CKG-TPI: integrating collaborative knowledge graph with sequence interactions for TCR-peptide binding specificity.

ABSTRACT: Accurately identifying interactions between T-cell receptors (TCRs) and peptides is a fundamental challenge in immunology, with significant implications for vaccine design and immunotherapy. While computational methods offer efficient alternatives to labor-intensive experimental screening, achieving robust and accurate TCR-peptide binding prediction remains a challenging task. To address this, we propose collaborative knowledge graph (CKG-TPI), a novel prediction framework based on graph neural networks that integrates both interaction patterns between TCR and peptide sequences and their higher-order biological context through a constructed collaborative knowledge graph. Experimental results on multiple publicly available independent datasets demonstrate that CKG-TPI consistently outperfor

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12451105 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature