GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models

T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep generative models have demonstrated remarkable capabilities in functional protein sequence generation, offering a promising solution for enhancing the acquisition of specific TCR sequences. Here, we propose GRATCR, a framework incorporates two pre-trained modules through a novel "grafting" strategy, to de-novo generate TCR sequences targeting specific epitopes. Experimental results demonstrate that TCRs generated by GRATCR exhibit higher specificity toward desired epitopes and are more biologically functional compared with the state-of-the-art model, by using significantly fewer training data. Additionally, the generated sequences display novelty compared to natural sequences, and the interpretability evaluation further confirmed that the model is capable of capturing important binding patterns.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2025-02-10
DOI
https://doi.org/10.1109/jbhi.2024.3514089
Citations
10
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
8.06

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article

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models

Liang Hong, Zhenghong Zhou, Yi Xiong, Dong‐Qing Wei et al.
10 citations
IEEE Journal of Biomedical and Health Informatics
vaccines and immunoinformatics approaches
8.06
article

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models

Liang Hong, Zhenghong Zhou, Yi Xiong, Dong‐Qing Wei, S L Lin, Junwei Chen
article en
10 citations

Abstract

T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep generative models have demonstrated remarkable capabilities in functional protein sequence generation, offering a promising solution for enhancing the acquisition of specific TCR sequences. Here, we propose GRATCR, a framework incorporates two pre-trained modules through a novel "grafting" strategy, to de-novo generate TCR sequences targeting specific epitopes. Experimental results demonstrate that TCRs generated by GRATCR exhibit higher specificity toward desired epitopes and are more biologically functional compared with the state-of-the-art model, by using significantly fewer training data. Additionally, the generated sequences display novelty compared to natural sequences, and the interpretability evaluation further confirmed that the model is capable of capturing important binding patterns.

IEEE Journal of Biomedical and Health InformaticsVol. 29(3)
Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
vaccines and immunoinformatics approaches
8.06
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GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models — Liang Hong, Zhenghong Zhou, et al. · IEEE Journal of Biomedical and Health Informatics (2025) | TGRS Research Map | TGRS