Our results demonstrate that prediction of C-terminal antigen processing achieves high accuracy on MHC-I (AUC of 0.91), while it remains challenging for MHC-II (AUC of 0.66). Moreover, we evaluated the performance of NetCleave and one of the most widely used current standards, NetChop3.1, for the evaluation of four independent immunogenicity datasets (H2-Db, H2-Kb, HLA-A*02:01 and HLAB: 07:02). Overall, we demonstrate that NetCleave outperforms NetChop3.1 for the prediction of Cterminal processing, and we provide one of the first evidences that C-terminal processing predictions may help in the discovery of immunogenic peptides.
NetCleave is a bioinformatic tool to aid in protein cleavage predictions by the Proteasome. More in detail, it is an open-source and retrainable algorithm for the prediction of the C-terminal antigen processing for both MHC-I and MHC-II pathways. NetCleave architecture consists of a neural network trained on 46 different physicochemical descriptors of the amino acids forming the cleavage site.
Contact:
License:
MIT License
Primary tabs
