Department of Chemistry, SUNY Stony Brook, 100 Nicolls Road, Stony Brook, NY 11794, USA.
Phys Chem Chem Phys. 2021 Feb 4;23(4):2860-2872. doi: 10.1039/d0cp02422h.
The critical role of energy consumption in biological systems including T cell discrimination process has been investigated in various ways. The kinetic proofreading (KPR) in T cell recognition involving different levels of energy dissipation influences functional outcomes such as error rates and specificity. In this work, we study quantitatively how the energy cost influences error fractions, sensitivity, specificity, kinetic speed in terms of Mean First Passage Time (MFPT) and adaption errors. These provide the background to adequately understand T cell dynamics. It is found that energy plays a central role in the system that aims to achieve minimum error fractions and maximum sensitivity and specificity with the fastest speed under our kinetic scheme for which numerical values of kinetic parameters are specially chosen, but such a condition can be broken with varying data. Starting with the application of steady state approximation (SSA) to the evaluation of the concentration of each complex produced associated with KPR, which is used to quantify various observables, we present both analytical and numerical results in detail.
能量消耗在包括 T 细胞识别过程在内的生物系统中的关键作用已通过各种方式进行了研究。T 细胞识别中的动力学校验（KPR）涉及不同水平的能量耗散，影响功能结果，如错误率和特异性。在这项工作中，我们定量研究了能量成本如何影响错误分数、灵敏度、特异性、平均首次通过时间（MFPT）和适应错误的动力学速度。这些为充分理解 T 细胞动力学提供了背景。结果表明，能量在系统中起着核心作用，该系统旨在以我们的动力学方案下实现最小的错误分数和最大的灵敏度和特异性，并具有最快的速度，而动力学参数的数值是专门选择的，但随着数据的变化，这种情况可能会被打破。我们从稳态近似（SSA）在评估与 KPR 相关的每个复合物的浓度中的应用开始，该浓度用于量化各种可观察量，详细介绍了分析和数值结果。
