope and depth of publicly available immunological databases and online analysis resources, which have become an integral part of the repertoire of tools available to the scientific community for basic and applied research. Herein, we present a general overview of different resources and databases currently available. Because of our association with the Immune Epitope Database and Analysis Resource, this resource is reviewed in more detail. Our review includes aspects such as the development of formal ontologies and the type and breadth of analytical tools available to predict epitopes and analyze immune epitope data. A common feature of immunological databases is the requirement to host large amounts of data extracted from disparate sources. Accordingly, we discuss and review processes to curate the immunological literature, as well as examples of how the curated data can be used to generate a meta-analysis of the epitope knowledge currently available for diseases of worldwide concern, such as influenza and malaria. Finally, we review the impact of immunological databases, by analyzing their usage and citations, and by categorizing the type of citations. Taken together, the results highlight the growing impact and utility of immunological databases for the scientific community.

Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical potentials derived from the analysis of known protein structures; energetic evaluation of different peptide snapshots in a molecular dynamics simulation; and direct analysis of contacts made in known 3D structures of peptide:MHC complexes. These methods are ab initio in that they require structural data of the MHC molecule examined, but no specific peptide:MHC binding data. Moreover, these methods retain the ability to make predictions in a sufficiently short time scale to be useful in a real world application, such as screening a whole proteome for candidate binding peptides. A rigorous evaluation of each methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results together in order to support the notion that generating structure based predictions of peptide:MHC binding without using binding data is unlikely to give satisfactory results.

The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180,978 experiments were curated manually from the literature, which covers approximately 99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129,186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009.

A major concern about the ongoing swine-origin H1N1 influenza virus (S-OIV) outbreak is that the virus may be so different from seasonal H1N1 that little immune protection exists in the human population. In this study, we examined the molecular basis for pre-existing immunity against S-OIV, namely the recognition of viral immune epitopes by T cells or B cells/antibodies that have been previously primed by circulating influenza strains. Using data from the Immune Epitope Database, we found that only 31% (8/26) of B-cell epitopes present in recently circulating H1N1 strains are conserved in the S-OIV, with only 17% (1/6) conserved in the hemagglutinin (HA) and neuraminidase (NA) surface proteins. In contrast, 69% (54/78) of the epitopes recognized by CD8(+) T cells are completely invariant. We further demonstrate experimentally that some memory T-cell immunity against S-OIV is present in the adult population and that such memory is of similar magnitude as the pre-existing memory against seasonal H1N1 influenza. Because protection from infection is antibody mediated, a new vaccine based on the specific S-OIV HA and NA proteins is likely to be required to prevent infection. However, T cells are known to blunt disease severity. Therefore, the conservation of a large fraction of T-cell epitopes suggests that the severity of an S-OIV infection, as far as it is determined by susceptibility of the virus to immune attack, would not differ much from that of seasonal flu. These results are consistent with reports about disease incidence, severity, and mortality rates associated with human S-OIV.

Background: A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continually updated by monitoring PubMed for new, potentially relevant references., Methodology: Herein we detail the classification of all epitope-specific literature in over 100 different immunological domains representing Infectious Diseases and Microbes, Autoimmunity, Allergy, Transplantation and Cancer. The relative number of references in each category reflects past and present areas of research on immune reactivities. In addition to describing the overall landscape of data distribution, this particular characterization of the epitope reference data also allows for the exploration of possible correlations with global disease morbidity and mortality data., Conclusions/significance: While in most cases diseases associated with high morbidity and mortality rates were amongst the most studied, a number of high impact diseases such as dengue, Schistosoma, HSV-2, B. pertussis and Chlamydia trachoma, were found to have very little coverage. The data analyzed in this fashion represents the first estimate of how reported immunological data corresponds to disease-related morbidity and mortality, and confirms significant discrepancies in the overall research foci versus disease burden, thus identifying important gaps to be pursued by future research. These findings may also provide a justification for redirecting a portion of research funds into some of the underfunded, critical disease areas.

The IEDB houses antibody and T cell epitope data and makes them accessible and searchable. The curation of literature references requires explicit guidelines in order to capture the data in an objective and consistent manner. Description of these guidelines ensures transparency of the database and facilitates direct submissions to the database.

