TAP Hunter: a SVM-based system for predicting TAP ligands using local description of amino acid sequence

BACKGROUND Selective peptide transport by the transporter associated with antigen processing (TAP) represents one of the main candidate mechanisms that may regulate the presentation of antigenic peptides to HLA class I molecules. Because TAP-binding preferences may significant impact T-cell epitope selection, there is great interest in applying computational techniques to systematically discover these elements. RESULTS We describe TAP Hunter, a web-based computational system for predicting TAP-binding peptides. A novel encoding scheme, based on representations of TAP peptide fragments and composition effects, allows the identification of variable-length TAP ligands using SVM as the prediction engine. The system was rigorously trained and tested using 613 experimentally verified peptide sequences. The results showed that the system has good predictive ability with area under the receiver operating characteristics curve (AROC) ≥0.88. In addition, TAP Hunter is compared against several existing public available TAP predictors and has showed either superior or comparable performance. CONCLUSIONS TAP Hunter provides a reliable platform for predicting variable length peptides binding onto the TAP transporter. To facilitate the usage of TAP Hunter to the scientific community, a simple, flexible and user-friendly web-server is developed and freely available at http://datam.i2r.a-star.edu.sg/taphunter/.