आईएसएसएन: 1745-7580
Guang Lan Zhang, Nikolai Petrovsky, Chee Keong Kwoh, J Thomas August and Vladimir Brusic
Background: The transporter associated with antigen processing (TAP) is a critical component of the major histocompatibility complex (MHC) class I antigen processing and presentation pathway. TAP transports antigenic peptides into the endoplasmic reticulum where it loads them into the binding groove of MHC class I molecules. Because peptides must first be transported by TAP in order to be presented on MHC class I, TAP binding preferences should impact significantly on T-cell epitope selection. Description: PREDTAP is a computational system that predicts peptide binding to human TAP. It uses artificial neural networks and hidden Markov models as predictive engines. Extensive testing was performed to valid the prediction models. The results showed that PREDTAP was both sensitive and specific and had good predictive ability (area under the receiver operating characteristic curve Aroc>0.85). Conclusion: PREDTAP can be integrated with prediction systems for MHC class I binding peptides for improved performance of in silico prediction of T-cell epitopes. PREDTAP is available for public use at [1].