Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Front Immunol. 2024 Jul 18;15:1411614. doi: 10.3389/fimmu.2024.1411614. eCollection 2024.
T cell receptors (TCRs) play crucial roles in regulating T cell response by rapidly and accurately recognizing foreign and non-self antigens. The process involves multiple molecules and regulatory mechanisms, forming a complex network to achieve effective antigen recognition. Mathematical modeling techniques can help unravel the intricate network of TCR signaling and identify key regulators that govern it. In this review, we introduce and briefly discuss relevant mathematical models of TCR initial triggering, with a focus on kinetic proofreading (KPR) models with different modified structures. We compare the topology structures, biological hypotheses, parameter choices, and simulation performance of each model, and summarize the advantages and limitations of them. Further studies on TCR modeling design, aiming for an optimized balance of specificity and sensitivity, are expected to contribute to the development of new therapeutic strategies.
T 细胞受体 (TCRs) 通过快速准确地识别外来和非自身抗原，在调节 T 细胞反应中发挥着关键作用。这一过程涉及多个分子和调节机制，形成一个复杂的网络以实现有效的抗原识别。数学建模技术可以帮助揭示 TCR 信号转导的复杂网络，并确定控制它的关键调节剂。在这篇综述中，我们介绍并简要讨论了 TCR 初始触发的相关数学模型，重点介绍了具有不同修改结构的动力学校验 (KPR) 模型。我们比较了每个模型的拓扑结构、生物学假设、参数选择和模拟性能，并总结了它们的优缺点。进一步的 TCR 建模设计研究，旨在优化特异性和敏感性之间的平衡，有望为新的治疗策略的发展做出贡献。
