PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions

摘要

BackgroundMany different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples are MHC-peptide complexes in the immune system. Developing computational methods for protein-peptide binding prediction is therefore an important task with applications to vaccine and drug design.