DeepMHCII: a novel binding core-aware deep interaction model for accurate MHC-II peptide binding affinity prediction.

ABSTRACT:

Motivation

Computationally predicting major histocompatibility complex (MHC)-peptide binding affinity is an important problem in immunological bioinformatics. Recent cutting-edge deep learning-based methods for this problem are unable to achieve satisfactory performance for MHC class II molecules. This is because such methods generate the input by simply concatenating the two given sequences: (the estimated binding core of) a peptide and (the pseudo sequence of) an MHC class II molecule, ignoring biological knowledge behind the interactions of the two molecules. We thus propose a binding core-aware deep learning-based model, DeepMHCII, with a binding interaction convolution layer, which allows to integrate all potential binding cores (in a given peptide) with the MHC pseudo (bindin

SUBMITTER: You R 

PROVIDER: S-EPMC9235502 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature