EBVdb: a data mining system for knowledge discovery in Epstein-Barr virus with applications in T cell immunology and vaccinology

摘要

As the first cancer-causing human virus identified, Epstein-Barr virus (EBV) has been implicated in the development of a wide range of B cell lymphoproliferative disorders, a subset of T/NK cell lymphomas, and post-transplant lymphoproliferative disorders. We made use of the immunological data on EBV available through publications, technical reports, and databases and constructed Epstein-Barr virus T cell Antigen Database (EBVdb). EBVdb contains 2622 curated antigen entries of EBV antigenic proteins, 610 verified T cell epitopes and 26 verified HLA ligands. The data were subject to extensive quality control (redundancy elimination, error detection, and vocabulary consolidation). A set of computational tools for in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, T cell epitope/HLA ligand visualization, T cell epitope/HLA ligand conservation analysis, and sequence variability analysis, have been integrated within the EBVdb. Predicted Class I and Class II HLA-binding peptides for 15 common HLA alleles are included in this database as putative targets. EBVdb seamlessly integrates curated data and information with tailored analysis tools to facilitate data mining for EBV vaccinology and immunology. EBVdb is a unique data source providing a comprehensive list of EBV antigens and peptides and is publicly available at http://projects.met-hilab.org/ebv/.