Supporting data for "epitopepredict: A tool for integrated MHC binding prediction"

A key step in the cellular adaptive immune response is the presentation of antigen to T cells. During this process, short peptides processed from self or foreign proteins may be presented on the surface-bound to MHC molecules for binding to T cell receptors. Those that bind and activate an immune response are called epitopes. Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics. This is the basis of immunoinformatics which allows <i>in silico</i> screening of peptides before experiments are performed. The most effective approach is to estimate the binding affinity of a given peptide fragment to MHC class I or II molecules. With the availability of whole genomes for many microbial species, it is now feasible to computationally screen whole proteomes for candidate peptides. epitopepredict is a programmatic framework and command-line tool designed to aid this process. It provides access to multiple binding prediction algorithms under a single interface and scales for whole genomes using multiple target MHC alleles. A web interface is provided to assist visualization and filtering of the results. The software is freely available under an open-source license from GitHub.