Welcome to DLpMHCII
The recognition of antigenic peptides presented by MHC-II molecules and targeted by CD4+ T cells remains a formidable challenge in the field of personalized tumor immunotherapy, due to the polymorphism of MHC-II genes, the immense diversity of MHC-II binding motifs, and the complexity of the MHC-II antigen presentation pathway. In this study, we present DLpMHCII (https://github.com/JiangBiolab/DLpMHCII), a deep learning computational framework based on attention mechanisms, designed to predict the likelihood of interactions between MHC-II alleles and antigenic peptides. This model efficiently screens CD4+ T cell epitopes that can serve as therapeutic targets in infectious diseases, autoimmune disorders, and cancer immunotherapy.
