全MHC和跨物种预测T细胞受体-抗原结合的T细胞受体-抗原结合
bioRxiv : the preprint server for biology
|December 18, 2023
概括
我们开发了pMTnet-omni,这是一个人工智能系统,可以准确预测T细胞受体 (TCR) 与-MHC复合体的相互作用. 该工具推进了基于TCR的免疫疗法,并预测了癌症治疗的不良事件.
科学领域:
- 免疫学 免疫学 免疫学
- 生物信息学是一种生物信息学.
- 人工智能的人工智能
背景情况:
- 预测T细胞受体 (TCR) 与-MHC (pMHC) 复合体的结合对于理解免疫反应至关重要,但在实验上具有挑战性.
- 目前用于探测TCR-pMHC相互作用的现有方法受到速度,成本和吞吐量的限制.
结论:
- pMTnet-omni代表了人工智能在TCR-pMHC配对预测方面的重大进步.
- 该工具有可能有助于设计和实施基于TCR的免疫疗法.
- 这种人工智能系统更接近于个性化癌症治疗策略的临床可用性.
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