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Related Experiment Video

Updated: May 10, 2025

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

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TRAIT: A Comprehensive Database for T-cell Receptor-antigen Interactions.

Mengmeng Wei^1,2, Jingcheng Wu¹, Shengzuo Bai¹

¹State Key Laboratory of Advanced Drug Delivery and Release Systems & Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.

Genomics, Proteomics & Bioinformatics

|April 21, 2025

Summary

This summary is machine-generated.

A new database, TRAIT, offers comprehensive T-cell receptor (TCR)-antigen interaction data. This resource integrates sequences, structures, and affinities to advance T-cell immunotherapies and vaccine design.

Keywords:

Antigen recognition Mutation Single-cell omics T-cell receptor–antigen interaction T-cell-based immunotherapy

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Published on: October 25, 2016

Area of Science:

Immunology
Bioinformatics
Computational Biology

Background:

Existing resources for T-cell receptor (TCR)-antigen interactions are insufficient for advancing adoptive T-cell immunotherapies.
Understanding TCR-antigen recognition mechanisms is crucial for developing effective immunotherapies.

Purpose of the Study:

To introduce the T-cell receptor-antigen interaction database (TRAIT), a novel, integrated resource for TCR-antigen interactions.
To provide a comprehensive platform for studying TCR-antigen recognition, aiding in T-cell immunotherapy and vaccine development.

Main Methods:

Integrated TCR sequences, structures, and affinities from experimental data.
Utilized single-cell omics data as a primary source for TCR-antigen interactions.
Included data on TCR-antigen mutations and TCRs from clinical trials.

Main Results:

Developed TRAIT, a database profiling millions of experimentally validated TCR-antigen pairs.
TRAIT provides an exhaustive landscape of antigen-specific TCRs, including non-interactive TCRs.
The database details TCR-antigen interactions, including effects of mutations, supporting affinity maturation and vaccine design.

Conclusions:

TRAIT offers a unique and comprehensive resource for TCR-antigen interactions, crucial for T-cell based immunotherapies.
The database is expected to drive advancements in algorithms and therapies by elucidating complex TCR-antigen recognition.
TRAIT is freely accessible, promoting research and development in immunology and immunotherapy.