Structure-aware Multi-task Collaborative Learning (SaMCL) framework accurately predicts peptide-protein interactions and binding domains.
Structure-aware Multi-task Collaborative Learning: a multi-task collaborative learning framework for peptide-protein interaction prediction based on structure-aware protein language models.
Abstract
SaMCL, a novel computational framework, accurately predicts peptide-protein interactions and binding domains, outperforming state-of-the-art methods in accuracy and generalization.