MHCherryPan. a novel model to predict the binding affinity of pan-specific class I HLA-peptide

The human leukocyte antigen (HLA) system or complex plays an essential role in regulating the immune system in humans. Accurate prediction of peptide binding with HLA can efficiently help to identify those neoantigens which potentially make a big difference in immune drug development. HLA is one of the most polymorphic genetic systems in humans and thousands of HLA allelic versions exist [1]. Due to the high polymorphism of the HLA complex, it remains difficulties to accurately predict the binding affinity. In this paper, we present a new algorithm to combine a convolutional neural network and long short-term memory to solve this problem. Compared with other current popular models, our model achieved state-of the-art results.