CPPIF: A multi-objective comprehensive framework for predicting protein-peptide interactions and binding residues
In this work, we developed a multi-objective comprehensive framework, called CPPIF, to predict both binary protein-peptide interaction and their binding residues. We also constructed a benchmark dataset containing more than 8,900 protein-peptide interacting pairs with non-covalent interactions and their corresponding binding residues to systematically evaluate the performances of existing models. Comprehensive evaluation on the benchmark datasets demonstrated that CPPIF can successfully predict the non-covalent protein-peptide interactions that cannot be effectively captured by previous prediction methods. Moreover, CPPIF outperformed other state-of-the-art methods in predicting binding residues in the peptides and achieved good performance in the identification of important binding residues in the proteins.
For further questions or details, reach out to Ruheng Wang ([email protected])