Investigating TCR-pMHC interactions for TCRs without identified epitopes by constructing a computational pipeline
Kaiyuan Song1, Honglin Xu2, Yi Shi3
1Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China.
International Journal of Biological Macromolecules
|October 18, 2024
Summary
This study introduces a computational method to identify T cell receptor (TCR) epitopes using single-cell sequencing and structural data. It successfully mapped SARS-CoV-2 epitopes for TCRs, aiding in the development of TCR-based therapies.
Area of Science:
- Immunology
- Computational Biology
- Structural Biology
Background:
- T cell receptor (TCR) epitope recognition is vital for immune responses and TCR-based therapeutics.
- Single-cell sequencing generates vast TCR data, but limited TCR-pMHC structures hinder analysis.
- Investigating TCRs without known epitopes requires advanced computational strategies.
Purpose of the Study:
- To develop and validate a computational pipeline for identifying TCR epitopes using integrated structural and single-cell sequencing data.
- To investigate epitope recognition mechanisms for TCRs lacking identified epitopes.
- To facilitate the rational design and optimization of TCR-based therapeutics.
Main Methods:
- Developed a computational pipeline combining structural information and single-cell sequencing data.
- Employed antigen specificity clustering to map epitopes between known and unknown TCRs.
- Utilized molecular dynamics (MD) simulations to elucidate detailed epitope-recognition mechanisms.
Main Results:
- Successfully mapped a known SARS-CoV-2 epitope (NQKLIANQF) to a specific TCR (TCR-614).
- Identified a potential cross-reactive epitope (KLKTLVATA) for another TCR (TCR-204).
- MD simulations confirmed structural motifs consistent with sequence-based clustering findings.
Conclusions:
- The proposed computational strategy effectively identifies TCR epitopes and elucidates recognition mechanisms.
- This approach can accelerate the discovery and optimization of TCR-based immunotherapies.
- The findings provide insights into TCR-epitope interactions relevant to infectious diseases and cancer therapy.
