ArticleGenomics, proteomics & bioinformatics2025
TRAIT: A Comprehensive Database for T-cell Receptor-antigen Interactions.
Article in Genomics, proteomics & bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- TCRBinder: Unified pre-trained language model with paired-chain synergy for predicting T-cell receptor binding specificity.PLoS computational biology · 2026Article
- AI-driven computational methods and benchmarking for T-cell antigen identification.Briefings in bioinformatics · 2026Review
- Multi-centered T cell repertoire profiling identifies alterations in the immune repertoire of individuals with inflammatory bowel disease across different disease stages.Genome medicine · 2026Article
- ProTCR: a protein language model-driven framework for decoding TCR-antigen recognition toward precision immunotherapies.Briefings in bioinformatics · 2026Article
- scMOVIR: a single-cell multi-omics database for human viral infections and immune responses.Nucleic acids research · 2026Article
- Differentiation-induced reduction in functional diversity restricts the ability of cytomegalovirus-specific CD8 T cells to eliminate virus-infected cells.EBioMedicine · 2026Article
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Authors and funding
12 authors.
Funding
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Abstract
Comprehensive and integrated resources on interactions between T-cell receptors (TCRs) and antigens are still lacking for adoptive T-cell-based immunotherapies, highlighting a significant gap that must be addressed to fully understand the mechanisms of antigen recognition by T cells. In this study, we present the T-cell receptor-antigen interaction database (TRAIT), a comprehensive database that profiles the interactions between TCRs and antigens. TRAIT stands out due to its comprehensive description of TCR-antigen interactions by integrating sequences, structures, and affinities. It provides millions of experimentally validated TCR-antigen pairs, resulting in an exhaustive landscape of antigen-specific TCRs. Notably, TRAIT emphasizes single-cell omics as a major reliable data source for TCR-antigen interactions and includes millions of reliable non-interactive TCRs. Additionally, it thoroughly demonstrates the interactions between mutations of TCRs and antigens, thereby benefiting affinity optimization of engineered TCRs as well as vaccine design. TCRs on clinical trials are innovatively provided. With the significant efforts made toward elucidating the complex interactions between TCRs and antigens, TRAIT is expected to ultimately contribute superior algorithms and substantial advancements in the field of T-cell-based immunotherapies. TRAIT is freely accessible at https://pgx.zju.edu.cn/traitdb.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.