PROJECT SUMMARY
Immune epitopes--the portions of an antigen that are recognized by antibodies and T-cell receptors--are key to
understanding healthy and abnormal immune responses. The Immune Epitope Database (IEDB) is a freely
available resource funded by the National Institute of Allergy and Infectious Diseases (NIAID) that catalogs
experimental data on more than one million antibody and T cell epitopes studied in humans, non-human
primates, and other animal species in the context of infectious disease, allergy, autoimmunity and
transplantation. As well, there is a wealth of information captured in other biomedical databases that could
potentially be applied to immunological research. The goal of this work is to integrate immune epitope
information from IEDB with the wealth of additional biomedical data in humans and model organisms, thereby
enabling novel opportunities for hypothesis generation and discovery. We will seamlessly connect epitopes to
the protein information in UniProtKB, which contains rich functional annotation and the means to display
protein sequence features, and the Protein Ontology (PRO), which provides orthology information and the
explicit representation of proteoforms. We will make further connections to resources specializing in protein
post-translational modifications (PTMs), protein-protein interactions, human genetic variation, diseases, and
drugs. Display of this information in the UniProt ProtVista environment and via the IEDB website will make it
easily accessible to the large community of immunology and disease researchers. Our work will enable novel
queries of high interest to translational researchers, such as: (1) What PTMs and/or genetic variants overlap
with an epitope of interest? Identification of such overlaps can provide insight into factors that affect
auto-antigenicity or immune evasion by pathogens; (2) Is a human epitope of interest found in
orthologous/homologous proteins in model organisms or vice-versa? This will allow researchers interested in
human disease to fully exploit knowledge derived from model organisms, and conversely, improve disease
models in non-human organisms. It will also enable identification of potential cross-reactivities within and
across organisms; and (3) Are there any druggable targets among the proteins that interact with autoantigenic
proteins associated with an autoimmune disease of interest? This work entails the following specific aims: (i)
Aim 1. Data exchange: Guided by use cases, we will connect epitopes within IEDB to data from PRO, UniProt,
and other informatics resources; (ii) Aim 2. Information access: Guided by user input, we will enhance
navigation, data visualization, and application interfaces at each resource and create connections between
them; and (iii) Aim 3. Community engagement: We will build community awareness of the connected resources
and ensure that the needs of stakeholders are reflected. This collaborative effort among multiple major
resources will overcome barriers to consumption of IEDB data, thereby supporting inquiry into the role of the
immune system in human disease.