We have reviewed the information about epitopes of immunological interest from Clostridium botulinum and Bacillus anthracis, by mining the Immune Epitope Database and Analysis Resource. For both pathogens, the vast majority of epitopes reported to date are derived from a single protein: the protective antigen of B. anthracis and the neurotoxin type A of C. botulinum. A detailed analysis of the data was performed to characterize the function, localization and conservancy of epitopes identified as neutralizing and/or protective. In order to broaden the scope of this analysis, we have also included data describing immune responses against defined fragments (over 50 amino acids long) of the relevant antigens. The scarce information on T-cell determinants and on epitopes from other antigens besides the toxins, highlights a gap in our knowledge and identifies areas for future research. Despite this, several distinct structures at the epitope and fragment level are described herein, which could be potential additions to future vaccines or targets of novel immunotherapeutics and diagnostic reagents.

Background: The Immune Epitope Database contains information on immune epitopes curated manually from the scientific literature. Like similar projects in other knowledge domains, significant effort is spent on identifying which articles are relevant for this purpose., Results: We here report our experience in automating this process using Naïve Bayes classifiers trained on 20,910 abstracts classified by domain experts. Improvements on the basic classifier performance were made by a) utilizing information stored in PubMed beyond the abstract itself b) applying standard feature selection criteria and c) extracting domain specific feature patterns that e.g. identify peptides sequences. We have implemented the classifier into the curation process determining if abstracts are clearly relevant, clearly irrelevant, or if no certain classification can be made, in which case the abstracts are manually classified. Testing this classification scheme on an independent dataset, we achieve 95% sensitivity and specificity in the 51.1% of abstracts that were automatically classified., Conclusion: By implementing text classification, we have sped up the reference selection process without sacrificing sensitivity or specificity of the human expert classification. This study provides both practical recommendations for users of text classification tools, as well as a large dataset which can serve as a benchmark for tool developers.

The recognition of immune epitopes is an important molecular mechanism of the vertebrate immune system to discriminate between self and non-self. Increasing amounts of data on immune epitopes are becoming available due to technological advances in epitope-mapping techniques and the availability of genomic information for pathogens. Organizing this data poses a challenge that is similar to the successful effort that was required to organize genomic data, which needed the establishment of centralized databases that complement the primary literature to make the data readily accessible and searchable by researchers. As described in this Innovation article, the Immune Epitope Database and Analysis Resource aims to achieve the same for the more complex and context-dependent information on immune epitopes, and to integrate this data with existing and emerging knowledge resources.

Technological advances have allowed for the creation of ever more complete maps of targets of immune responses in infectious pathogens. The evidence accumulating from such recent studies points to a broader range of targets recognized than previously expected, in terms of both numbers and characteristics of the targeted antigens. Also, multiple studies report a substantial variation in the targets recognized in different human individuals. These findings are not in conflict with the concept of immunodominance, because there are still only a few targets recognized compared with the multitude of potential targets available in a complex pathogen. However, they raise the question if vaccines, which try to emulate protective natural immune responses, should elicit an equally broad range of responses to efficiently convey protection.

Background: The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data http://www.immuneepitope.org., Description: To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation., Conclusion: Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise.

Epitopes are defined as parts of antigens interacting with receptors of the immune system. Knowledge about their intrinsic structure and how they affect the immune response is required to continue development of techniques that detect, monitor, and fight diseases. Their scientific importance is reflected in the vast amount of epitope-related information gathered, ranging from interactions between epitopes and major histocompatibility complex molecules determined by X-ray crystallography to clinical studies analyzing correlates of protection for epitope based vaccines. Our goal is to provide a central resource capable of capturing this information, allowing users to access and connect realms of knowledge that are currently separated and difficult to access. Here, we portray a new initiative, "The Immune Epitope Database and Analysis Resource." We describe how we plan to capture, structure, and store this information, what query interfaces we will make available to the public, and what additional predictive and analytical tools we will provide.

Motivation: Various methods have been proposed to predict the binding affinities of peptides to Major Histocompatibility Complex class I (MHC-I) molecules based on experimental binding data. They can be classified into two groups: (1) AIB methods that assume independent contributions of all peptide positions to the binding to MHC-I molecule (e.g. scoring matrices) and (2) general methods which can take into account interactions between different positions (e.g. artificial neural networks). We aim to compare the prediction accuracies of these methods, and quantify the impact of interactions between peptide positions., Results: We compared several previously published and widely used methods and discovered that the best AIB methods gave significantly better predictions than three previously published general methods, possibly due to the lack of a sufficient training data for the general methods. The best results, however, were achieved with our newly developed general method, which combined a matrix describing independent binding with pair coefficients describing pair-wise interactions between peptide positions. The pair coefficients consistently but only slightly improved prediction accuracy, and were much smaller than the matrix entries. This explains why neglecting them-as is done in AIB methods-can still lead to good predictions., Availability: The new prediction model is implemented at http://zlab.bu.edu/SMM. The underlying matrix and pair coefficients are also available as supplementary materials.

Background Allergens from house dust mites ( HDM) are a common cause of asthma. Der p and Der f from Dermatophagoides sp. are strong immunogens in humans. Allergen extracts are used to study T helper (Th2) cell responses to HDM, which are implicated in the development and regulation of allergic disease. Objective To define an epitope mixture that recapitulates, and might substitute for, HDM extract in terms of detecting and characterizing Th2 cell responses. Methods Peripheral blood mononuclear cells (PBMC) from 52 HDM allergic and 10 non-allergic individuals were stimulated with HDM extracts and assayed with a set of 178 peptides spanning mite allergens group Der p 1, 2, 23 and Der f group 1 and 2 allergens. A pool of the most dominant T cell epitopes identified in the present study and from published literature was assembled and tested for ex vivo T cell responses. Correlation with HDM-specific IgE titres was examined. Results Patterns of T cell reactivity to Der p and Der f - derived peptides revealed a large number of epitopes. Clear patterns of immunodominance were apparent, with HDM allergen group 1 and 2 dominant over group 23. Furthermore, within a given antigen, 6-11 epitopes accounted for the vast majority of responses. Based on these results and published data, a comprehensive dust mite pool ( DMP) of epitopes was designed and found to allow detection of ex vivo T cell responses. DMP ex vivo reactivity correlated with HDM-specific IgE titres and was similar to that detected with commonly used HDM extracts. Ex vivo DMP stimulation was associated with a predominant Th2 response in allergic donors, and minor reactivity of T cells producing IFNγ, IL17 and IL10. Conclusions & Clinical Relevance A detailed map of Der p and Der f antigens defined a pool of epitopes that can be used to detect ex vivo HDM responses. [ABSTRACT FROM AUTHOR]

We present a comprehensive meta-analysis of more than 500 references, describing nearly 5000 unique B cell and T cell epitopes derived from the Plasmodium genus, and detailing thousands of immunological assays. This is the first inventory of epitope data related to malaria-specific immunology, plasmodial pathogenesis, and vaccine performance. The survey included host and pathogen species distribution of epitopes, the number of antibody vs. CD4+ and CD8+ T cell epitopes, the genomic distribution of recognized epitopes, variance among epitopes from different parasite strains, and the characterization of protective epitopes and of epitopes associated with parasite evasion of the host immune response. The results identify knowledge gaps and areas for further investigation. This information has relevance to issues, such as the identification of epitopes and antigens associated with protective immunity, the design and development of candidate malaria vaccines, and characterization of immune response to strain polymorphisms. [ABSTRACT FROM AUTHOR]

Abstract: Non-human primates, in general, and Indian rhesus macaques, specifically, play an important role in the development and testing of vaccines and diagnostics destined for human use. To date, several frequently expressed macaque MHC molecules have been identified and their binding specificities characterized in detail. Here, we report the development of computational algorithms to predict peptide binding and potential T cell epitopes for the common MHC class I alleles Mamu-A*01, -A*02, -A*11, -B*01 and -B*17, which cover approximately two thirds of the captive Indian rhesus macaque populations. We validated this method utilizing an SIV derived data set encompassing 59 antigenic peptides. Of all peptides contained in the SIV proteome, the 2.4% scoring highest in the prediction contained 80% of the antigenic peptides. The method was implemented in a freely accessible and user friendly website at www.mamu.liai.org. Thus, we anticipate that our approach can be utilized to rapidly and efficiently identify CD8+ T cell epitopes recognized by rhesus macaques and derived from any pathogen of interest. [Copyright &y& Elsevier]

Epitopes presented by major histocompatibility complex (MHC) class I molecules are selected by a multi-step process. Here we present the first computational prediction of this process based on in vitro experiments characterizing proteasomal cleavage, transport by the transporter associated with antigen processing (TAP) and MHC class I binding. Our novel prediction method for proteasomal cleavages outperforms existing methods when tested on in vitro cleavage data. The analysis of our predictions for a new dataset consisting of 390 endogenously processed MHC class I ligands from cells with known proteasome composition shows that the immunological advantage of switching from constitutive to immunoproteasomes is mainly to suppress the creation of peptides in the cytosol that TAP cannot transport. Furthermore, we show that proteasomes are unlikely to generate MHC class I ligands with a C-terminal lysine residue, suggesting processing of these ligands by a different protease that may be tripeptidyl-peptidase II (TPPII). [ABSTRACT FROM AUTHOR]