Nafiz Abeer, a senior Ph.D student in the BioMLSP lab, has recently presented his work on TCR-pMHC binding prediction at the 16th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2025), the flagship conference of ACM SIGBio. His poster presentation has been selected by the ACM-BCB 2025 Poster Chairs for the Best Poster Award.

Understanding the interaction between the T-cell receptor (TCR) and the peptide-major histocompatibility complex (pMHC) is a crucial step in T-cell activation and the initiation of the T-cell mediated adaptive immune response. Despite efforts in developing various computational approaches for TCR-pMHC binding prediction, identifying TCR recognition for new peptides forming pMHCs on the surface of antigen-presenting cells (APCs) remains a critical challenge. In his work, Nafiz proposed a novel dual encoder strategy to effectively leverage predicted TCR-pMHC complex structures, thereby achieving better prediction performance for peptides that were not observed during training. His findings demonstrate that the dual-encoder-based approach often improves prediction performance (especially for EGNN) over existing single-encoder-based schemes.